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The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
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Claims 1 – 20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1, 2, 4, 6, 7, 10, 14, 17, and 19 of U.S. Patent No. 11,388,397. Although the claims at issue are not identical, they are not patentably distinct from each other because the scope of the patented case wholly encompasses the scope of the current application.
Current Application
U.S. Patent No. 11,388,397
1. A decoder for picture component prediction, comprising: a memory for storing executable video component prediction instructions; and a processor configured to perform the executable video component prediction instructions stored in the memory to perform following operations: determining a first picture component reference sample set of a current block; determining multiple first picture component reference samples according to the first picture component reference sample set; performing first filtering processing on the multiple first picture component reference samples, to determine multiple filtered first picture reference samples; determining a parameter of a component model according to the multiple filtered first picture reference samples and corresponding to-be-predicted picture component reference samples, a to-be-predicted picture component being a picture component which is different from a first picture component, and the component model characterizing a mapping relationship for mapping a sample of the first picture component to a sample of the to-be-predicted picture component; performing mapping processing on a reconstructed sample of the first picture component of the current block according to the component model to obtain a mapped sample; and determining a predicted sample of the to-be-predicted picture component of the current block according to the mapped sample, wherein determining multiple first picture component reference samples according to the first picture component reference sample set comprises: determining multiple reference samples based on samples in multiple neighboring lines at a top side of the current block according to two preset positions, and determining multiple reference samples based on samples in multiple neighboring columns at a left side of the current block according to two preset positions; and determining the multiple first picture component reference samples according to the selected reference samples.
1. A picture component prediction method, applied to a decoder, the method comprising: determining a first picture component reference value set of a current block; determining multiple first picture component reference values according to the first picture component reference value set, wherein the multiple first picture component reference values include four reference values corresponding to four preset sample positions, respectively; performing first filtering processing on sample values of samples corresponding to the multiple first picture component reference values, respectively, to determine multiple filtered first picture reference sample values, wherein the first filtering processing is performed on the sample values of the samples corresponding to the multiple first picture component reference values to obtain a filtered reference value set, and wherein reference sample values in the filtered reference value set are compared, and wherein a set of greater first picture component reference values and a set of smaller first picture component reference values are determined based on the reference sample values, wherein the multiple filtered first picture reference sample values are determined by using multiple values from each of the set of greater first picture component reference values and the set of smaller first picture component reference values; determining a parameter of a component linear model according to the multiple filtered first picture reference sample values and a corresponding to-be-predicted picture component reference values, the to-be-predicted picture component being a picture component which is different from the first picture component, and the component linear model characterizing a linear mapping relationship for mapping a sample value of the first picture component to a sample value of the to-be-predicted picture component; performing mapping processing on a reconstructed value of the first picture component of the current block according to the component linear model to obtain a mapped value; and determining a predicted value of the to-be-predicted picture component of the current block according to the mapped value.
4. The method of claim 3, wherein determining the multiple first picture component reference values according to the first picture component reference value set comprises: selecting two reference samples from the samples in the one or more neighboring lines at the top side of the current block according to a preset position, and selecting two reference samples from the samples in the one or more neighboring columns at the left side of the current block according to a preset position; determining the multiple first picture component reference values according to the four selected samples.
2. The decoder of claim 1, wherein determining the first picture component reference sample set of the current block comprises: determining multiple reference samples that locate outside of the current block, and determining the multiple reference samples as the first picture component reference sample set.
2. The method of claim 1, wherein determining the first picture component reference value set of a current block comprises: determining one or more reference samples that locate outside of the current block, and determining the one or more reference samples as the first picture component reference value set, wherein determining the one or more reference samples that locate outside of the current block comprises: determining neighboring samples of the current block as one or more reference samples.
3. The decoder of claim 1, wherein performing first filtering processing on the multiple first picture component reference samples, to determine the multiple filtered first picture reference samples comprises: performing first filtering processing on the multiple first picture component reference samples to obtain a filtered reference sample set; by comparing reference samples in the filtered reference sample set, determining a set of greater first picture component reference samples and a set of smaller first picture component reference samples; and determining a filtered maximum first picture component reference sample and a filtered minimum first picture component reference sample based on the set of greater first picture component reference samples and the set of smaller first picture component reference samples; wherein a number of samples in the set of greater first picture component reference samples is 2, and a number of samples in the set of smaller first picture component reference samples is 2.
1. A picture component prediction method, applied to a decoder, the method comprising: determining a first picture component reference value set of a current block; determining multiple first picture component reference values according to the first picture component reference value set, wherein the multiple first picture component reference values include four reference values corresponding to four preset sample positions, respectively; performing first filtering processing on sample values of samples corresponding to the multiple first picture component reference values, respectively, to determine multiple filtered first picture reference sample values, wherein the first filtering processing is performed on the sample values of the samples corresponding to the multiple first picture component reference values to obtain a filtered reference value set, and wherein reference sample values in the filtered reference value set are compared, and wherein a set of greater first picture component reference values and a set of smaller first picture component reference values are determined based on the reference sample values, wherein the multiple filtered first picture reference sample values are determined by using multiple values from each of the set of greater first picture component reference values and the set of smaller first picture component reference values; determining a parameter of a component linear model according to the multiple filtered first picture reference sample values and a corresponding to-be-predicted picture component reference values, the to-be-predicted picture component being a picture component which is different from the first picture component, and the component linear model characterizing a linear mapping relationship for mapping a sample value of the first picture component to a sample value of the to-be-predicted picture component; performing mapping processing on a reconstructed value of the first picture component of the current block according to the component linear model to obtain a mapped value; and determining a predicted value of the to-be-predicted picture component of the current block according to the mapped value.
7. The method of claim 6, wherein determining the parameter of the component linear model according to the multiple filtered first picture reference sample values and a corresponding to-be-predicted picture component reference values comprises: determining the parameter of the component linear model according to the filtered maximum first picture component reference value, the maximum to-be-predicted picture component reference value, the filtered minimum first picture component reference value and the minimum to-be-predicted picture component reference value, the component linear model characterizing the linear mapping relationship for mapping the sample value of the first picture component to the sample value of the to-be-predicted picture component.
4. The decoder of claim 3, the operations further comprising: determining a maximum to-be-predicted picture component reference sample corresponding to the filtered maximum first picture component reference sample and a minimum to-be-predicted picture component reference sample corresponding to the filtered minimum first picture component reference sample; and determining the parameter of the component model according to the filtered maximum first picture component reference sample, the maximum to-be-predicted picture component reference sample, the filtered minimum first picture component reference sample and the minimum to-be-predicted picture component reference sample.
6. The method of claim 5, further comprising: determining a maximum to-be-predicted picture component reference value corresponding to the filtered maximum first picture component reference value and a minimum to-be-predicted picture component reference value corresponding to the filtered minimum first picture component reference value.
7. The method of claim 6, wherein determining the parameter of the component linear model according to the multiple filtered first picture reference sample values and a corresponding to-be-predicted picture component reference values comprises: determining the parameter of the component linear model according to the filtered maximum first picture component reference value, the maximum to-be-predicted picture component reference value, the filtered minimum first picture component reference value and the minimum to-be-predicted picture component reference value, the component linear model characterizing the linear mapping relationship for mapping the sample value of the first picture component to the sample value of the to-be-predicted picture component.
5. The decoder of claim 1, wherein performing mapping processing on the reconstructed sample of the first picture component of the current block according to the component model to obtain the mapped sample comprises: performing second filtering processing on the reconstructed samples of the first picture component to obtain a second filtered sample of the reconstructed samples of the first picture component; and performing mapping processing on the second filtered sample according to the component model to obtain the mapped sample; wherein second filtering processing is down-sampling filtering.
14. The method of claim 1, wherein performing mapping processing on the reconstructed value of the first picture component of the current block according to the component linear model to obtain the mapped value comprises: performing second filtering processing on the reconstructed value of the first picture component to obtain a second filtered value of the reconstructed value of the first picture component; and performing mapping processing on the second filtered value according to the component linear model to obtain the mapped value, wherein second filtering processing is down-sampling filtering or low-pass filtering.
6. The decoder of claim 4, wherein determining the maximum to-be-predicted picture component reference sample corresponding to the filtered maximum first picture component reference sample and the minimum to-be-predicted picture component reference sample corresponding to the filtered minimum first picture component reference sample comprises: determining a set of greater to-be-predicted picture component reference samples corresponding to the reference samples in the set of greater first picture component reference samples and a set of smaller to-be-predicted picture component reference samples corresponding to the reference samples in the set of smaller first picture component reference samples; determining the maximum to-be-predicted picture component reference sample based on a mean processing on reference samples in the set of greater to-be-predicted picture component reference samples, and determining the minimum to-be-predicted picture component reference sample based on a mean processing on reference samples in the set of smaller the to-be-predicted picture component reference samples.
10. The method of claim 6, wherein determining the maximum to-be-predicted picture component reference value corresponding to the filtered maximum first picture component reference value and the minimum to-be-predicted picture component reference value corresponding to the filtered minimum first picture component reference value comprises: acquiring to-be-predicted picture component reference values of the reference samples in the set of greater first picture component reference values and to-be-predicted picture component reference values of the reference samples in the set of smaller first picture component reference values; performing meaning processing on the to-be-predicted picture component reference values of the reference samples in the set of greater first picture component reference values, and determining the maximum to-be-predicted picture component reference value; and performing meaning processing on the to-be-predicted picture component reference values of the reference samples in the set of smaller first picture component reference values, and determining minimum to-be-predicted picture component reference value.
7. The decoder of claim 1, wherein the first picture component is a luma component, and the to-be-predicted picture component is a first or second chroma component.
17. The method of claim 1, wherein the first picture component is a luma component, and the to-be-predicted picture component is a first or second chroma component; or the first picture component is the first chroma component, and the to-be-predicted picture component is the luma component or the second chroma component; or the first picture component is the second chroma component, and the to-be-predicted picture component is the luma component or the first chroma component; or the first picture component is a first colour component, and the to-be-predicted picture component is a second colour component or a third colour component; or the first picture component is the second colour component, and the to-be-predicted picture component is the first colour component or the third colour component; or the first picture component is the third colour component, and the to-be-predicted picture component is the second colour component or the first colour component, wherein the first colour component is a red component, the second colour component is a green component, and the third colour component is a blue component.
8. An encoder for picture component prediction, comprising: determining a first picture component reference sample set of a current block; determining multiple first picture component reference samples according to the first picture component reference sample set; performing first filtering processing on the multiple first picture component reference samples, to determine multiple filtered first picture reference samples; determining a parameter of a component model according to the multiple filtered first picture reference samples and corresponding to-be-predicted picture component reference samples, a to-be-predicted picture component being a picture component which is different from a first picture component, and the component model characterizing a mapping relationship for mapping a sample of the first picture component to a sample of the to-be-predicted picture component; performing mapping processing on a reconstructed sample of the first picture component of the current block according to the component model to obtain a mapped sample; and determining a predicted sample of the to-be-predicted picture component of the current block according to the mapped sample, wherein determining multiple first picture component reference samples according to the first picture component reference sample set comprises: determining multiple reference samples based on samples in multiple neighboring lines at a top side of the current block according to two preset positions, and determining multiple reference samples based on samples in multiple neighboring columns at a left side of the current block according to two preset positions; and determining the multiple first picture component reference samples according to the selected reference samples.
19. A picture component prediction method, applied to an encoder, the method comprising: determining a first picture component reference value set of a current block; determining multiple first picture component reference values according to the first picture component reference value set, wherein the multiple first picture component reference values include four reference values corresponding to four preset sample positions, respectively; performing first filtering processing on sample values of samples corresponding to the multiple first picture component reference values, respectively, to determine multiple filtered first picture reference sample values, wherein the first filtering processing is performed on the sample values of the samples corresponding to the multiple first picture component reference values to obtain a filtered reference value set, and wherein reference sample values in the filtered reference value set are compared, and wherein a set of greater first picture component reference values and a set of smaller first picture component reference values are determined based on the reference sample values, and wherein the multiple filtered first picture reference sample values are determined by using multiple values from each of the set of greater first picture component reference values and the set of smaller first picture component reference values; determining a parameter of a component linear model according to the multiple filtered first picture reference sample values and a corresponding to-be-predicted picture component reference values, the to-be-predicted picture component being a picture component which is different from the first picture component, and the component linear model characterizing a linear mapping relationship for mapping a sample value of the first picture component to a sample value of the to-be-predicted picture component; performing mapping processing on a reconstructed value of the first picture component of the current block according to the component linear model to obtain a mapped value; and determining a predicted value of the to-be-predicted picture component of the current block according to the mapped value.
4. The method of claim 3, wherein determining the multiple first picture component reference values according to the first picture component reference value set comprises: selecting two reference samples from the samples in the one or more neighboring lines at the top side of the current block according to a preset position, and selecting two reference samples from the samples in the one or more neighboring columns at the left side of the current block according to a preset position; determining the multiple first picture component reference values according to the four selected samples.
9. The encoder of claim 8, wherein determining the first picture component reference sample set of the current block comprises: determining multiple reference samples that locate outside of the current block, and determining the multiple reference samples as the first picture component reference sample set.
2. The method of claim 1, wherein determining the first picture component reference value set of a current block comprises: determining one or more reference samples that locate outside of the current block, and determining the one or more reference samples as the first picture component reference value set, wherein determining the one or more reference samples that locate outside of the current block comprises: determining neighboring samples of the current block as one or more reference samples.
10. The encoder of claim 8, wherein performing first filtering processing on the multiple first picture component reference samples, to determine the multiple filtered first picture reference samples comprises: performing first filtering processing on the multiple first picture component reference samples to obtain a filtered reference sample set; by comparing reference samples in the filtered reference sample set, determining a set of greater first picture component reference samples and a set of smaller first picture component reference samples; and determining a filtered maximum first picture component reference sample and a filtered minimum first picture component reference sample based on the set of greater first picture component reference samples and the set of smaller first picture component reference samples; wherein a number of samples in the set of greater first picture component reference samples is 2, and a number of samples in the set of smaller first picture component reference samples is 2.
19. A picture component prediction method, applied to an encoder, the method comprising: determining a first picture component reference value set of a current block; determining multiple first picture component reference values according to the first picture component reference value set, wherein the multiple first picture component reference values include four reference values corresponding to four preset sample positions, respectively; performing first filtering processing on sample values of samples corresponding to the multiple first picture component reference values, respectively, to determine multiple filtered first picture reference sample values, wherein the first filtering processing is performed on the sample values of the samples corresponding to the multiple first picture component reference values to obtain a filtered reference value set, and wherein reference sample values in the filtered reference value set are compared, and wherein a set of greater first picture component reference values and a set of smaller first picture component reference values are determined based on the reference sample values, and wherein the multiple filtered first picture reference sample values are determined by using multiple values from each of the set of greater first picture component reference values and the set of smaller first picture component reference values; determining a parameter of a component linear model according to the multiple filtered first picture reference sample values and a corresponding to-be-predicted picture component reference values, the to-be-predicted picture component being a picture component which is different from the first picture component, and the component linear model characterizing a linear mapping relationship for mapping a sample value of the first picture component to a sample value of the to-be-predicted picture component; performing mapping processing on a reconstructed value of the first picture component of the current block according to the component linear model to obtain a mapped value; and determining a predicted value of the to-be-predicted picture component of the current block according to the mapped value.
6. The method of claim 5, further comprising: determining a maximum to-be-predicted picture component reference value corresponding to the filtered maximum first picture component reference value and a minimum to-be-predicted picture component reference value corresponding to the filtered minimum first picture component reference value.
11. The encoder of claim 10, the operations further comprising: determining a maximum to-be-predicted picture component reference sample corresponding to the filtered maximum first picture component reference sample and a minimum to-be-predicted picture component reference sample corresponding to the filtered minimum first picture component reference sample; and determining the parameter of the component model according to the filtered maximum first picture component reference sample, the maximum to-be-predicted picture component reference sample, the filtered minimum first picture component reference sample and the minimum to-be-predicted picture component reference sample.
6. The method of claim 5, further comprising: determining a maximum to-be-predicted picture component reference value corresponding to the filtered maximum first picture component reference value and a minimum to-be-predicted picture component reference value corresponding to the filtered minimum first picture component reference value.
7. The method of claim 6, wherein determining the parameter of the component linear model according to the multiple filtered first picture reference sample values and a corresponding to-be-predicted picture component reference values comprises: determining the parameter of the component linear model according to the filtered maximum first picture component reference value, the maximum to-be-predicted picture component reference value, the filtered minimum first picture component reference value and the minimum to-be-predicted picture component reference value, the component linear model characterizing the linear mapping relationship for mapping the sample value of the first picture component to the sample value of the to-be-predicted picture component.
12. The encoder of claim 8, wherein performing mapping processing on the reconstructed sample of the first picture component of the current block according to the component model to obtain the mapped sample comprises: performing second filtering processing on the reconstructed samples of the first picture component to obtain a second filtered sample of the reconstructed samples of the first picture component; and performing mapping processing on the second filtered sample according to the component model to obtain the mapped sample; wherein second filtering processing is down-sampling filtering.
14. The method of claim 1, wherein performing mapping processing on the reconstructed value of the first picture component of the current block according to the component linear model to obtain the mapped value comprises: performing second filtering processing on the reconstructed value of the first picture component to obtain a second filtered value of the reconstructed value of the first picture component; and performing mapping processing on the second filtered value according to the component linear model to obtain the mapped value, wherein second filtering processing is down-sampling filtering or low-pass filtering.
13. The encoder of claim 11, wherein determining the maximum to-be-predicted picture component reference sample corresponding to the filtered maximum first picture component reference sample and the minimum to-be-predicted picture component reference sample corresponding to the filtered minimum first picture component reference sample comprises: determining a set of greater to-be-predicted picture component reference samples corresponding to the reference samples in the set of greater first picture component reference samples and a set of smaller to-be-predicted picture component reference samples corresponding to the reference samples in the set of smaller first picture component reference samples; determining the maximum to-be-predicted picture component reference sample based on a mean processing on reference samples in the set of greater to-be-predicted picture component reference samples, and determining the minimum to-be-predicted picture component reference sample based on a mean processing on reference samples in the set of smaller the to-be-predicted picture component reference samples.
10. The method of claim 6, wherein determining the maximum to-be-predicted picture component reference value corresponding to the filtered maximum first picture component reference value and the minimum to-be-predicted picture component reference value corresponding to the filtered minimum first picture component reference value comprises: acquiring to-be-predicted picture component reference values of the reference samples in the set of greater first picture component reference values and to-be-predicted picture component reference values of the reference samples in the set of smaller first picture component reference values; performing meaning processing on the to-be-predicted picture component reference values of the reference samples in the set of greater first picture component reference values, and determining the maximum to-be-predicted picture component reference value; and performing meaning processing on the to-be-predicted picture component reference values of the reference samples in the set of smaller first picture component reference values, and determining minimum to-be-predicted picture component reference value.
14. The encoder of claim 8, wherein the first picture component is a luma component, and the to-be-predicted picture component is a first or second chroma component.
17. The method of claim 1, wherein the first picture component is a luma component, and the to-be-predicted picture component is a first or second chroma component; or the first picture component is the first chroma component, and the to-be-predicted picture component is the luma component or the second chroma component; or the first picture component is the second chroma component, and the to-be-predicted picture component is the luma component or the first chroma component; or the first picture component is a first colour component, and the to-be-predicted picture component is a second colour component or a third colour component; or the first picture component is the second colour component, and the to-be-predicted picture component is the first colour component or the third colour component; or the first picture component is the third colour component, and the to-be-predicted picture component is the second colour component or the first colour component, wherein the first colour component is a red component, the second colour component is a green component, and the third colour component is a blue component.
15. A non-transitory computer-readable storage medium, having a computer program and a bitstream stored thereon, wherein the computer program, when executed by a processor, enables the processor to perform an encoding method to generate the bitstream, and the encoding method comprises: determining a first picture component reference sample set of a current block; determining multiple first picture component reference samples according to the first picture component reference sample set; performing first filtering processing on the multiple first picture component reference samples, to determine multiple filtered first picture reference samples; determining a parameter of a component model according to the multiple filtered first picture reference samples and corresponding to-be-predicted picture component reference samples, a to-be-predicted picture component being a picture component which is different from a first picture component, and the component model characterizing a mapping relationship for mapping a sample of the first picture component to a sample of the to-be-predicted picture component; performing mapping processing on a reconstructed sample of the first picture component of the current block according to the component model to obtain a mapped sample; and determining a predicted sample of the to-be-predicted picture component of the current block according to the mapped sample, wherein determining multiple first picture component reference samples according to the first picture component reference sample set comprises: determining multiple reference samples based on samples in multiple neighboring lines at a top side of the current block according to two preset positions, and determining multiple reference samples based on samples in multiple neighboring columns at a left side of the current block according to two preset positions; and determining the multiple first picture component reference samples according to the selected reference samples.
19. A picture component prediction method, applied to an encoder, the method comprising: determining a first picture component reference value set of a current block; determining multiple first picture component reference values according to the first picture component reference value set, wherein the multiple first picture component reference values include four reference values corresponding to four preset sample positions, respectively; performing first filtering processing on sample values of samples corresponding to the multiple first picture component reference values, respectively, to determine multiple filtered first picture reference sample values, wherein the first filtering processing is performed on the sample values of the samples corresponding to the multiple first picture component reference values to obtain a filtered reference value set, and wherein reference sample values in the filtered reference value set are compared, and wherein a set of greater first picture component reference values and a set of smaller first picture component reference values are determined based on the reference sample values, and wherein the multiple filtered first picture reference sample values are determined by using multiple values from each of the set of greater first picture component reference values and the set of smaller first picture component reference values; determining a parameter of a component linear model according to the multiple filtered first picture reference sample values and a corresponding to-be-predicted picture component reference values, the to-be-predicted picture component being a picture component which is different from the first picture component, and the component linear model characterizing a linear mapping relationship for mapping a sample value of the first picture component to a sample value of the to-be-predicted picture component; performing mapping processing on a reconstructed value of the first picture component of the current block according to the component linear model to obtain a mapped value; and determining a predicted value of the to-be-predicted picture component of the current block according to the mapped value.
4. The method of claim 3, wherein determining the multiple first picture component reference values according to the first picture component reference value set comprises: selecting two reference samples from the samples in the one or more neighboring lines at the top side of the current block according to a preset position, and selecting two reference samples from the samples in the one or more neighboring columns at the left side of the current block according to a preset position; determining the multiple first picture component reference values according to the four selected samples.
16. The non-transitory computer-readable storage medium of claim 15, wherein determining the first picture component reference sample set of the current block comprises: determining multiple reference samples that locate outside of the current block, and determining the multiple reference samples as the first picture component reference sample set.
2. The method of claim 1, wherein determining the first picture component reference value set of a current block comprises: determining one or more reference samples that locate outside of the current block, and determining the one or more reference samples as the first picture component reference value set, wherein determining the one or more reference samples that locate outside of the current block comprises: determining neighboring samples of the current block as one or more reference samples.
17. The non-transitory computer-readable storage medium of claim 15, wherein performing first filtering processing on the multiple first picture component reference samples, to determine the multiple filtered first picture reference samples comprises: performing first filtering processing on the multiple first picture component reference samples to obtain a filtered reference sample set; by comparing reference samples in the filtered reference sample set, determining a set of greater first picture component reference samples and a set of smaller first picture component reference samples; and determining a filtered maximum first picture component reference sample and a filtered minimum first picture component reference sample based on the set of greater first picture component reference samples and the set of smaller first picture component reference samples; wherein a number of samples in the set of greater first picture component reference samples is 2, and a number of samples in the set of smaller first picture component reference samples is 2.
19. A picture component prediction method, applied to an encoder, the method comprising: determining a first picture component reference value set of a current block; determining multiple first picture component reference values according to the first picture component reference value set, wherein the multiple first picture component reference values include four reference values corresponding to four preset sample positions, respectively; performing first filtering processing on sample values of samples corresponding to the multiple first picture component reference values, respectively, to determine multiple filtered first picture reference sample values, wherein the first filtering processing is performed on the sample values of the samples corresponding to the multiple first picture component reference values to obtain a filtered reference value set, and wherein reference sample values in the filtered reference value set are compared, and wherein a set of greater first picture component reference values and a set of smaller first picture component reference values are determined based on the reference sample values, and wherein the multiple filtered first picture reference sample values are determined by using multiple values from each of the set of greater first picture component reference values and the set of smaller first picture component reference values; determining a parameter of a component linear model according to the multiple filtered first picture reference sample values and a corresponding to-be-predicted picture component reference values, the to-be-predicted picture component being a picture component which is different from the first picture component, and the component linear model characterizing a linear mapping relationship for mapping a sample value of the first picture component to a sample value of the to-be-predicted picture component; performing mapping processing on a reconstructed value of the first picture component of the current block according to the component linear model to obtain a mapped value; and determining a predicted value of the to-be-predicted picture component of the current block according to the mapped value.
6. The method of claim 5, further comprising: determining a maximum to-be-predicted picture component reference value corresponding to the filtered maximum first picture component reference value and a minimum to-be-predicted picture component reference value corresponding to the filtered minimum first picture component reference value.
18. The non-transitory computer-readable storage medium of claim 17, the method further comprising: determining a maximum to-be-predicted picture component reference sample corresponding to the filtered maximum first picture component reference sample and a minimum to-be-predicted picture component reference sample corresponding to the filtered minimum first picture component reference sample; and determining the parameter of the component model according to the filtered maximum first picture component reference sample, the maximum to-be-predicted picture component reference sample, the filtered minimum first picture component reference sample and the minimum to-be-predicted picture component reference sample.
6. The method of claim 5, further comprising: determining a maximum to-be-predicted picture component reference value corresponding to the filtered maximum first picture component reference value and a minimum to-be-predicted picture component reference value corresponding to the filtered minimum first picture component reference value.
7. The method of claim 6, wherein determining the parameter of the component linear model according to the multiple filtered first picture reference sample values and a corresponding to-be-predicted picture component reference values comprises: determining the parameter of the component linear model according to the filtered maximum first picture component reference value, the maximum to-be-predicted picture component reference value, the filtered minimum first picture component reference value and the minimum to-be-predicted picture component reference value, the component linear model characterizing the linear mapping relationship for mapping the sample value of the first picture component to the sample value of the to-be-predicted picture component.
19. The non-transitory computer-readable storage medium of claim 15, wherein performing mapping processing on the reconstructed sample of the first picture component of the current block according to the component model to obtain the mapped sample comprises: performing second filtering processing on the reconstructed samples of the first picture component to obtain a second filtered sample of the reconstructed samples of the first picture component; and performing mapping processing on the second filtered sample according to the component model to obtain the mapped sample; wherein second filtering processing is down-sampling filtering.
14. The method of claim 1, wherein performing mapping processing on the reconstructed value of the first picture component of the current block according to the component linear model to obtain the mapped value comprises: performing second filtering processing on the reconstructed value of the first picture component to obtain a second filtered value of the reconstructed value of the first picture component; and performing mapping processing on the second filtered value according to the component linear model to obtain the mapped value, wherein second filtering processing is down-sampling filtering or low-pass filtering.
20. The non-transitory computer-readable storage medium of claim 18, wherein determining the maximum to-be-predicted picture component reference sample corresponding to the filtered maximum first picture component reference sample and the minimum to-be-predicted picture component reference sample corresponding to the filtered minimum first picture component reference sample comprises: determining a set of greater to-be-predicted picture component reference samples corresponding to the reference samples in the set of greater first picture component reference samples and a set of smaller to-be-predicted picture component reference samples corresponding to the reference samples in the set of smaller first picture component reference samples; determining the maximum to-be-predicted picture component reference sample based on a mean processing on reference samples in the set of greater to-be-predicted picture component reference samples, and determining the minimum to-be-predicted picture component reference sample based on a mean processing on reference samples in the set of smaller the to-be-predicted picture component reference samples.
10. The method of claim 6, wherein determining the maximum to-be-predicted picture component reference value corresponding to the filtered maximum first picture component reference value and the minimum to-be-predicted picture component reference value corresponding to the filtered minimum first picture component reference value comprises: acquiring to-be-predicted picture component reference values of the reference samples in the set of greater first picture component reference values and to-be-predicted picture component reference values of the reference samples in the set of smaller first picture component reference values; performing meaning processing on the to-be-predicted picture component reference values of the reference samples in the set of greater first picture component reference values, and determining the maximum to-be-predicted picture component reference value; and performing meaning processing on the to-be-predicted picture component reference values of the reference samples in the set of smaller first picture component reference values, and determining minimum to-be-predicted picture component reference value.
Claims 1 – 20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1, 2, 4 – 10, and 13 - 19 of U.S. Patent No. 11,876,958. Although the claims at issue are not identical, they are not patentably distinct from each other because the scope of the patented case wholly encompasses the scope of the current application.
Current Application
U.S. Patent No. 11,876,958
1. A decoder for picture component prediction, comprising: a memory for storing executable video component prediction instructions; and a processor configured to perform the executable video component prediction instructions stored in the memory to perform following operations: determining a first picture component reference sample set of a current block; determining multiple first picture component reference samples according to the first picture component reference sample set; performing first filtering processing on the multiple first picture component reference samples, to determine multiple filtered first picture reference samples; determining a parameter of a component model according to the multiple filtered first picture reference samples and corresponding to-be-predicted picture component reference samples, a to-be-predicted picture component being a picture component which is different from a first picture component, and the component model characterizing a mapping relationship for mapping a sample of the first picture component to a sample of the to-be-predicted picture component; performing mapping processing on a reconstructed sample of the first picture component of the current block according to the component model to obtain a mapped sample; and determining a predicted sample of the to-be-predicted picture component of the current block according to the mapped sample, wherein determining multiple first picture component reference samples according to the first picture component reference sample set comprises: determining multiple reference samples based on samples in multiple neighboring lines at a top side of the current block according to two preset positions, and determining multiple reference samples based on samples in multiple neighboring columns at a left side of the current block according to two preset positions; and determining the multiple first picture component reference samples according to the selected reference samples.
1. A picture component prediction method, applied to a decoder, the method comprising: determining a first picture component reference value set of a current block; determining multiple first picture component reference values according to the first picture component reference value set, wherein the multiple first picture component reference values include four reference values corresponding to four preset sample positions, respectively; performing first filtering processing on sample values of samples corresponding to the multiple first picture component reference values, respectively, to determine multiple filtered first picture reference sample values; determining a parameter of a component linear model according to the multiple filtered first picture reference sample values and a corresponding to-be-predicted picture component reference values, the to-be-predicted picture component being a picture component which is different from the first picture component, and the component linear model characterizing a linear mapping relationship for mapping a sample value of the first picture component to a sample value of the to-be-predicted picture component; performing mapping processing on a reconstructed value of the first picture component of the current block according to the component linear model to obtain a mapped value; and determining a predicted value of the to-be-predicted picture component of the current block according to the mapped value.
4. The method of claim 3, wherein determining the multiple first picture component reference values according to the first picture component reference value set comprises: selecting two reference samples from the samples in the one or more neighboring lines at the top side of the current block according to a preset position, and selecting two reference samples from the samples in the one or more neighboring columns at the left side of the current block according to a preset position; determining the multiple first picture component reference values according to the four selected samples.
2. The decoder of claim 1, wherein determining the first picture component reference sample set of the current block comprises: determining multiple reference samples that locate outside of the current block, and determining the multiple reference samples as the first picture component reference sample set.
2. The method of claim 1, wherein determining the first picture component reference value set of a current block comprises: determining one or more reference samples that locate outside of the current block, and determining the one or more reference samples as the first picture component reference value set, wherein determining the one or more reference samples that locate outside of the current block comprises: determining neighboring samples of the current block as one or more reference samples.
3. The decoder of claim 1, wherein performing first filtering processing on the multiple first picture component reference samples, to determine the multiple filtered first picture reference samples comprises: performing first filtering processing on the multiple first picture component reference samples to obtain a filtered reference sample set; by comparing reference samples in the filtered reference sample set, determining a set of greater first picture component reference samples and a set of smaller first picture component reference samples; and determining a filtered maximum first picture component reference sample and a filtered minimum first picture component reference sample based on the set of greater first picture component reference samples and the set of smaller first picture component reference samples; wherein a number of samples in the set of greater first picture component reference samples is 2, and a number of samples in the set of smaller first picture component reference samples is 2.
5. The method of claim of claim 1, wherein the first filtering processing is performed on the sample values of the samples corresponding to the multiple first picture component reference values to obtain a filtered reference value set, and wherein reference sample values in the filtered reference value set are compared, and wherein a set of greater first picture component reference values and a set of smaller first picture component reference values are determined based on the reference sample values, wherein the multiple filtered first picture reference sample values are determined by using multiple values from each of the set of greater first picture component reference values and the set of smaller first picture component reference values.
7. The method of claim 5, wherein a number of sample values in the set of greater first picture component reference values is an integer which is equal to or greater than 1, and a number of sample values in the set of smaller first picture component reference values is an integer which is equal to or greater than 1, wherein the number of sample values in the set of greater first picture component reference values is 2, and a number of sample values in the set of smaller first picture component reference values is 2.
4. The decoder of claim 3, the operations further comprising: determining a maximum to-be-predicted picture component reference sample corresponding to the filtered maximum first picture component reference sample and a minimum to-be-predicted picture component reference sample corresponding to the filtered minimum first picture component reference sample; and determining the parameter of the component model according to the filtered maximum first picture component reference sample, the maximum to-be-predicted picture component reference sample, the filtered minimum first picture component reference sample and the minimum to-be-predicted picture component reference sample.
8. The method of claim 6, further comprising: determining a maximum to-be-predicted picture component reference value corresponding to the filtered maximum first picture component reference value and a minimum to-be-predicted picture component reference value corresponding to the filtered minimum first picture component reference value.
9. The method of claim 8, wherein determining the parameter of the component linear model according to the multiple filtered first picture reference sample values and a corresponding to-be-predicted picture component reference values comprises: determining the parameter of the component linear model according to the filtered maximum first picture component reference value, the maximum to-be-predicted picture component reference value, the filtered minimum first picture component reference value and the minimum to-be-predicted picture component reference value, the component linear model characterizing the linear mapping relationship for mapping the sample value of the first picture component to the sample value of the to-be-predicted picture component.
5. The decoder of claim 1, wherein performing mapping processing on the reconstructed sample of the first picture component of the current block according to the component model to obtain the mapped sample comprises: performing second filtering processing on the reconstructed samples of the first picture component to obtain a second filtered sample of the reconstructed samples of the first picture component; and performing mapping processing on the second filtered sample according to the component model to obtain the mapped sample; wherein second filtering processing is down-sampling filtering.
10. The method of claim 1, wherein performing mapping processing on the reconstructed value of the first picture component of the current block according to the component linear model to obtain the mapped value comprises: performing second filtering processing on the reconstructed value of the first picture component to obtain a second filtered value of the reconstructed value of the first picture component; and performing mapping processing on the second filtered value according to the component linear model to obtain the mapped value, wherein second filtering processing is down-sampling filtering or low-pass filtering.
6. The decoder of claim 4, wherein determining the maximum to-be-predicted picture component reference sample corresponding to the filtered maximum first picture component reference sample and the minimum to-be-predicted picture component reference sample corresponding to the filtered minimum first picture component reference sample comprises: determining a set of greater to-be-predicted picture component reference samples corresponding to the reference samples in the set of greater first picture component reference samples and a set of smaller to-be-predicted picture component reference samples corresponding to the reference samples in the set of smaller first picture component reference samples; determining the maximum to-be-predicted picture component reference sample based on a mean processing on reference samples in the set of greater to-be-predicted picture component reference samples, and determining the minimum to-be-predicted picture component reference sample based on a mean processing on reference samples in the set of smaller the to-be-predicted picture component reference samples.
6. The method of claim 5, wherein determining the multiple filtered first picture reference sample values based on the set of greater first picture component reference values and set of smaller first picture component reference values comprises: performing mean processing on the set of greater first picture component reference values to obtain a filtered maximum first picture component reference value; and performing mean processing on the set of smaller first picture component reference values to obtain a filtered minimum first picture component reference value.
8. The method of claim 6, further comprising: determining a maximum to-be-predicted picture component reference value corresponding to the filtered maximum first picture component reference value and a minimum to-be-predicted picture component reference value corresponding to the filtered minimum first picture component reference value.
7. The decoder of claim 1, wherein the first picture component is a luma component, and the to-be-predicted picture component is a first or second chroma component.
13. The method of claim 1, wherein the first picture component is a luma component, and the to-be-predicted picture component is a first or second chroma component; or the first picture component is the first chroma component, and the to-be-predicted picture component is the luma component or the second chroma component; or the first picture component is the second chroma component, and the to-be-predicted picture component is the luma component or the first chroma component; or the first picture component is a first colour component, and the to-be-predicted picture component is a second colour component or a third colour component; or the first picture component is the second colour component, and the to-be-predicted picture component is the first colour component or the third colour component; or the first picture component is the third colour component, and the to-be-predicted picture component is the second colour component or the first colour component, wherein the first colour component is a red component, the second colour component is a green component, and the third colour component is a blue component.
8. An encoder for picture component prediction, comprising: determining a first picture component reference sample set of a current block; determining multiple first picture component reference samples according to the first picture component reference sample set; performing first filtering processing on the multiple first picture component reference samples, to determine multiple filtered first picture reference samples; determining a parameter of a component model according to the multiple filtered first picture reference samples and corresponding to-be-predicted picture component reference samples, a to-be-predicted picture component being a picture component which is different from a first picture component, and the component model characterizing a mapping relationship for mapping a sample of the first picture component to a sample of the to-be-predicted picture component; performing mapping processing on a reconstructed sample of the first picture component of the current block according to the component model to obtain a mapped sample; and determining a predicted sample of the to-be-predicted picture component of the current block according to the mapped sample, wherein determining multiple first picture component reference samples according to the first picture component reference sample set comprises: determining multiple reference samples based on samples in multiple neighboring lines at a top side of the current block according to two preset positions, and determining multiple reference samples based on samples in multiple neighboring columns at a left side of the current block according to two preset positions; and determining the multiple first picture component reference samples according to the selected reference samples.
14. A picture component prediction method, applied to an encoder, the method comprising: determining a first picture component reference value set of a current block; determining multiple first picture component reference values according to the first picture component reference value set, wherein the multiple first picture component reference values include four reference values corresponding to four preset sample positions, respectively; performing first filtering processing on sample values of samples corresponding to the multiple first picture component reference values, respectively, to determine multiple filtered first picture reference sample values; determining a parameter of a component linear model according to the multiple filtered first picture reference sample values and a corresponding to-be-predicted picture component reference values, the to-be-predicted picture component being a picture component which is different from the first picture component, and the component linear model characterizing a linear mapping relationship for mapping a sample value of the first picture component to a sample value of the to-be-predicted picture component; performing mapping processing on a reconstructed value of the first picture component of the current block according to the component linear model to obtain a mapped value; and determining a predicted value of the to-be-predicted picture component of the current block according to the mapped value.
16. The method of claim 15, wherein determining the multiple first picture component reference values according to the first picture component reference value set comprises: selecting two reference samples from the samples in the one or more neighboring lines at the top side of the current block according to a preset position, and selecting two reference samples from the samples in the one or more neighboring columns at the left side of the current block according to a preset position; determining the multiple first picture component reference values according to the four selected samples.
9. The encoder of claim 8, wherein determining the first picture component reference sample set of the current block comprises: determining multiple reference samples that locate outside of the current block, and determining the multiple reference samples as the first picture component reference sample set.
15. The method of claim 14, wherein determining the first picture component reference value set of a current block comprises: determining one or more reference samples that locate outside of the current block, and determining the one or more reference samples as the first picture component reference value set, wherein determining the one or more reference samples that locate outside of the current block comprises: determining neighboring samples of the current block as one or more reference samples; wherein the neighboring samples of the current block comprise at least one of: samples in one or more neighboring lines at a top side of the current block, or samples in one or more neighboring columns at a left side of the current block.
10. The encoder of claim 8, wherein performing first filtering processing on the multiple first picture component reference samples, to determine the multiple filtered first picture reference samples comprises: performing first filtering processing on the multiple first picture component reference samples to obtain a filtered reference sample set; by comparing reference samples in the filtered reference sample set, determining a set of greater first picture component reference samples and a set of smaller first picture component reference samples; and determining a filtered maximum first picture component reference sample and a filtered minimum first picture component reference sample based on the set of greater first picture component reference samples and the set of smaller first picture component reference samples; wherein a number of samples in the set of greater first picture component reference samples is 2, and a number of samples in the set of smaller first picture component reference samples is 2.
17. The method of claim of claim 14, wherein the first filtering processing is performed on the sample values of the samples corresponding to the multiple first picture component reference values to obtain a filtered reference value set, and wherein reference sample values in the filtered reference value set are compared, and wherein a set of greater first picture component reference values and a set of smaller first picture component reference values are determined based on the reference sample values, wherein the multiple filtered first picture reference sample values are determined by using multiple values from each of the set of greater first picture component reference values and the set of smaller first picture component reference values.
18. The method of claim 17, wherein determining the multiple filtered first picture reference sample values based on the set of greater first picture component reference values and set of smaller first picture component reference values comprises: performing mean processing on the set of greater first picture component reference values to obtain a filtered maximum first picture component reference value; and performing mean processing on the set of smaller first picture component reference values to obtain a filtered minimum first picture component reference value.
19. The method of claim 17, wherein a number of sample values in the set of greater first picture component reference values is an integer which is equal to or greater than 1, and a number of sample values in the set of smaller first picture component reference values is an integer which is equal to or greater than 1, wherein the number of sample values in the set of greater first picture component reference values is 2, and a number of sample values in the set of smaller first picture component reference values is 2.
11. The encoder of claim 10, the operations further comprising: determining a maximum to-be-predicted picture component reference sample corresponding to the filtered maximum first picture component reference sample and a minimum to-be-predicted picture component reference sample corresponding to the filtered minimum first picture component reference sample; and determining the parameter of the component model according to the filtered maximum first picture component reference sample, the maximum to-be-predicted picture component reference sample, the filtered minimum first picture component reference sample and the minimum to-be-predicted picture component reference sample.
18. The method of claim 17, wherein determining the multiple filtered first picture reference sample values based on the set of greater first picture component reference values and set of smaller first picture component reference values comprises: performing mean processing on the set of greater first picture component reference values to obtain a filtered maximum first picture component reference value; and performing mean processing on the set of smaller first picture component reference values to obtain a filtered minimum first picture component reference value.
12. The encoder of claim 8, wherein performing mapping processing on the reconstructed sample of the first picture component of the current block according to the component model to obtain the mapped sample comprises: performing second filtering processing on the reconstructed samples of the first picture component to obtain a second filtered sample of the reconstructed samples of the first picture component; and performing mapping processing on the second filtered sample according to the component model to obtain the mapped sample; wherein second filtering processing is down-sampling filtering.
10. The method of claim 1, wherein performing mapping processing on the reconstructed value of the first picture component of the current block according to the component linear model to obtain the mapped value comprises: performing second filtering processing on the reconstructed value of the first picture component to obtain a second filtered value of the reconstructed value of the first picture component; and performing mapping processing on the second filtered value according to the component linear model to obtain the mapped value, wherein second filtering processing is down-sampling filtering or low-pass filtering.
13. The encoder of claim 11, wherein determining the maximum to-be-predicted picture component reference sample corresponding to the filtered maximum first picture component reference sample and the minimum to-be-predicted picture component reference sample corresponding to the filtered minimum first picture component reference sample comprises: determining a set of greater to-be-predicted picture component reference samples corresponding to the reference samples in the set of greater first picture component reference samples and a set of smaller to-be-predicted picture component reference samples corresponding to the reference samples in the set of smaller first picture component reference samples; determining the maximum to-be-predicted picture component reference sample based on a mean processing on reference samples in the set of greater to-be-predicted picture component reference samples, and determining the minimum to-be-predicted picture component reference sample based on a mean processing on reference samples in the set of smaller the to-be-predicted picture component reference samples.
18. The method of claim 17, wherein determining the multiple filtered first picture reference sample values based on the set of greater first picture component reference values and set of smaller first picture component reference values comprises: performing mean processing on the set of greater first picture component reference values to obtain a filtered maximum first picture component reference value; and performing mean processing on the set of smaller first picture component reference values to obtain a filtered minimum first picture component reference value.
14. The encoder of claim 8, wherein the first picture component is a luma component, and the to-be-predicted picture component is a first or second chroma component.
13. The method of claim 1, wherein the first picture component is a luma component, and the to-be-predicted picture component is a first or second chroma component; or the first picture component is the first chroma component, and the to-be-predicted picture component is the luma component or the second chroma component; or the first picture component is the second chroma component, and the to-be-predicted picture component is the luma component or the first chroma component; or the first picture component is a first colour component, and the to-be-predicted picture component is a second colour component or a third colour component; or the first picture component is the second colour component, and the to-be-predicted picture component is the first colour component or the third colour component; or the first picture component is the third colour component, and the to-be-predicted picture component is the second colour component or the first colour component, wherein the first colour component is a red component, the second colour component is a green component, and the third colour component is a blue component.
15. A non-transitory computer-readable storage medium, having a computer program and a bitstream stored thereon, wherein the computer program, when executed by a processor, enables the processor to perform an encoding method to generate the bitstream, and the encoding method comprises: determining a first picture component reference sample set of a current block; determining multiple first picture component reference samples according to the first picture component reference sample set; performing first filtering processing on the multiple first picture component reference samples, to determine multiple filtered first picture reference samples; determining a parameter of a component model according to the multiple filtered first picture reference samples and corresponding to-be-predicted picture component reference samples, a to-be-predicted picture component being a picture component which is different from a first picture component, and the component model characterizing a mapping relationship for mapping a sample of the first picture component to a sample of the to-be-predicted picture component; performing mapping processing on a reconstructed sample of the first picture component of the current block according to the component model to obtain a mapped sample; and determining a predicted sample of the to-be-predicted picture component of the current block according to the mapped sample, wherein determining multiple first picture component reference samples according to the first picture component reference sample set comprises: determining multiple reference samples based on samples in multiple neighboring lines at a top side of the current block according to two preset positions, and determining multiple reference samples based on samples in multiple neighboring columns at a left side of the current block according to two preset positions; and determining the multiple first picture component reference samples according to the selected reference samples.
14. A picture component prediction method, applied to an encoder, the method comprising: determining a first picture component reference value set of a current block; determining multiple first picture component reference values according to the first picture component reference value set, wherein the multiple first picture component reference values include four reference values corresponding to four preset sample positions, respectively; performing first filtering processing on sample values of samples corresponding to the multiple first picture component reference values, respectively, to determine multiple filtered first picture reference sample values; determining a parameter of a component linear model according to the multiple filtered first picture reference sample values and a corresponding to-be-predicted picture component reference values, the to-be-predicted picture component being a picture component which is different from the first picture component, and the component linear model characterizing a linear mapping relationship for mapping a sample value of the first picture component to a sample value of the to-be-predicted picture component; performing mapping processing on a reconstructed value of the first picture component of the current block according to the component linear model to obtain a mapped value; and determining a predicted value of the to-be-predicted picture component of the current block according to the mapped value.
16. The method of claim 15, wherein determining the multiple first picture component reference values according to the first picture component reference value set comprises: selecting two reference samples from the samples in the one or more neighboring lines at the top side of the current block according to a preset position, and selecting two reference samples from the samples in the one or more neighboring columns at the left side of the current block according to a preset position; determining the multiple first picture component reference values according to the four selected samples.
16. The non-transitory computer-readable storage medium of claim 15, wherein determining the first picture component reference sample set of the current block comprises: determining multiple reference samples that locate outside of the current block, and determining the multiple reference samples as the first picture component reference sample set.
15. The method of claim 14, wherein determining the first picture component reference value set of a current block comprises: determining one or more reference samples that locate outside of the current block, and determining the one or more reference samples as the first picture component reference value set, wherein determining the one or more reference samples that locate outside of the current block comprises: determining neighboring samples of the current block as one or more reference samples; wherein the neighboring samples of the current block comprise at least one of: samples in one or more neighboring lines at a top side of the current block, or samples in one or more neighboring columns at a left side of the current block.
17. The non-transitory computer-readable storage medium of claim 15, wherein performing first filtering processing on the multiple first picture component reference samples, to determine the multiple filtered first picture reference samples comprises: performing first filtering processing on the multiple first picture component reference samples to obtain a filtered reference sample set; by comparing reference samples in the filtered reference sample set, determining a set of greater first picture component reference samples and a set of smaller first picture component reference samples; and determining a filtered maximum first picture component reference sample and a filtered minimum first picture component reference sample based on the set of greater first picture component reference samples and the set of smaller first picture component reference samples; wherein a number of samples in the set of greater first picture component reference samples is 2, and a number of samples in the set of smaller first picture component reference samples is 2.
17. The method of claim of claim 14, wherein the first filtering processing is performed on the sample values of the samples corresponding to the multiple first picture component reference values to obtain a filtered reference value set, and wherein reference sample values in the filtered reference value set are compared, and wherein a set of greater first picture component reference values and a set of smaller first picture component reference values are determined based on the reference sample values, wherein the multiple filtered first picture reference sample values are determined by using multiple values from each of the set of greater first picture component reference values and the set of smaller first picture component reference values.
18. The method of claim 17, wherein determining the multiple filtered first picture reference sample values based on the set of greater first picture component reference values and set of smaller first picture component reference values comprises: performing mean processing on the set of greater first picture component reference values to obtain a filtered maximum first picture component reference value; and performing mean processing on the set of smaller first picture component reference values to obtain a filtered minimum first picture component reference value.
19. The method of claim 17, wherein a number of sample values in the set of greater first picture component reference values is an integer which is equal to or greater than 1, and a number of sample values in the set of smaller first picture component reference values is an integer which is equal to or greater than 1, wherein the number of sample values in the set of greater first picture component reference values is 2, and a number of sample values in the set of smaller first picture component reference values is 2.
18. The non-transitory computer-readable storage medium of claim 17, the method further comprising: determining a maximum to-be-predicted picture component reference sample corresponding to the filtered maximum first picture component reference sample and a minimum to-be-predicted picture component reference sample corresponding to the filtered minimum first picture component reference sample; and determining the parameter of the component model according to the filtered maximum first picture component reference sample, the maximum to-be-predicted picture component reference sample, the filtered minimum first picture component reference sample and the minimum to-be-predicted picture component reference sample.
18. The method of claim 17, wherein determining the multiple filtered first picture reference sample values based on the set of greater first picture component reference values and set of smaller first picture component reference values comprises: performing mean processing on the set of greater first picture component reference values to obtain a filtered maximum first picture component reference value; and performing mean processing on the set of smaller first picture component reference values to obtain a filtered minimum first picture component reference value.
19. The non-transitory computer-readable storage medium of claim 15, wherein performing mapping processing on the reconstructed sample of the first picture component of the current block according to the component model to obtain the mapped sample comprises: performing second filtering processing on the reconstructed samples of the first picture component to obtain a second filtered sample of the reconstructed samples of the first picture component; and performing mapping processing on the second filtered sample according to the component model to obtain the mapped sample; wherein second filtering processing is down-sampling filtering.
10. The method of claim 1, wherein performing mapping processing on the reconstructed value of the first picture component of the current block according to the component linear model to obtain the mapped value comprises: performing second filtering processing on the reconstructed value of the first picture component to obtain a second filtered value of the reconstructed value of the first picture component; and performing mapping processing on the second filtered value according to the component linear model to obtain the mapped value, wherein second filtering processing is down-sampling filtering or low-pass filtering.
20. The non-transitory computer-readable storage medium of claim 18, wherein determining the maximum to-be-predicted picture component reference sample corresponding to the filtered maximum first picture component reference sample and the minimum to-be-predicted picture component reference sample corresponding to the filtered minimum first picture component reference sample comprises: determining a set of greater to-be-predicted picture component reference samples corresponding to the reference samples in the set of greater first picture component reference samples and a set of smaller to-be-predicted picture component reference samples corresponding to the reference samples in the set of smaller first picture component reference samples; determining the maximum to-be-predicted picture component reference sample based on a mean processing on reference samples in the set of greater to-be-predicted picture component reference samples, and determining the minimum to-be-predicted picture component reference sample based on a mean processing on reference samples in the set of smaller the to-be-predicted picture component reference samples.
18. The method of claim 17, wherein determining the multiple filtered first picture reference sample values based on the set of greater first picture component reference values and set of smaller first picture component reference values comprises: performing mean processing on the set of greater first picture component reference values to obtain a filtered maximum first picture component reference value; and performing mean processing on the set of smaller first picture component reference values to obtain a filtered minimum first picture component reference value.
Claims 1 – 20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1- 7, and 10 - 17 of U.S. Patent No. 12,323,584. Although the claims at issue are not identical, they are not patentably distinct from each other because the scope of the patented case wholly encompasses the scope of the current application.
Current Application
U.S. Patent No. 12,323,584
1. A decoder for picture component prediction, comprising: a memory for storing executable video component prediction instructions; and a processor configured to perform the executable video component prediction instructions stored in the memory to perform following operations: determining a first picture component reference sample set of a current block; determining multiple first picture component reference samples according to the first picture component reference sample set; performing first filtering processing on the multiple first picture component reference samples, to determine multiple filtered first picture reference samples; determining a parameter of a component model according to the multiple filtered first picture reference samples and corresponding to-be-predicted picture component reference samples, a to-be-predicted picture component being a picture component which is different from a first picture component, and the component model characterizing a mapping relationship for mapping a sample of the first picture component to a sample of the to-be-predicted picture component; performing mapping processing on a reconstructed sample of the first picture component of the current block according to the component model to obtain a mapped sample; and determining a predicted sample of the to-be-predicted picture component of the current block according to the mapped sample, wherein determining multiple first picture component reference samples according to the first picture component reference sample set comprises: determining multiple reference samples based on samples in multiple neighboring lines at a top side of the current block according to two preset positions, and determining multiple reference samples based on samples in multiple neighboring columns at a left side of the current block according to two preset positions; and determining the multiple first picture component reference samples according to the selected reference samples.
1. A picture component prediction method, applied to a decoder, the method comprising: determining a first picture component reference value set of a current block; determining multiple first picture component reference values according to the first picture component reference value set, wherein the multiple first picture component reference values include four reference values corresponding to four preset sample positions, respectively; performing first filtering processing on sample values of samples corresponding to the multiple first picture component reference values, respectively, to determine multiple filtered first picture reference sample values; determining a parameter of a component linear model according to the multiple filtered first picture reference sample values and corresponding to-be-predicted picture component reference values, the to-be-predicted picture component being a picture component which is different from the first picture component, and the component linear model characterizing a linear mapping relationship for mapping a sample value of the first picture component to a sample value of the to-be-predicted picture component; performing mapping processing on a reconstructed value of the first picture component of the current block according to the component linear model to obtain a mapped value; and determining a predicted value of the to-be-predicted picture component of the current block according to the mapped value; wherein determining the multiple first picture component reference values according to the first picture component reference value set comprises: selecting two reference samples from samples in one or more neighboring lines at a top side of the current block according to preset positions, and selecting two reference samples from samples in one or more neighboring columns at a left side of the current block according to preset positions; and determining the multiple first picture component reference values according to the four selected samples.
2. The decoder of claim 1, wherein determining the first picture component reference sample set of the current block comprises: determining multiple reference samples that locate outside of the current block, and determining the multiple reference samples as the first picture component reference sample set.
3. The decoder of claim 1, wherein performing first filtering processing on the multiple first picture component reference samples, to determine the multiple filtered first picture reference samples comprises: performing first filtering processing on the multiple first picture component reference samples to obtain a filtered reference sample set; by comparing reference samples in the filtered reference sample set, determining a set of greater first picture component reference samples and a set of smaller first picture component reference samples; and determining a filtered maximum first picture component reference sample and a filtered minimum first picture component reference sample based on the set of greater first picture component reference samples and the set of smaller first picture component reference samples; wherein a number of samples in the set of greater first picture component reference samples is 2, and a number of samples in the set of smaller first picture component reference samples is 2.
2. The method of claim of claim 1, wherein the first filtering processing is performed on the sample values of the samples corresponding to the multiple first picture component reference values to obtain a filtered reference value set, and wherein reference sample values in the filtered reference value set are compared, and wherein a set of greater first picture component reference values and a set of smaller first picture component reference values are determined based on the reference sample values, wherein the multiple filtered first picture reference sample values are determined by using multiple values from each of the set of greater first picture component reference values and the set of smaller first picture component reference values.
3. The method of claim 2, wherein determining the multiple filtered first picture reference sample values based on the set of greater first picture component reference values and set of smaller first picture component reference values comprises: performing mean processing on the set of greater first picture component reference values to obtain a filtered maximum first picture component reference value; and performing mean processing on the set of smaller first picture component reference values to obtain a filtered minimum first picture component reference value.
4. The method of claim 2, wherein a number of sample values in the set of greater first picture component reference values is an integer which is equal to or greater than 1, and a number of sample values in the set of smaller first picture component reference values is an integer which is equal to or greater than 1, wherein the number of sample values in the set of greater first picture component reference values is 2, and a number of sample values in the set of smaller first picture component reference values is 2.
4. The decoder of claim 3, the operations further comprising: determining a maximum to-be-predicted picture component reference sample corresponding to the filtered maximum first picture component reference sample and a minimum to-be-predicted picture component reference sample corresponding to the filtered minimum first picture component reference sample; and determining the parameter of the component model according to the filtered maximum first picture component reference sample, the maximum to-be-predicted picture component reference sample, the filtered minimum first picture component reference sample and the minimum to-be-predicted picture component reference sample.
5. The method of claim 3, further comprising: determining a maximum to-be-predicted picture component reference value corresponding to the filtered maximum first picture component reference value and a minimum to-be-predicted picture component reference value corresponding to the filtered minimum first picture component reference value.
6. The method of claim 5, wherein determining the parameter of the component linear model according to the multiple filtered first picture reference sample values and corresponding to-be-predicted picture component reference values comprises: determining the parameter of the component linear model according to the filtered maximum first picture component reference value, the maximum to-be-predicted picture component reference value, the filtered minimum first picture component reference value and the minimum to-be-predicted picture component reference value, the component linear model characterizing the linear mapping relationship for mapping the sample value of the first picture component to the sample value of the to-be-predicted picture component.
5. The decoder of claim 1, wherein performing mapping processing on the reconstructed sample of the first picture component of the current block according to the component model to obtain the mapped sample comprises: performing second filtering processing on the reconstructed samples of the first picture component to obtain a second filtered sample of the reconstructed samples of the first picture component; and performing mapping processing on the second filtered sample according to the component model to obtain the mapped sample; wherein second filtering processing is down-sampling filtering.
7. The method of claim 1, wherein performing mapping processing on the reconstructed value of the first picture component of the current block according to the component linear model to obtain the mapped value comprises: performing second filtering processing on the reconstructed value of the first picture component to obtain a second filtered value of the reconstructed value of the first picture component; and performing mapping processing on the second filtered value according to the component linear model to obtain the mapped value, wherein second filtering processing is down-sampling filtering or low-pass filtering.
6. The decoder of claim 4, wherein determining the maximum to-be-predicted picture component reference sample corresponding to the filtered maximum first picture component reference sample and the minimum to-be-predicted picture component reference sample corresponding to the filtered minimum first picture component reference sample comprises: determining a set of greater to-be-predicted picture component reference samples corresponding to the reference samples in the set of greater first picture component reference samples and a set of smaller to-be-predicted picture component reference samples corresponding to the reference samples in the set of smaller first picture component reference samples; determining the maximum to-be-predicted picture component reference sample based on a mean processing on reference samples in the set of greater to-be-predicted picture component reference samples, and determining the minimum to-be-predicted picture component reference sample based on a mean processing on reference samples in the set of smaller the to-be-predicted picture component reference samples.
3. The method of claim 2, wherein determining the multiple filtered first picture reference sample values based on the set of greater first picture component reference values and set of smaller first picture component reference values comprises: performing mean processing on the set of greater first picture component reference values to obtain a filtered maximum first picture component reference value; and performing mean processing on the set of smaller first picture component reference values to obtain a filtered minimum first picture component reference value.
7. The decoder of claim 1, wherein the first picture component is a luma component, and the to-be-predicted picture component is a first or second chroma component.
10. The method of claim 1, wherein the first picture component is a luma component, and the to-be-predicted picture component is a first or second chroma component; or the first picture component is the first chroma component, and the to-be-predicted picture component is the luma component or the second chroma component; or the first picture component is the second chroma component, and the to-be-predicted picture component is the luma component or the first chroma component; or the first picture component is a first colour component, and the to-be-predicted picture component is a second colour component or a third colour component; or the first picture component is the second colour component, and the to-be-predicted picture component is the first colour component or the third colour component; or the first picture component is the third colour component, and the to-be-predicted picture component is the second colour component or the first colour component, wherein the first colour component is a red component, the second colour component is a green component, and the third colour component is a blue component.
8. An encoder for picture component prediction, comprising: determining a first picture component reference sample set of a current block; determining multiple first picture component reference samples according to the first picture component reference sample set; performing first filtering processing on the multiple first picture component reference samples, to determine multiple filtered first picture reference samples; determining a parameter of a component model according to the multiple filtered first picture reference samples and corresponding to-be-predicted picture component reference samples, a to-be-predicted picture component being a picture component which is different from a first picture component, and the component model characterizing a mapping relationship for mapping a sample of the first picture component to a sample of the to-be-predicted picture component; performing mapping processing on a reconstructed sample of the first picture component of the current block according to the component model to obtain a mapped sample; and determining a predicted sample of the to-be-predicted picture component of the current block according to the mapped sample, wherein determining multiple first picture component reference samples according to the first picture component reference sample set comprises: determining multiple reference samples based on samples in multiple neighboring lines at a top side of the current block according to two preset positions, and determining multiple reference samples based on samples in multiple neighboring columns at a left side of the current block according to two preset positions; and determining the multiple first picture component reference samples according to the selected reference samples.
11. A picture component prediction method, applied to an encoder, the method comprising: determining a first picture component reference value set of a current block; determining multiple first picture component reference values according to the first picture component reference value set, wherein the multiple first picture component reference values include four reference values corresponding to four preset sample positions, respectively; performing first filtering processing on sample values of samples corresponding to the multiple first picture component reference values, respectively, to determine multiple filtered first picture reference sample values; determining a parameter of a component linear model according to the multiple filtered first picture reference sample values and corresponding to-be-predicted picture component reference values, the to-be-predicted picture component being a picture component which is different from the first picture component, and the component linear model characterizing a linear mapping relationship for mapping a sample value of the first picture component to a sample value of the to-be-predicted picture component; performing mapping processing on a reconstructed value of the first picture component of the current block according to the component linear model to obtain a mapped value; and determining a predicted value of the to-be-predicted picture component of the current block according to the mapped value; wherein determining the multiple first picture component reference values according to the first picture component reference value set comprises: selecting two reference samples from samples in one or more neighboring lines at a top side of the current block according to preset positions, and selecting two reference samples from samples in one or more neighboring columns at a left side of the current block according to preset positions; and determining the multiple first picture component reference values according to the four selected samples.
9. The encoder of claim 8, wherein determining the first picture component reference sample set of the current block comprises: determining multiple reference samples that locate outside of the current block, and determining the multiple reference samples as the first picture component reference sample set.
10. The encoder of claim 8, wherein performing first filtering processing on the multiple first picture component reference samples, to determine the multiple filtered first picture reference samples comprises: performing first filtering processing on the multiple first picture component reference samples to obtain a filtered reference sample set; by comparing reference samples in the filtered reference sample set, determining a set of greater first picture component reference samples and a set of smaller first picture component reference samples; and determining a filtered maximum first picture component reference sample and a filtered minimum first picture component reference sample based on the set of greater first picture component reference samples and the set of smaller first picture component reference samples; wherein a number of samples in the set of greater first picture component reference samples is 2, and a number of samples in the set of smaller first picture component reference samples is 2.
12. The method of claim of claim 11, wherein the first filtering processing is performed on the sample values of the samples corresponding to the multiple first picture component reference values to obtain a filtered reference value set, and wherein reference sample values in the filtered reference value set are compared, and wherein a set of greater first picture component reference values and a set of smaller first picture component reference values are determined based on the reference sample values, wherein the multiple filtered first picture reference sample values are determined by using multiple values from each of the set of greater first picture component reference values and the set of smaller first picture component reference values.
13. The method of claim 12, wherein determining the multiple filtered first picture reference sample values based on the set of greater first picture component reference values and set of smaller first picture component reference values comprises: performing mean processing on the set of greater first picture component reference values to obtain a filtered maximum first picture component reference value; and performing mean processing on the set of smaller first picture component reference values to obtain a filtered minimum first picture component reference value.
14. The method of claim 12, wherein a number of sample values in the set of greater first picture component reference values is an integer which is equal to or greater than 1, and a number of sample values in the set of smaller first picture component reference values is an integer which is equal to or greater than 1, wherein the number of sample values in the set of greater first picture component reference values is 2, and a number of sample values in the set of smaller first picture component reference values is 2.
11. The encoder of claim 10, the operations further comprising: determining a maximum to-be-predicted picture component reference sample corresponding to the filtered maximum first picture component reference sample and a minimum to-be-predicted picture component reference sample corresponding to the filtered minimum first picture component reference sample; and determining the parameter of the component model according to the filtered maximum first picture component reference sample, the maximum to-be-predicted picture component reference sample, the filtered minimum first picture component reference sample and the minimum to-be-predicted picture component reference sample.
15. The method of claim 13, further comprising: determining a maximum to-be-predicted picture component reference value corresponding to the filtered maximum first picture component reference value and a minimum to-be-predicted picture component reference value corresponding to the filtered minimum first picture component reference value.
16. The method of claim 15, wherein determining the parameter of the component linear model according to the multiple filtered first picture reference sample values and corresponding to-be-predicted picture component reference values comprises: determining the parameter of the component linear model according to the filtered maximum first picture component reference value, the maximum to-be-predicted picture component reference value, the filtered minimum first picture component reference value and the minimum to-be-predicted picture component reference value, the component linear model characterizing the linear mapping relationship for mapping the sample value of the first picture component to the sample value of the to-be-predicted picture component.
12. The encoder of claim 8, wherein performing mapping processing on the reconstructed sample of the first picture component of the current block according to the component model to obtain the mapped sample comprises: performing second filtering processing on the reconstructed samples of the first picture component to obtain a second filtered sample of the reconstructed samples of the first picture component; and performing mapping processing on the second filtered sample according to the component model to obtain the mapped sample; wherein second filtering processing is down-sampling filtering.
17. The method of claim 11, wherein performing mapping processing on the reconstructed value of the first picture component of the current block according to the component linear model to obtain the mapped value comprises: performing second filtering processing on the reconstructed value of the first picture component to obtain a second filtered value of the reconstructed value of the first picture component; and performing mapping processing on the second filtered value according to the component linear model to obtain the mapped value, wherein second filtering processing is down-sampling filtering or low-pass filtering.
13. The encoder of claim 11, wherein determining the maximum to-be-predicted picture component reference sample corresponding to the filtered maximum first picture component reference sample and the minimum to-be-predicted picture component reference sample corresponding to the filtered minimum first picture component reference sample comprises: determining a set of greater to-be-predicted picture component reference samples corresponding to the reference samples in the set of greater first picture component reference samples and a set of smaller to-be-predicted picture component reference samples corresponding to the reference samples in the set of smaller first picture component reference samples; determining the maximum to-be-predicted picture component reference sample based on a mean processing on reference samples in the set of greater to-be-predicted picture component reference samples, and determining the minimum to-be-predicted picture component reference sample based on a mean processing on reference samples in the set of smaller the to-be-predicted picture component reference samples.
13. The method of claim 12, wherein determining the multiple filtered first picture reference sample values based on the set of greater first picture component reference values and set of smaller first picture component reference values comprises: performing mean processing on the set of greater first picture component reference values to obtain a filtered maximum first picture component reference value; and performing mean processing on the set of smaller first picture component reference values to obtain a filtered minimum first picture component reference value.
14. The encoder of claim 8, wherein the first picture component is a luma component, and the to-be-predicted picture component is a first or second chroma component.
10. The method of claim 1, wherein the first picture component is a luma component, and the to-be-predicted picture component is a first or second chroma component; or the first picture component is the first chroma component, and the to-be-predicted picture component is the luma component or the second chroma component; or the first picture component is the second chroma component, and the to-be-predicted picture component is the luma component or the first chroma component; or the first picture component is a first colour component, and the to-be-predicted picture component is a second colour component or a third colour component; or the first picture component is the second colour component, and the to-be-predicted picture component is the first colour component or the third colour component; or the first picture component is the third colour component, and the to-be-predicted picture component is the second colour component or the first colour component, wherein the first colour component is a red component, the second colour component is a green component, and the third colour component is a blue component.
15. A non-transitory computer-readable storage medium, having a computer program and a bitstream stored thereon, wherein the computer program, when executed by a processor, enables the processor to perform an encoding method to generate the bitstream, and the encoding method comprises: determining a first picture component reference sample set of a current block; determining multiple first picture component reference samples according to the first picture component reference sample set; performing first filtering processing on the multiple first picture component reference samples, to determine multiple filtered first picture reference samples; determining a parameter of a component model according to the multiple filtered first picture reference samples and corresponding to-be-predicted picture component reference samples, a to-be-predicted picture component being a picture component which is different from a first picture component, and the component model characterizing a mapping relationship for mapping a sample of the first picture component to a sample of the to-be-predicted picture component; performing mapping processing on a reconstructed sample of the first picture component of the current block according to the component model to obtain a mapped sample; and determining a predicted sample of the to-be-predicted picture component of the current block according to the mapped sample, wherein determining multiple first picture component reference samples according to the first picture component reference sample set comprises: determining multiple reference samples based on samples in multiple neighboring lines at a top side of the current block according to two preset positions, and determining multiple reference samples based on samples in multiple neighboring columns at a left side of the current block according to two preset positions; and determining the multiple first picture component reference samples according to the selected reference samples.
11. A picture component prediction method, applied to an encoder, the method comprising: determining a first picture component reference value set of a current block; determining multiple first picture component reference values according to the first picture component reference value set, wherein the multiple first picture component reference values include four reference values corresponding to four preset sample positions, respectively; performing first filtering processing on sample values of samples corresponding to the multiple first picture component reference values, respectively, to determine multiple filtered first picture reference sample values; determining a parameter of a component linear model according to the multiple filtered first picture reference sample values and corresponding to-be-predicted picture component reference values, the to-be-predicted picture component being a picture component which is different from the first picture component, and the component linear model characterizing a linear mapping relationship for mapping a sample value of the first picture component to a sample value of the to-be-predicted picture component; performing mapping processing on a reconstructed value of the first picture component of the current block according to the component linear model to obtain a mapped value; and determining a predicted value of the to-be-predicted picture component of the current block according to the mapped value; wherein determining the multiple first picture component reference values according to the first picture component reference value set comprises: selecting two reference samples from samples in one or more neighboring lines at a top side of the current block according to preset positions, and selecting two reference samples from samples in one or more neighboring columns at a left side of the current block according to preset positions; and determining the multiple first picture component reference values according to the four selected samples.
16. The non-transitory computer-readable storage medium of claim 15, wherein determining the first picture component reference sample set of the current block comprises: determining multiple reference samples that locate outside of the current block, and determining the multiple reference samples as the first picture component reference sample set.
17. The non-transitory computer-readable storage medium of claim 15, wherein performing first filtering processing on the multiple first picture component reference samples, to determine the multiple filtered first picture reference samples comprises: performing first filtering processing on the multiple first picture component reference samples to obtain a filtered reference sample set; by comparing reference samples in the filtered reference sample set, determining a set of greater first picture component reference samples and a set of smaller first picture component reference samples; and determining a filtered maximum first picture component reference sample and a filtered minimum first picture component reference sample based on the set of greater first picture component reference samples and the set of smaller first picture component reference samples; wherein a number of samples in the set of greater first picture component reference samples is 2, and a number of samples in the set of smaller first picture component reference samples is 2.
12. The method of claim of claim 11, wherein the first filtering processing is performed on the sample values of the samples corresponding to the multiple first picture component reference values to obtain a filtered reference value set, and wherein reference sample values in the filtered reference value set are compared, and wherein a set of greater first picture component reference values and a set of smaller first picture component reference values are determined based on the reference sample values, wherein the multiple filtered first picture reference sample values are determined by using multiple values from each of the set of greater first picture component reference values and the set of smaller first picture component reference values.
13. The method of claim 12, wherein determining the multiple filtered first picture reference sample values based on the set of greater first picture component reference values and set of smaller first picture component reference values comprises: performing mean processing on the set of greater first picture component reference values to obtain a filtered maximum first picture component reference value; and performing mean processing on the set of smaller first picture component reference values to obtain a filtered minimum first picture component reference value.
14. The method of claim 12, wherein a number of sample values in the set of greater first picture component reference values is an integer which is equal to or greater than 1, and a number of sample values in the set of smaller first picture component reference values is an integer which is equal to or greater than 1, wherein the number of sample values in the set of greater first picture component reference values is 2, and a number of sample values in the set of smaller first picture component reference values is 2.
18. The non-transitory computer-readable storage medium of claim 17, the method further comprising: determining a maximum to-be-predicted picture component reference sample corresponding to the filtered maximum first picture component reference sample and a minimum to-be-predicted picture component reference sample corresponding to the filtered minimum first picture component reference sample; and determining the parameter of the component model according to the filtered maximum first picture component reference sample, the maximum to-be-predicted picture component reference sample, the filtered minimum first picture component reference sample and the minimum to-be-predicted picture component reference sample.
15. The method of claim 13, further comprising: determining a maximum to-be-predicted picture component reference value corresponding to the filtered maximum first picture component reference value and a minimum to-be-predicted picture component reference value corresponding to the filtered minimum first picture component reference value.
16. The method of claim 15, wherein determining the parameter of the component linear model according to the multiple filtered first picture reference sample values and corresponding to-be-predicted picture component reference values comprises: determining the parameter of the component linear model according to the filtered maximum first picture component reference value, the maximum to-be-predicted picture component reference value, the filtered minimum first picture component reference value and the minimum to-be-predicted picture component reference value, the component linear model characterizing the linear mapping relationship for mapping the sample value of the first picture component to the sample value of the to-be-predicted picture component.
19. The non-transitory computer-readable storage medium of claim 15, wherein performing mapping processing on the reconstructed sample of the first picture component of the current block according to the component model to obtain the mapped sample comprises: performing second filtering processing on the reconstructed samples of the first picture component to obtain a second filtered sample of the reconstructed samples of the first picture component; and performing mapping processing on the second filtered sample according to the component model to obtain the mapped sample; wherein second filtering processing is down-sampling filtering.
17. The method of claim 11, wherein performing mapping processing on the reconstructed value of the first picture component of the current block according to the component linear model to obtain the mapped value comprises: performing second filtering processing on the reconstructed value of the first picture component to obtain a second filtered value of the reconstructed value of the first picture component; and performing mapping processing on the second filtered value according to the component linear model to obtain the mapped value, wherein second filtering processing is down-sampling filtering or low-pass filtering.
20. The non-transitory computer-readable storage medium of claim 18, wherein determining the maximum to-be-predicted picture component reference sample corresponding to the filtered maximum first picture component reference sample and the minimum to-be-predicted picture component reference sample corresponding to the filtered minimum first picture component reference sample comprises: determining a set of greater to-be-predicted picture component reference samples corresponding to the reference samples in the set of greater first picture component reference samples and a set of smaller to-be-predicted picture component reference samples corresponding to the reference samples in the set of smaller first picture component reference samples; determining the maximum to-be-predicted picture component reference sample based on a mean processing on reference samples in the set of greater to-be-predicted picture component reference samples, and determining the minimum to-be-predicted picture component reference sample based on a mean processing on reference samples in the set of smaller the to-be-predicted picture component reference samples.
10. The method of claim 1, wherein the first picture component is a luma component, and the to-be-predicted picture component is a first or second chroma component; or the first picture component is the first chroma component, and the to-be-predicted picture component is the luma component or the second chroma component; or the first picture component is the second chroma component, and the to-be-predicted picture component is the luma component or the first chroma component; or the first picture component is a first colour component, and the to-be-predicted picture component is a second colour component or a third colour component; or the first picture component is the second colour component, and the to-be-predicted picture component is the first colour component or the third colour component; or the first picture component is the third colour component, and the to-be-predicted picture component is the second colour component or the first colour component, wherein the first colour component is a red component, the second colour component is a green component, and the third colour component is a blue component.
Claims 1 – 5 and 7 - 20 are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1, 2, 4 – 10, and 13 - 19 of copending Application No. 19/073,537 (reference application). Although the claims at issue are not identical, they are not patentably distinct from each other because the scope of the copending application wholly encompass the scope of the current application.
This is a provisional nonstatutory double patenting rejection because the patentably indistinct claims have not in fact been patented.
Current Application
Copending Application No. 19/073,537
1. A decoder for picture component prediction, comprising: a memory for storing executable video component prediction instructions; and a processor configured to perform the executable video component prediction instructions stored in the memory to perform following operations: determining a first picture component reference sample set of a current block; determining multiple first picture component reference samples according to the first picture component reference sample set; performing first filtering processing on the multiple first picture component reference samples, to determine multiple filtered first picture reference samples; determining a parameter of a component model according to the multiple filtered first picture reference samples and corresponding to-be-predicted picture component reference samples, a to-be-predicted picture component being a picture component which is different from a first picture component, and the component model characterizing a mapping relationship for mapping a sample of the first picture component to a sample of the to-be-predicted picture component; performing mapping processing on a reconstructed sample of the first picture component of the current block according to the component model to obtain a mapped sample; and determining a predicted sample of the to-be-predicted picture component of the current block according to the mapped sample, wherein determining multiple first picture component reference samples according to the first picture component reference sample set comprises: determining multiple reference samples based on samples in multiple neighboring lines at a top side of the current block according to two preset positions, and determining multiple reference samples based on samples in multiple neighboring columns at a left side of the current block according to two preset positions; and determining the multiple first picture component reference samples according to the selected reference samples.
1. A picture component prediction method, applied to a decoder, the method comprising: determining a first picture component reference value set of a current block; determining multiple first picture component reference values according to the first picture component reference value set, wherein the multiple first picture component reference values include four reference values corresponding to four preset sample positions, respectively; performing first filtering processing on sample values of samples corresponding to the multiple first picture component reference values, respectively, to determine multiple filtered first picture reference sample values; determining a parameter of a component linear model according to the multiple filtered first picture reference sample values and corresponding to-be-predicted picture component reference values, the to-be-predicted picture component being a picture component which is different from the first picture component, and the component linear model characterizing a linear mapping relationship for mapping a sample value of the first picture component to a sample value of the to-be-predicted picture component; performing mapping processing on a reconstructed value of the first picture component of the current block according to the component linear model to obtain a mapped value; and determining a predicted value of the to-be-predicted picture component of the current block according to the mapped value; wherein determining the multiple first picture component reference values according to the first picture component reference value set comprises: determining the multiple first picture component reference values from samples in one or more neighboring lines at a top side of the current block according to four preset positions, or determining the multiple first picture component reference values from samples in one or more neighboring columns at a left side of the current block according to four preset positions;
2. The decoder of claim 1, wherein determining the first picture component reference sample set of the current block comprises: determining multiple reference samples that locate outside of the current block, and determining the multiple reference samples as the first picture component reference sample set.
3. The decoder of claim 1, wherein performing first filtering processing on the multiple first picture component reference samples, to determine the multiple filtered first picture reference samples comprises: performing first filtering processing on the multiple first picture component reference samples to obtain a filtered reference sample set; by comparing reference samples in the filtered reference sample set, determining a set of greater first picture component reference samples and a set of smaller first picture component reference samples; and determining a filtered maximum first picture component reference sample and a filtered minimum first picture component reference sample based on the set of greater first picture component reference samples and the set of smaller first picture component reference samples; wherein a number of samples in the set of greater first picture component reference samples is 2, and a number of samples in the set of smaller first picture component reference samples is 2.
2. The method of claim of claim 1, wherein the first filtering processing is performed on the sample values of the samples corresponding to the multiple first picture component reference values to obtain a filtered reference value set, and wherein reference sample values in the filtered reference value set are compared, and wherein a set of greater first picture component reference values and a set of smaller first picture component reference values are determined based on the reference sample values, wherein the multiple filtered first picture reference sample values are determined by using multiple values from each of the set of greater first picture component reference values and the set of smaller first picture component reference values.
4. The method of claim 2, wherein a number of sample values in the set of greater first picture component reference values is an integer which is equal to or greater than 1, and a number of sample values in the set of smaller first picture component reference values is an integer which is equal to or greater than 1, wherein the number of sample values in the set of greater first picture component reference values is 2, and a number of sample values in the set of smaller first picture component reference values is 2.
4. The decoder of claim 3, the operations further comprising: determining a maximum to-be-predicted picture component reference sample corresponding to the filtered maximum first picture component reference sample and a minimum to-be-predicted picture component reference sample corresponding to the filtered minimum first picture component reference sample; and determining the parameter of the component model according to the filtered maximum first picture component reference sample, the maximum to-be-predicted picture component reference sample, the filtered minimum first picture component reference sample and the minimum to-be-predicted picture component reference sample.
5. The method of claim 3, further comprising: determining a maximum to-be-predicted picture component reference value corresponding to the filtered maximum first picture component reference value and a minimum to-be-predicted picture component reference value corresponding to the filtered minimum first picture component reference value.
6. The method of claim 5, wherein determining the parameter of the component linear model according to the multiple filtered first picture reference sample values and corresponding to-be-predicted picture component reference values comprises: determining the parameter of the component linear model according to the filtered maximum first picture component reference value, the maximum to-be-predicted picture component reference value, the filtered minimum first picture component reference value and the minimum to-be-predicted picture component reference value, the component linear model characterizing the linear mapping relationship for mapping the sample value of the first picture component to the sample value of the to-be-predicted picture component.
5. The decoder of claim 1, wherein performing mapping processing on the reconstructed sample of the first picture component of the current block according to the component model to obtain the mapped sample comprises: performing second filtering processing on the reconstructed samples of the first picture component to obtain a second filtered sample of the reconstructed samples of the first picture component; and performing mapping processing on the second filtered sample according to the component model to obtain the mapped sample; wherein second filtering processing is down-sampling filtering.
7. The method of claim 1, wherein performing mapping processing on the reconstructed value of the first picture component of the current block according to the component linear model to obtain the mapped value comprises: performing second filtering processing on the reconstructed value of the first picture component to obtain a second filtered value of the reconstructed value of the first picture component; and performing mapping processing on the second filtered value according to the component linear model to obtain the mapped value, wherein second filtering processing is down-sampling filtering or low-pass filtering.
7. The decoder of claim 1, wherein the first picture component is a luma component, and the to-be-predicted picture component is a first or second chroma component.
10. The method of claim 1, wherein the first picture component is a luma component, and the to-be-predicted picture component is a first or second chroma component; or the first picture component is the first chroma component, and the to-be-predicted picture component is the luma component or the second chroma component; or the first picture component is the second chroma component, and the to-be-predicted picture component is the luma component or the first chroma component; or the first picture component is a first colour component, and the to-be-predicted picture component is a second colour component or a third colour component; or the first picture component is the second colour component, and the to-be-predicted picture component is the first colour component or the third colour component; or the first picture component is the third colour component, and the to-be-predicted picture component is the second colour component or the first colour component, wherein the first colour component is a red component, the second colour component is a green component, and the third colour component is a blue component.
8. An encoder for picture component prediction, comprising: determining a first picture component reference sample set of a current block; determining multiple first picture component reference samples according to the first picture component reference sample set; performing first filtering processing on the multiple first picture component reference samples, to determine multiple filtered first picture reference samples; determining a parameter of a component model according to the multiple filtered first picture reference samples and corresponding to-be-predicted picture component reference samples, a to-be-predicted picture component being a picture component which is different from a first picture component, and the component model characterizing a mapping relationship for mapping a sample of the first picture component to a sample of the to-be-predicted picture component; performing mapping processing on a reconstructed sample of the first picture component of the current block according to the component model to obtain a mapped sample; and determining a predicted sample of the to-be-predicted picture component of the current block according to the mapped sample, wherein determining multiple first picture component reference samples according to the first picture component reference sample set comprises: determining multiple reference samples based on samples in multiple neighboring lines at a top side of the current block according to two preset positions, and determining multiple reference samples based on samples in multiple neighboring columns at a left side of the current block according to two preset positions; and determining the multiple first picture component reference samples according to the selected reference samples.
11. A picture component prediction method, applied to an encoder, the method comprising: determining a first picture component reference value set of a current block; determining multiple first picture component reference values according to the first picture component reference value set, wherein the multiple first picture component reference values include four reference values corresponding to four preset sample positions, respectively; performing first filtering processing on sample values of samples corresponding to the multiple first picture component reference values, respectively, to determine multiple filtered first picture reference sample values; determining a parameter of a component linear model according to the multiple filtered first picture reference sample values and corresponding to-be-predicted picture component reference values, the to-be-predicted picture component being a picture component which is different from the first picture component, and the component linear model characterizing a linear mapping relationship for mapping a sample value of the first picture component to a sample value of the to-be-predicted picture component; performing mapping processing on a reconstructed value of the first picture component of the current block according to the component linear model to obtain a mapped value; and determining a predicted value of the to-be-predicted picture component of the current block according to the mapped value; wherein determining the multiple first picture component reference values according to the first picture component reference value set comprises: determining the multiple first picture component reference values from samples in one or more neighboring lines at a top side of the current block according to four preset positions, or determining the multiple first picture component reference values from samples in one or more neighboring columns at a left side of the current block according to four preset positions
9. The encoder of claim 8, wherein determining the first picture component reference sample set of the current block comprises: determining multiple reference samples that locate outside of the current block, and determining the multiple reference samples as the first picture component reference sample set.
10. The encoder of claim 8, wherein performing first filtering processing on the multiple first picture component reference samples, to determine the multiple filtered first picture reference samples comprises: performing first filtering processing on the multiple first picture component reference samples to obtain a filtered reference sample set; by comparing reference samples in the filtered reference sample set, determining a set of greater first picture component reference samples and a set of smaller first picture component reference samples; and determining a filtered maximum first picture component reference sample and a filtered minimum first picture component reference sample based on the set of greater first picture component reference samples and the set of smaller first picture component reference samples; wherein a number of samples in the set of greater first picture component reference samples is 2, and a number of samples in the set of smaller first picture component reference samples is 2.
12. The method of claim of claim 11, wherein the first filtering processing is performed on the sample values of the samples corresponding to the multiple first picture component reference values to obtain a filtered reference value set, and wherein reference sample values in the filtered reference value set are compared, and wherein a set of greater first picture component reference values and a set of smaller first picture component reference values are determined based on the reference sample values, wherein the multiple filtered first picture reference sample values are determined by using multiple values from each of the set of greater first picture component reference values and the set of smaller first picture component reference values.
14. The method of claim 12, wherein a number of sample values in the set of greater first picture component reference values is an integer which is equal to or greater than 1, and a number of sample values in the set of smaller first picture component reference values is an integer which is equal to or greater than 1, wherein the number of sample values in the set of greater first picture component reference values is 2, and a number of sample values in the set of smaller first picture component reference values is 2.
11. The encoder of claim 10, the operations further comprising: determining a maximum to-be-predicted picture component reference sample corresponding to the filtered maximum first picture component reference sample and a minimum to-be-predicted picture component reference sample corresponding to the filtered minimum first picture component reference sample; and determining the parameter of the component model according to the filtered maximum first picture component reference sample, the maximum to-be-predicted picture component reference sample, the filtered minimum first picture component reference sample and the minimum to-be-predicted picture component reference sample.
15. The method of claim 13, further comprising: determining a maximum to-be-predicted picture component reference value corresponding to the filtered maximum first picture component reference value and a minimum to-be-predicted picture component reference value corresponding to the filtered minimum first picture component reference value.
16. The method of claim 15, wherein determining the parameter of the component linear model according to the multiple filtered first picture reference sample values and corresponding to-be-predicted picture component reference values comprises: determining the parameter of the component linear model according to the filtered maximum first picture component reference value, the maximum to-be-predicted picture component reference value, the filtered minimum first picture component reference value and the minimum to-be-predicted picture component reference value, the component linear model characterizing the linear mapping relationship for mapping the sample value of the first picture component to the sample value of the to-be-predicted picture component.
12. The encoder of claim 8, wherein performing mapping processing on the reconstructed sample of the first picture component of the current block according to the component model to obtain the mapped sample comprises: performing second filtering processing on the reconstructed samples of the first picture component to obtain a second filtered sample of the reconstructed samples of the first picture component; and performing mapping processing on the second filtered sample according to the component model to obtain the mapped sample; wherein second filtering processing is down-sampling filtering.
17. The method of claim 11, wherein performing mapping processing on the reconstructed value of the first picture component of the current block according to the component linear model to obtain the mapped value comprises: performing second filtering processing on the reconstructed value of the first picture component to obtain a second filtered value of the reconstructed value of the first picture component; and performing mapping processing on the second filtered value according to the component linear model to obtain the mapped value, wherein second filtering processing is down-sampling filtering or low-pass filtering.
13. The encoder of claim 11, wherein determining the maximum to-be-predicted picture component reference sample corresponding to the filtered maximum first picture component reference sample and the minimum to-be-predicted picture component reference sample corresponding to the filtered minimum first picture component reference sample comprises: determining a set of greater to-be-predicted picture component reference samples corresponding to the reference samples in the set of greater first picture component reference samples and a set of smaller to-be-predicted picture component reference samples corresponding to the reference samples in the set of smaller first picture component reference samples; determining the maximum to-be-predicted picture component reference sample based on a mean processing on reference samples in the set of greater to-be-predicted picture component reference samples, and determining the minimum to-be-predicted picture component reference sample based on a mean processing on reference samples in the set of smaller the to-be-predicted picture component reference samples.
13. The method of claim 12, wherein determining the multiple filtered first picture reference sample values based on the set of greater first picture component reference values and set of smaller first picture component reference values comprises: performing mean processing on the set of greater first picture component reference values to obtain a filtered maximum first picture component reference value; and performing mean processing on the set of smaller first picture component reference values to obtain a filtered minimum first picture component reference value.
14. The encoder of claim 8, wherein the first picture component is a luma component, and the to-be-predicted picture component is a first or second chroma component.
10. The method of claim 1, wherein the first picture component is a luma component, and the to-be-predicted picture component is a first or second chroma component; or the first picture component is the first chroma component, and the to-be-predicted picture component is the luma component or the second chroma component; or the first picture component is the second chroma component, and the to-be-predicted picture component is the luma component or the first chroma component; or the first picture component is a first colour component, and the to-be-predicted picture component is a second colour component or a third colour component; or the first picture component is the second colour component, and the to-be-predicted picture component is the first colour component or the third colour component; or the first picture component is the third colour component, and the to-be-predicted picture component is the second colour component or the first colour component, wherein the first colour component is a red component, the second colour component is a green component, and the third colour component is a blue component.
15. A non-transitory computer-readable storage medium, having a computer program and a bitstream stored thereon, wherein the computer program, when executed by a processor, enables the processor to perform an encoding method to generate the bitstream, and the encoding method comprises: determining a first picture component reference sample set of a current block; determining multiple first picture component reference samples according to the first picture component reference sample set; performing first filtering processing on the multiple first picture component reference samples, to determine multiple filtered first picture reference samples; determining a parameter of a component model according to the multiple filtered first picture reference samples and corresponding to-be-predicted picture component reference samples, a to-be-predicted picture component being a picture component which is different from a first picture component, and the component model characterizing a mapping relationship for mapping a sample of the first picture component to a sample of the to-be-predicted picture component; performing mapping processing on a reconstructed sample of the first picture component of the current block according to the component model to obtain a mapped sample; and determining a predicted sample of the to-be-predicted picture component of the current block according to the mapped sample, wherein determining multiple first picture component reference samples according to the first picture component reference sample set comprises: determining multiple reference samples based on samples in multiple neighboring lines at a top side of the current block according to two preset positions, and determining multiple reference samples based on samples in multiple neighboring columns at a left side of the current block according to two preset positions; and determining the multiple first picture component reference samples according to the selected reference samples.
21. A non-transitory computer-readable storage medium, having a computer program and a bitstream stored thereon, wherein the computer program, when executed by a processor, enables the processor to perform a picture component prediction method to generate the bitstream, and the method comprises: determining a first picture component reference value set of a current block; determining multiple first picture component reference values according to the first picture component reference value set, wherein the multiple first picture component reference values include four reference values corresponding to four preset sample positions, respectively; performing first filtering processing on sample values of samples corresponding to the multiple first picture component reference values, respectively, to determine multiple filtered first picture reference sample values; determining a parameter of a component linear model according to the multiple filtered first picture reference sample values and corresponding to-be-predicted picture component reference values, the to-be-predicted picture component being a picture component which is different from the first picture component, and the component linear model characterizing a linear mapping relationship for mapping a sample value of the first picture component to a sample value of the to-be-predicted picture component; performing mapping processing on a reconstructed value of the first picture component of the current block according to the component linear model to obtain a mapped value; and determining a predicted value of the to-be-predicted picture component of the current block according to the mapped value; wherein determining the multiple first picture component reference values according to the first picture component reference value set comprises: determining the multiple first picture component reference values from samples in one or more neighboring lines at a top side of the current block according to four preset positions, or determining the multiple first picture component reference values from samples in one or more neighboring columns at a left side of the current block according to four preset positions.
16. The non-transitory computer-readable storage medium of claim 15, wherein determining the first picture component reference sample set of the current block comprises: determining multiple reference samples that locate outside of the current block, and determining the multiple reference samples as the first picture component reference sample set.
17. The non-transitory computer-readable storage medium of claim 15, wherein performing first filtering processing on the multiple first picture component reference samples, to determine the multiple filtered first picture reference samples comprises: performing first filtering processing on the multiple first picture component reference samples to obtain a filtered reference sample set; by comparing reference samples in the filtered reference sample set, determining a set of greater first picture component reference samples and a set of smaller first picture component reference samples; and determining a filtered maximum first picture component reference sample and a filtered minimum first picture component reference sample based on the set of greater first picture component reference samples and the set of smaller first picture component reference samples; wherein a number of samples in the set of greater first picture component reference samples is 2, and a number of samples in the set of smaller first picture component reference samples is 2.
12. The method of claim of claim 11, wherein the first filtering processing is performed on the sample values of the samples corresponding to the multiple first picture component reference values to obtain a filtered reference value set, and wherein reference sample values in the filtered reference value set are compared, and wherein a set of greater first picture component reference values and a set of smaller first picture component reference values are determined based on the reference sample values, wherein the multiple filtered first picture reference sample values are determined by using multiple values from each of the set of greater first picture component reference values and the set of smaller first picture component reference values.
14. The method of claim 12, wherein a number of sample values in the set of greater first picture component reference values is an integer which is equal to or greater than 1, and a number of sample values in the set of smaller first picture component reference values is an integer which is equal to or greater than 1, wherein the number of sample values in the set of greater first picture component reference values is 2, and a number of sample values in the set of smaller first picture component reference values is 2.
18. The non-transitory computer-readable storage medium of claim 17, the method further comprising: determining a maximum to-be-predicted picture component reference sample corresponding to the filtered maximum first picture component reference sample and a minimum to-be-predicted picture component reference sample corresponding to the filtered minimum first picture component reference sample; and determining the parameter of the component model according to the filtered maximum first picture component reference sample, the maximum to-be-predicted picture component reference sample, the filtered minimum first picture component reference sample and the minimum to-be-predicted picture component reference sample.
15. The method of claim 13, further comprising: determining a maximum to-be-predicted picture component reference value corresponding to the filtered maximum first picture component reference value and a minimum to-be-predicted picture component reference value corresponding to the filtered minimum first picture component reference value.
16. The method of claim 15, wherein determining the parameter of the component linear model according to the multiple filtered first picture reference sample values and corresponding to-be-predicted picture component reference values comprises: determining the parameter of the component linear model according to the filtered maximum first picture component reference value, the maximum to-be-predicted picture component reference value, the filtered minimum first picture component reference value and the minimum to-be-predicted picture component reference value, the component linear model characterizing the linear mapping relationship for mapping the sample value of the first picture component to the sample value of the to-be-predicted picture component.
19. The non-transitory computer-readable storage medium of claim 15, wherein performing mapping processing on the reconstructed sample of the first picture component of the current block according to the component model to obtain the mapped sample comprises: performing second filtering processing on the reconstructed samples of the first picture component to obtain a second filtered sample of the reconstructed samples of the first picture component; and performing mapping processing on the second filtered sample according to the component model to obtain the mapped sample; wherein second filtering processing is down-sampling filtering.
17. The method of claim 11, wherein performing mapping processing on the reconstructed value of the first picture component of the current block according to the component linear model to obtain the mapped value comprises: performing second filtering processing on the reconstructed value of the first picture component to obtain a second filtered value of the reconstructed value of the first picture component; and performing mapping processing on the second filtered value according to the component linear model to obtain the mapped value, wherein second filtering processing is down-sampling filtering or low-pass filtering.
20. The non-transitory computer-readable storage medium of claim 18, wherein determining the maximum to-be-predicted picture component reference sample corresponding to the filtered maximum first picture component reference sample and the minimum to-be-predicted picture component reference sample corresponding to the filtered minimum first picture component reference sample comprises: determining a set of greater to-be-predicted picture component reference samples corresponding to the reference samples in the set of greater first picture component reference samples and a set of smaller to-be-predicted picture component reference samples corresponding to the reference samples in the set of smaller first picture component reference samples; determining the maximum to-be-predicted picture component reference sample based on a mean processing on reference samples in the set of greater to-be-predicted picture component reference samples, and determining the minimum to-be-predicted picture component reference sample based on a mean processing on reference samples in the set of smaller the to-be-predicted picture component reference samples.
13. The method of claim 12, wherein determining the multiple filtered first picture reference sample values based on the set of greater first picture component reference values and set of smaller first picture component reference values comprises: performing mean processing on the set of greater first picture component reference values to obtain a filtered maximum first picture component reference value; and performing mean processing on the set of smaller first picture component reference values to obtain a filtered minimum first picture component reference value.
Claim 1, 2, 4, 6, 8, 9, 11, 13 – 16, 18, and 20 are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1, 2, 4, 6, 7, 9 – 11, 13, 15, 16, and 18 - 20 of copending Application No. 19/354,315 (reference application). Although the claims at issue are not identical, they are not patentably distinct from each other because the scope of the copending application wholly encompasses the scope of the current application.
This is a provisional nonstatutory double patenting rejection because the patentably indistinct claims have not in fact been patented.
Current Application
Copending Application No. 19/354,315
1. A decoder for picture component prediction, comprising: a memory for storing executable video component prediction instructions; and a processor configured to perform the executable video component prediction instructions stored in the memory to perform following operations: determining a first picture component reference sample set of a current block; determining multiple first picture component reference samples according to the first picture component reference sample set; performing first filtering processing on the multiple first picture component reference samples, to determine multiple filtered first picture reference samples; determining a parameter of a component model according to the multiple filtered first picture reference samples and corresponding to-be-predicted picture component reference samples, a to-be-predicted picture component being a picture component which is different from a first picture component, and the component model characterizing a mapping relationship for mapping a sample of the first picture component to a sample of the to-be-predicted picture component; performing mapping processing on a reconstructed sample of the first picture component of the current block according to the component model to obtain a mapped sample; and determining a predicted sample of the to-be-predicted picture component of the current block according to the mapped sample, wherein determining multiple first picture component reference samples according to the first picture component reference sample set comprises: determining multiple reference samples based on samples in multiple neighboring lines at a top side of the current block according to two preset positions, and determining multiple reference samples based on samples in multiple neighboring columns at a left side of the current block according to two preset positions; and determining the multiple first picture component reference samples according to the selected reference samples.
1. A decoder for picture component prediction, comprising: a memory for storing executable video component prediction instructions; and a processor configured to perform the executable video component prediction instructions stored in the memory to perform following operations: determining a first picture component reference value set of a current block; determining multiple first picture component reference values according to the first picture component reference value set; performing first filtering processing on sample values of samples corresponding to the multiple first picture component reference values to obtain a filtered reference value set, wherein reference sample values in the filtered reference value set are compared, and a set of greater first picture component reference values and a set of smaller first picture component reference values are determined; determining multiple filtered first picture reference sample values based on the set of greater first picture component reference values and the set of smaller first picture component reference values; determining a parameter of a component model according to the multiple filtered first picture reference sample values and corresponding to-be-predicted picture component reference values, the to-be-predicted picture component being a picture component which is different from the first picture component, and the component model characterizing a mapping relationship for mapping a sample value of the first picture component to a sample value of the to-be-predicted picture component; performing mapping processing on a reconstructed value of the first picture component of the current block according to the component model to obtain a mapped value; and determining a predicted value of the to-be-predicted picture component of the current block according to the mapped value.
4. The decoder of claim 3, wherein determining the multiple first picture component reference values according to the first picture component reference value set comprises: selecting reference samples from the samples in the one or more neighboring lines at the top side of the current block according to two preset positions, and selecting reference samples from the samples in the one or more neighboring columns at the left side of the current block according to two preset positions; determining the multiple first picture component reference values according to the selected samples.
2. The decoder of claim 1, wherein determining the first picture component reference sample set of the current block comprises: determining multiple reference samples that locate outside of the current block, and determining the multiple reference samples as the first picture component reference sample set.
2. The decoder of claim 1, wherein determining the first picture component reference value set of the current block comprises: determining one or more reference samples that locate outside of the current block, and determining the one or more reference samples as the first picture component reference value set, wherein determining the one or more reference samples that locate outside of the current block comprises: determining neighboring samples of the current block as one or more reference samples.
4. The decoder of claim 3, the operations further comprising: determining a maximum to-be-predicted picture component reference sample corresponding to the filtered maximum first picture component reference sample and a minimum to-be-predicted picture component reference sample corresponding to the filtered minimum first picture component reference sample; and determining the parameter of the component model according to the filtered maximum first picture component reference sample, the maximum to-be-predicted picture component reference sample, the filtered minimum first picture component reference sample and the minimum to-be-predicted picture component reference sample.
6. The decoder of claim 5, the operations further comprising: determining a maximum to-be-predicted picture component reference value corresponding to the filtered maximum first picture component reference value and a minimum to-be-predicted picture component reference value corresponding to the filtered minimum first picture component reference value.
7. The decoder of claim 6, wherein determining the parameter of the component model according to the multiple filtered first picture reference sample values and the corresponding to-be-predicted picture component reference values comprises: determining the parameter of the component model according to the filtered maximum first picture component reference value, the maximum to-be-predicted picture component reference value, the filtered minimum first picture component reference value and the minimum to-be-predicted picture component reference value, the component model characterizing the mapping relationship for mapping the sample value of the first picture component to the sample value of the to-be-predicted picture component.
6. The decoder of claim 4, wherein determining the maximum to-be-predicted picture component reference sample corresponding to the filtered maximum first picture component reference sample and the minimum to-be-predicted picture component reference sample corresponding to the filtered minimum first picture component reference sample comprises: determining a set of greater to-be-predicted picture component reference samples corresponding to the reference samples in the set of greater first picture component reference samples and a set of smaller to-be-predicted picture component reference samples corresponding to the reference samples in the set of smaller first picture component reference samples; determining the maximum to-be-predicted picture component reference sample based on a mean processing on reference samples in the set of greater to-be-predicted picture component reference samples, and determining the minimum to-be-predicted picture component reference sample based on a mean processing on reference samples in the set of smaller the to-be-predicted picture component reference samples.
9. The decoder of claim 6, wherein determining the maximum to-be-predicted picture component reference value corresponding to the filtered maximum first picture component reference value and the minimum to-be-predicted picture component reference value corresponding to the filtered minimum first picture component reference value comprises: acquiring to-be-predicted picture component reference values of the reference samples in the set of greater first picture component reference values and to-be-predicted picture component reference values of the reference samples in the set of smaller first picture component reference values; performing meaning processing on the to-be-predicted picture component reference values of the reference samples in the set of greater first picture component reference values, and determining the maximum to-be-predicted picture component reference value; and performing meaning processing on the to-be-predicted picture component reference values of the reference samples in the set of smaller first picture component reference values, and determining minimum to-be-predicted picture component reference value.
8. An encoder for picture component prediction, comprising: determining a first picture component reference sample set of a current block; determining multiple first picture component reference samples according to the first picture component reference sample set; performing first filtering processing on the multiple first picture component reference samples, to determine multiple filtered first picture reference samples; determining a parameter of a component model according to the multiple filtered first picture reference samples and corresponding to-be-predicted picture component reference samples, a to-be-predicted picture component being a picture component which is different from a first picture component, and the component model characterizing a mapping relationship for mapping a sample of the first picture component to a sample of the to-be-predicted picture component; performing mapping processing on a reconstructed sample of the first picture component of the current block according to the component model to obtain a mapped sample; and determining a predicted sample of the to-be-predicted picture component of the current block according to the mapped sample, wherein determining multiple first picture component reference samples according to the first picture component reference sample set comprises: determining multiple reference samples based on samples in multiple neighboring lines at a top side of the current block according to two preset positions, and determining multiple reference samples based on samples in multiple neighboring columns at a left side of the current block according to two preset positions; and determining the multiple first picture component reference samples according to the selected reference samples.
10. An encoder for picture component prediction, comprising: a memory for storing executable video component prediction instructions; and a processor configured to perform the executable video component prediction instructions stored in the memory to perform following operations: determining a first picture component reference value set of a current block; determining multiple first picture component reference values according to the first picture component reference value set; performing first filtering processing on sample values of samples corresponding to the multiple first picture component reference values to obtain a filtered reference value set, wherein reference sample values in the filtered reference value set are compared, and a set of greater first picture component reference values and a set of smaller first picture component reference values are determined; determining multiple filtered first picture reference sample values based on the set of greater first picture component reference values and the set of smaller first picture component reference values; determining a parameter of a component model according to the multiple filtered first picture reference sample values and corresponding to-be-predicted picture component reference values, the to-be-predicted picture component being a picture component which is different from the first picture component, and the component model characterizing a mapping relationship for mapping a sample value of the first picture component to a sample value of the to-be-predicted picture component; performing mapping processing on a reconstructed value of the first picture component of the current block according to the component model to obtain a mapped value; and determining a predicted value of the to-be-predicted picture component of the current block according to the mapped value.
13. The encoder of claim 12, wherein determining the multiple first picture component reference values according to the first picture component reference value set comprises: selecting reference samples from the samples in the one or more neighboring lines at the top side of the current block according to two preset positions, and selecting reference samples from the samples in the one or more neighboring columns at the left side of the current block according to two preset positions; determining the multiple first picture component reference values according to the selected samples.
9. The encoder of claim 8, wherein determining the first picture component reference sample set of the current block comprises: determining multiple reference samples that locate outside of the current block, and determining the multiple reference samples as the first picture component reference sample set.
11. The encoder of claim 10, wherein determining the first picture component reference value set of the current block comprises: determining one or more reference samples that locate outside of the current block, and determining the one or more reference samples as the first picture component reference value set, wherein determining the one or more reference samples that locate outside of the current block comprises: determining neighboring samples of the current block as one or more reference samples.
11. The encoder of claim 10, the operations further comprising: determining a maximum to-be-predicted picture component reference sample corresponding to the filtered maximum first picture component reference sample and a minimum to-be-predicted picture component reference sample corresponding to the filtered minimum first picture component reference sample; and determining the parameter of the component model according to the filtered maximum first picture component reference sample, the maximum to-be-predicted picture component reference sample, the filtered minimum first picture component reference sample and the minimum to-be-predicted picture component reference sample.
15. The encoder of claim 14, the operations further comprising: determining a maximum to-be-predicted picture component reference value corresponding to the filtered maximum first picture component reference value and a minimum to-be-predicted picture component reference value corresponding to the filtered minimum first picture component reference value.
16. The encoder of claim 15, wherein determining the parameter of the component model according to the multiple filtered first picture reference sample values and the corresponding to-be-predicted picture component reference values comprises: determining the parameter of the component model according to the filtered maximum first picture component reference value, the maximum to-be-predicted picture component reference value, the filtered minimum first picture component reference value and the minimum to-be-predicted picture component reference value, the component model characterizing the mapping relationship for mapping the sample value of the first picture component to the sample value of the to-be-predicted picture component.
13. The encoder of claim 11, wherein determining the maximum to-be-predicted picture component reference sample corresponding to the filtered maximum first picture component reference sample and the minimum to-be-predicted picture component reference sample corresponding to the filtered minimum first picture component reference sample comprises: determining a set of greater to-be-predicted picture component reference samples corresponding to the reference samples in the set of greater first picture component reference samples and a set of smaller to-be-predicted picture component reference samples corresponding to the reference samples in the set of smaller first picture component reference samples; determining the maximum to-be-predicted picture component reference sample based on a mean processing on reference samples in the set of greater to-be-predicted picture component reference samples, and determining the minimum to-be-predicted picture component reference sample based on a mean processing on reference samples in the set of smaller the to-be-predicted picture component reference samples.
18. The encoder of claim 15, wherein determining the maximum to-be-predicted picture component reference value corresponding to the filtered maximum first picture component reference value and the minimum to-be-predicted picture component reference value corresponding to the filtered minimum first picture component reference value comprises: acquiring to-be-predicted picture component reference values of the reference samples in the set of greater first picture component reference values and to-be-predicted picture component reference values of the reference samples in the set of smaller first picture component reference values; performing meaning processing on the to-be-predicted picture component reference values of the reference samples in the set of greater first picture component reference values, and determining the maximum to-be-predicted picture component reference value; and performing meaning processing on the to-be-predicted picture component reference values of the reference samples in the set of smaller first picture component reference values, and determining minimum to-be-predicted picture component reference value.
15. A non-transitory computer-readable storage medium, having a computer program and a bitstream stored thereon, wherein the computer program, when executed by a processor, enables the processor to perform an encoding method to generate the bitstream, and the encoding method comprises: determining a first picture component reference sample set of a current block; determining multiple first picture component reference samples according to the first picture component reference sample set; performing first filtering processing on the multiple first picture component reference samples, to determine multiple filtered first picture reference samples; determining a parameter of a component model according to the multiple filtered first picture reference samples and corresponding to-be-predicted picture component reference samples, a to-be-predicted picture component being a picture component which is different from a first picture component, and the component model characterizing a mapping relationship for mapping a sample of the first picture component to a sample of the to-be-predicted picture component; performing mapping processing on a reconstructed sample of the first picture component of the current block according to the component model to obtain a mapped sample; and determining a predicted sample of the to-be-predicted picture component of the current block according to the mapped sample, wherein determining multiple first picture component reference samples according to the first picture component reference sample set comprises: determining multiple reference samples based on samples in multiple neighboring lines at a top side of the current block according to two preset positions, and determining multiple reference samples based on samples in multiple neighboring columns at a left side of the current block according to two preset positions; and determining the multiple first picture component reference samples according to the selected reference samples.
19. A non-transitory computer-readable storage medium, having a computer program and a bitstream stored thereon, wherein the computer program, when executed by a processor, enables the processor to perform an encoding method to generate the bitstream, and the encoding method comprises: determining a first picture component reference value set of a current block; determining multiple first picture component reference values according to the first picture component reference value set; performing first filtering processing on sample values of samples corresponding to the multiple first picture component reference values to obtain a filtered reference value set, wherein reference sample values in the filtered reference value set are compared, and a set of greater first picture component reference values and a set of smaller first picture component reference values are determined; determining multiple filtered first picture reference sample values based on the set of greater first picture component reference values and the set of smaller first picture component reference values; determining a parameter of a component model according to the multiple filtered first picture reference sample values and corresponding to-be-predicted picture component reference values, the to-be-predicted picture component being a picture component which is different from the first picture component, and the component model characterizing a mapping relationship for mapping a sample value of the first picture component to a sample value of the to-be-predicted picture component; performing mapping processing on a reconstructed value of the first picture component of the current block according to the component model to obtain a mapped value; and determining a predicted value of the to-be-predicted picture component of the current block according to the mapped value.
13. The encoder of claim 12, wherein determining the multiple first picture component reference values according to the first picture component reference value set comprises: selecting reference samples from the samples in the one or more neighboring lines at the top side of the current block according to two preset positions, and selecting reference samples from the samples in the one or more neighboring columns at the left side of the current block according to two preset positions; determining the multiple first picture component reference values according to the selected samples.
16. The non-transitory computer-readable storage medium of claim 15, wherein determining the first picture component reference sample set of the current block comprises: determining multiple reference samples that locate outside of the current block, and determining the multiple reference samples as the first picture component reference sample set.
20. The non-transitory computer-readable storage medium of claim 19, wherein determining the first picture component reference value set of the current block comprises: determining one or more reference samples that locate outside of the current block, and determining the one or more reference samples as the first picture component reference value set, wherein determining the one or more reference samples that locate outside of the current block comprises: determining neighboring samples of the current block as one or more reference samples.
18. The non-transitory computer-readable storage medium of claim 17, the method further comprising: determining a maximum to-be-predicted picture component reference sample corresponding to the filtered maximum first picture component reference sample and a minimum to-be-predicted picture component reference sample corresponding to the filtered minimum first picture component reference sample; and determining the parameter of the component model according to the filtered maximum first picture component reference sample, the maximum to-be-predicted picture component reference sample, the filtered minimum first picture component reference sample and the minimum to-be-predicted picture component reference sample.
15. The encoder of claim 14, the operations further comprising: determining a maximum to-be-predicted picture component reference value corresponding to the filtered maximum first picture component reference value and a minimum to-be-predicted picture component reference value corresponding to the filtered minimum first picture component reference value.
16. The encoder of claim 15, wherein determining the parameter of the component model according to the multiple filtered first picture reference sample values and the corresponding to-be-predicted picture component reference values comprises: determining the parameter of the component model according to the filtered maximum first picture component reference value, the maximum to-be-predicted picture component reference value, the filtered minimum first picture component reference value and the minimum to-be-predicted picture component reference value, the component model characterizing the mapping relationship for mapping the sample value of the first picture component to the sample value of the to-be-predicted picture component.
20. The non-transitory computer-readable storage medium of claim 18, wherein determining the maximum to-be-predicted picture component reference sample corresponding to the filtered maximum first picture component reference sample and the minimum to-be-predicted picture component reference sample corresponding to the filtered minimum first picture component reference sample comprises: determining a set of greater to-be-predicted picture component reference samples corresponding to the reference samples in the set of greater first picture component reference samples and a set of smaller to-be-predicted picture component reference samples corresponding to the reference samples in the set of smaller first picture component reference samples; determining the maximum to-be-predicted picture component reference sample based on a mean processing on reference samples in the set of greater to-be-predicted picture component reference samples, and determining the minimum to-be-predicted picture component reference sample based on a mean processing on reference samples in the set of smaller the to-be-predicted picture component reference samples.
18. The encoder of claim 15, wherein determining the maximum to-be-predicted picture component reference value corresponding to the filtered maximum first picture component reference value and the minimum to-be-predicted picture component reference value corresponding to the filtered minimum first picture component reference value comprises: acquiring to-be-predicted picture component reference values of the reference samples in the set of greater first picture component reference values and to-be-predicted picture component reference values of the reference samples in the set of smaller first picture component reference values; performing meaning processing on the to-be-predicted picture component reference values of the reference samples in the set of greater first picture component reference values, and determining the maximum to-be-predicted picture component reference value; and performing meaning processing on the to-be-predicted picture component reference values of the reference samples in the set of smaller first picture component reference values, and determining minimum to-be-predicted picture component reference value.
Conclusion
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SHANIKA M. BRUMFIELD
Examiner
Art Unit 2487
/SHANIKA M BRUMFIELD/Examiner, Art Unit 2487
/Dave Czekaj/Supervisory Patent Examiner, Art Unit 2487
