DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 04/14/2026 has been entered.
Response to Amendment
The Examiner acknowledges amendments to the claims dated 02/17/2026 and enters for consideration. Claims 4 and 13 have been cancelled. Claims 21-22 have been newly added. The amendments are in response to the Final Office Action mailed on 12/16/2025. Therefore, claims 1-3, 5-12, 14-22 remain pending in the current application.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-3, 5-7, 10-12, 14-16, 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Zhang et al. (US PGPub 2018/0077426 A1) in view of Du et al. (US PGPub 2022/0182680 A1).
Regarding claim 1 (Currently Amended), Zhang et al. teach a method for decoding video data (Abstract), comprising:
obtaining, from a bitstream, a video block (Fig. 3; [0101]; It teaches that video decoder 30 receives an encoded video bitstream that represents video blocks) and filter shape information ([0126]; it teaches that filter tap information is signaled in SPS, PPS, etc.), wherein the filter shape information comprises an index to one of a plurality of filter shape candidates having different filter shapes and/or different numbers of filter taps;
determining a region to derive a multiple linear regression (MLR) model ([0121]-[0122], [0125], [0128]; Figs. 4-5; Fig. 4 shows locations of samples used for deriving model parameters α and β, which means the region for deriving the models is determined. It also teaches that a linear relationship between luma and chroma components may be solved using a linear regression method. When an MMLM method is utilized, video encoder 20 and video decoder 30 may be configured to use more than one linear model (e.g., multiple linear models), for a single block/coding unit (CU)/transform unit (TU), to predict chroma components of the block from luma components of the block. Video encoder 20 and video decoder 30 may be configured to derive the multiple linear models [i.e. derive multiple linear regression model] using neighboring luma samples and neighboring chroma samples);
obtaining luma and chroma sample values in the region ([0158]-[0159]; Fig. 9; It teaches that coded neighboring chroma samples and corresponding coded luma samples are obtained which are in the region);
deriving the MLR model using the luma and chroma sample values in the region ([0121]-[0122], [0128], [0160]; Figs. 4-5, 10, 13; It teaches that a linear relationship between luma and chroma components may be solved using a linear regression method, when an MMLM method is utilized, video encoder 20 and video decoder 30 may be configured to use more than one linear model (e.g., multiple linear models), for a single block/coding unit (CU)/transform unit (TU), to predict chroma components of the block from luma components of the block. Video encoder 20 and video decoder 30 may be configured to derive the multiple linear models [i.e. derive multiple linear regression model] using neighboring luma samples and neighboring chroma samples. Video decoder 30 may be configured to derive two independent linear models. The parameters for the linear models may be derived in the same manner as derived above [i.e., using the luma and chroma samples in the region]. Fig. 13 shows an MLR model with at least two models) based on the filter shape information (Figs. 14A-C show different sub-sampling filters that are being used to derive the linear model as described in [0173]);
predicting each of chroma samples in the video block by applying the MLR model to corresponding luma samples for that chroma sample based on the filter shape information ([0121]-[0122], [0128], [0165], [0258]; Figs. 5, 13, 19; It teaches that a linear relationship between luma and chroma components may be solved using a linear regression method, when an MMLM method is utilized, video encoder 20 and video decoder 30 may be configured to use more than one linear model (e.g., multiple linear models), for a single block/coding unit (CU)transform unit (TU), to predict chroma components of the block’ from luma components of the block. Video encoder 20 and video decoder 30 may be configured to derive the multiple linear models [i.e. multiple linear regression model] using neighboring luma samples and neighboring chroma samples. It also teaches predicting chroma samples for the first block of video data using the reconstructed luma samples for the first block of video data and two or more linear prediction models as shown in Fig. 19 and disclosed in [0258]); and
obtaining decoded video block using the predicted chroma samples ([0258]; Fig. 19; it teaches to predict chroma samples for the first block of video data, i.e., the decoded video block is determined).
Although, Zhang et al. teach that video encoder may scan the transform coefficients, producing a one-dimensional vector from the two-dimensional matrix including the quantized transform coefficients (Zhang et al.; [0072]), but it fails to teach obtaining filter shape information wherein the filter shape information comprises an index to one of a plurality of filter shape candidates having different filter shapes.
However, Du et al., in the same field of endeavor (Abstract), teach obtaining filter shape information (Du et al.; [0027], L1-2; It teaches decoding an index from the coded video bitstream that carries the video, wherein the index is indicative of the filter shape configuration) wherein the filter shape information comprises an index to one of a plurality of filter shape candidates having different filter shapes (Du et al.; [0260]-[0261]; it teaches an index indicative of the selected filter shape configuration from multiple candidate filter shape configurations is signaled for each picture in the coded video bitstream).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to combine Zhang et al’s invention of linear model chroma intra prediction for video coding to include Du et al's usage of filter shape information in an index, because the coding efficiency may be further improved by redesigning the filter coefficients (Du et al.; [0166]).
Regarding claim 2 (Original), Zhang et al. and Du et al. teach the method of claim 1, wherein the filter shape information is signaled in Sequence Parameter Set (SPS), Adaptation Parameter Set (APS), Picture Parameter Set (PPS), Picture Header (PH), Slice Header (SH), Region, Coding Tree Unit (CTU), Coding Unit (CU), Subblock, or Sample level (Zhang et al.; [0126]; it teaches that filter tap information is signaled in SPS, PPS, etc.).
Regarding claim 3 (Original), Zhang et al. and Du et al. teach the method of claim 1, wherein the filter shape information is indicative of at least one of a shape of a filter, or a number of filter taps (Zhang et al.; [0126]; it teaches that filter tap information is signaled in SPS, PPS, etc.).
Regarding claim 5 (Original), Zhang et al. and Du et al. teach the method of claim 1, wherein the same or different filter shape information is used for different chroma components and/or different color formats (Zhang et al.; [0126]; it teaches that when LM chroma prediction mode is enabled, one or more sets of the down-sampling filter may be further signaled, which means same (one set of filter) or different (more than one set of filters) filter shapes are used for chroma prediction).
Regarding claim 6 (Original), Zhang et al. and Du et al. teach the method of claim 2, wherein the filter shape information is signaled in the same or different levels for different chroma components (Zhang et al.; [0126]; it teaches that when LM chroma prediction mode is enabled, one or more sets of the down-sampling filter may be further signaled in either a sequence parameter set (SPS), a picture parameter set (PPS), or a slice header, which means the filter information is signaled in the same level (SPS or PPS or SH)).
Regarding claim 7 (Currently Amended), Zhang et al. and Du et al. teach the method of claim 1, wherein the filter shape information is signaled via respective indices, or a single index for different chroma components (Zhang et al.; [0126]; It teaches that video encoder 20 may signal an index of the filter that is used in LM prediction mode).
Regarding claim 10 (Currently Amended), Zhang et al. teach an apparatus for video decoding (Fig. 1; [0057]), comprising:
one or more processors ([0302]); and
one or more storage devices storing instructions that ([0057]), when executed by the one or more processors, cause the apparatus to:
obtain, from a bitstream, a video block (Fig. 3; [0101]; It teaches that video decoder 30 receives an encoded video bitstream that represents video blocks) and filter shape information ([0126]; it teaches that filter tap information is signaled in SPS, PPS, etc.), wherein the filter shape information comprises an index to one of a plurality of filter shape candidates having different filter shapes and/or different numbers of filter taps;
determine a region to derive a multiple linear regression (MLR) model ([0121]-[0122], [0125], [0128]; Figs. 4-5; Fig. 4 shows locations of samples used for deriving model parameters α and β, which means the region for deriving the models is determined. It also teaches that a linear relationship between luma and chroma components may be solved using a linear regression method. When an MMLM method is utilized, video encoder 20 and video decoder 30 may be configured to use more than one linear model (e.g., multiple linear models), for a single block/coding unit (CU)/transform unit (TU), to predict chroma components of the block from luma components of the block. Video encoder 20 and video decoder 30 may be configured to derive the multiple linear models [i.e. derive multiple linear regression model] using neighboring luma samples and neighboring chroma samples);
obtain luma and chroma sample values in the region ([0158]-[0159]; Fig. 9; It teaches that coded neighboring chroma samples and corresponding coded luma samples are obtained which are in the region);
derive the MLR model using the luma and chroma sample values in the region ([0121]-[0122], [0128], [0160]; Figs. 4-5, 10, 13; It teaches that a linear relationship between luma and chroma components may be solved using a linear regression method, when an MMLM method is utilized, video encoder 20 and video decoder 30 may be configured to use more than one linear model (e.g., multiple linear models), for a single block/coding unit (CU)/transform unit (TU), to predict chroma components of the block from luma components of the block. Video encoder 20 and video decoder 30 may be configured to derive the multiple linear models [i.e. derive multiple linear regression model] using neighboring luma samples and neighboring chroma samples. Video decoder 30 may be configured to derive two independent linear models. The parameters for the linear models may be derived in the same manner as derived above [i.e., using the luma and chroma samples in the region]. Fig. 13 shows an MLR model with at least two models) based on the filter shape information (Figs. 14A-C show different sub-sampling filters that are being used to derive the linear model as described in [0173]);
predict each of chroma samples in the video block by applying the MLR model to corresponding luma samples for that chroma sample based on the filter shape information ([0121]-[0122], [0128], [0165], [0258]; Figs. 5, 13, 19; It teaches that a linear relationship between luma and chroma components may be solved using a linear regression method, when an MMLM method is utilized, video encoder 20 and video decoder 30 may be configured to use more than one linear model (e.g., multiple linear models), for a single block/coding unit (CU)transform unit (TU), to predict chroma components of the block’ from luma components of the block. Video encoder 20 and video decoder 30 may be configured to derive the multiple linear models [i.e. multiple linear regression model] using neighboring luma samples and neighboring chroma samples. It also teaches predicting chroma samples for the first block of video data using the reconstructed luma samples for the first block of video data and two or more linear prediction models as shown in Fig. 19 and disclosed in [0258]); and
obtain decoded video block using the predicted chroma samples ([0258]; Fig. 19; it teaches to predict chroma samples for the first block of video data, i.e., the decoded video block is determined).
Although, Zhang et al. teach that video encoder may scan the transform coefficients, producing a one-dimensional vector from the two-dimensional matrix including the quantized transform coefficients (Zhang et al.; [0072]), but it fails to teach obtaining filter shape information wherein the filter shape information comprises an index to one of a plurality of filter shape candidates having different filter shapes.
However, Du et al., in the same field of endeavor (Abstract), teach obtaining filter shape information (Du et al.; [0027], L1-2; It teaches decoding an index from the coded video bitstream that carries the video, wherein the index is indicative of the filter shape configuration) wherein the filter shape information comprises an index to one of a plurality of filter shape candidates having different filter shapes (Du et al.; [0260]-[0261]; it teaches an index indicative of the selected filter shape configuration from multiple candidate filter shape configurations is signaled for each picture in the coded video bitstream).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to combine Zhang et al’s invention of linear model chroma intra prediction for video coding to include Du et al's usage of filter shape information in an index, because the coding efficiency may be further improved by redesigning the filter coefficients (Du et al.; [0166]).
Regarding claim 11 (Original), Zhang et al. and Du et al. teach the apparatus of claim 10, wherein the filter shape information is signaled in Sequence Parameter Set (SPS), Adaptation Parameter Set (APS), Picture Parameter Set (PPS), Picture Header (PH), Slice Header (SH), Region, Coding Tree Unit (CTU), Coding Unit (CU), Subblock, or Sample level (Zhang et al.; [0126]; it teaches that filter tap information is signaled in SPS, PPS, etc.).
Regarding claim 12 (Original), Zhang et al. and Du et al. teach the apparatus of claim 10, wherein the filter shape information is indicative of at least one of a shape of a filter, or a number of filter taps (Zhang et al.; [0126]; it teaches that filter tap information is signaled in SPS, PPS, etc.).
Regarding claim 14 (Original), Zhang et al. and Du et al. teach the apparatus of claim 10, wherein the same or different filter shape information is used for different chroma components and/or different color formats (Zhang et al.; [0126]; it teaches that when LM chroma prediction mode is enabled, one or more sets of the down-sampling filter may be further signaled, which means same (one set of filter) or different (more than one set of filters) filter shapes are used for chroma prediction).
Regarding claim 15 (Original), Zhang et al. and Du et al. teach the apparatus of claim 11, wherein the filter shape information is signaled in the same or different levels for different chroma components (Zhang et al.; [0126]; it teaches that when LM chroma prediction mode is enabled, one or more sets of the down-sampling filter may be further signaled in either a sequence parameter set (SPS), a picture parameter set (PPS), or a slice header, which means the filter information is signaled in the same level (SPS or PPS or SH)).
Regarding claim 16 (Currently Amended), Zhang et al. and Du et al. teach the apparatus of claim 10, wherein the filter shape information is signaled via respective indices, or a single index for different chroma components (Zhang et al.; [0126]; It teaches that video encoder 20 may signal an index of the filter that is used in LM prediction mode).
Regarding claim 19 (Currently Amended), Zhang et al. teach a method for storing a bitstream ([0095], L1-3), comprising:
performing a method for video encoding to generate a bitstream (Fig. 2) including:
obtaining a video block from a video frame (Fig. 2; [0077]; It teaches that video encoder 20 receives a current video block within a video frame to be encoded) and filter shape information ([0126]; it teaches that filter tap information is signaled in SPS, PPS, etc.),
determining a region to derive a multiple linear regression (MLR) model ([0121]-[0122], [0125], [0128]; Figs. 4-5; Fig. 4 shows locations of samples used for deriving model parameters α and β, which means the region for deriving the models is determined. It also teaches that a linear relationship between luma and chroma components may be solved using a linear regression method. When an MMLM method is utilized, video encoder 20 and video decoder 30 may be configured to use more than one linear model (e.g., multiple linear models), for a single block/coding unit (CU)/transform unit (TU), to predict chroma components of the block from luma components of the block. Video encoder 20 and video decoder 30 may be configured to derive the multiple linear models [i.e. derive multiple linear regression model] using neighboring luma samples and neighboring chroma samples),
obtaining luma and chroma sample values in the region ([0158]-[0159]; Fig. 9; It teaches that coded neighboring chroma samples and corresponding coded luma samples are obtained which are in the region),
deriving the MLR model using the luma and chroma sample values in the region ([0121]-[0122], [0128], [0160]; Figs. 4-5, 10, 13; It teaches that a linear relationship between luma and chroma components may be solved using a linear regression method, when an MMLM method is utilized, video encoder 20 and video decoder 30 may be configured to use more than one linear model (e.g., multiple linear models), for a single block/coding unit (CU)/transform unit (TU), to predict chroma components of the block from luma components of the block. Video encoder 20 and video decoder 30 may be configured to derive the multiple linear models [i.e. derive multiple linear regression model] using neighboring luma samples and neighboring chroma samples. Video decoder 30 may be configured to derive two independent linear models. The parameters for the linear models may be derived in the same manner as derived above [i.e., using the luma and chroma samples in the region]. Fig. 13 shows an MLR model with at least two models) based on filter shape information (Figs. 14A-C show different sub-sampling filters that are being used to derive the linear model as described in [0173]), wherein the filter shape information comprises an index to one of a plurality of filter shape candidates having different filter shapes and/or different numbers of filter taps;
predicting each of chroma samples in the video block by applying the MLR model to corresponding luma samples for that chroma sample based on the filter shape information ([0121]-[0122], [0128], [0165], [0258]; Figs. 5, 13, 19; It teaches that a linear relationship between luma and chroma components may be solved using a linear regression method, when an MMLM method is utilized, video encoder 20 and video decoder 30 may be configured to use more than one linear model (e.g., multiple linear models), for a single block/coding unit (CU)transform unit (TU), to predict chroma components of the block’ from luma components of the block. Video encoder 20 and video decoder 30 may be configured to derive the multiple linear models [i.e. multiple linear regression model] using neighboring luma samples and neighboring chroma samples. It also teaches predicting chroma samples for the first block of video data using the reconstructed luma samples for the first block of video data and two or more linear prediction models as shown in Fig. 19 and disclosed in [0258]), and
obtaining a bitstream having encoded video block using the predicted chroma samples ([0258]; Fig. 19; it teaches to predict chroma samples for the first block of video data, i.e., the decoded video block is determined. Fig. 3 shows the that the encoded video bitstream is received by the video decoder 30) and the filter shape information (Figs. 14A-C show different sub-sampling filters that are being used to derive the linear model as described in [0173]); and
storing the bitstream into a non-transitory computer-readable medium ([0095], L1-3).
Although, Zhang et al. teach that video encoder may scan the transform coefficients, producing a one-dimensional vector from the two-dimensional matrix including the quantized transform coefficients (Zhang et al.; [0072]), but it fails to teach obtaining filter shape information wherein the filter shape information comprises an index to one of a plurality of filter shape candidates having different filter shapes.
However, Du et al., in the same field of endeavor (Abstract), teach obtaining filter shape information (Du et al.; [0027], L1-2; It teaches decoding an index from the coded video bitstream that carries the video, wherein the index is indicative of the filter shape configuration) wherein the filter shape information comprises an index to one of a plurality of filter shape candidates having different filter shapes (Du et al.; [0260]-[0261]; it teaches an index indicative of the selected filter shape configuration from multiple candidate filter shape configurations is signaled for each picture in the coded video bitstream).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to combine Zhang et al’s invention of linear model chroma intra prediction for video coding to include Du et al's usage of filter shape information in an index, because the coding efficiency may be further improved by redesigning the filter coefficients (Du et al.; [0166]).
Regarding claim 20 (Previously Presented), Zhang et al. and Du et al. teach the method of claim 19, wherein the filter shape information is signaled in Sequence Parameter Set (SPS), Adaptation Parameter Set (APS), Picture Parameter Set (PPS), Picture Header (PH), Slice Header (SH), Region, Coding Tree Unit (CTU), Coding Unit (CU), Subblock, or Sample level (Zhang et al.; [0126]; it teaches that filter tap information is signaled in SPS, PPS, etc.).
Claims 8-9, 17-18 are rejected under 35 U.S.C. 103 as being unpatentable over Zhang et al. (US PGPub 2018/0077426 A1) in view of Du et al. (US PGPub 2022/0182680 A1) and further in view of Hu et al. (US PGPub 2021/0152841 A1).
Regarding claim 8 (Original), Zhang et al. and Du et al. teach the method of claim 1.
But Zhang et al. or Du et al. do not explicitly teach padding for unavailable luma and chroma samples.
However, Hu et al., in the same field of endeavor (Abstract), teach a decoding system/method where padding is used for unavailable luma and chroma samples (Hu et al.; [0012]; [0154]; Fig. 12 shows that the unavailable luma and chroma samples become available after padding).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to combine Zhang et al’s invention of linear model chroma intra prediction for video coding and Du et al’s invention of non-linear mapping based filter with filter shape configuration to include Hu et al's usage of padding, because the example techniques may result in better quality filtering and/or better performance of video encoder and video decoder (Hu et al.; [0074]).
Regarding claim 9 (Original), Zhang et al. and Du et al. teach the method of claim 8.
But Zhang et al. or Du et al. do not explicitly teach padding is performed by padding repetitions of values of available luma and chroma samples for the unavailable luma and chroma samples.
However, Hu et al., in the same field of endeavor (Abstract), teach a decoding system/method where padding is performed by padding repetitions of values of available luma and chroma samples for the unavailable luma and chroma samples (Hu et al.; [0012]; [0154]; Fig. 12 shows that the unavailable luma and chroma samples become available after repetitive padding).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to combine Zhang et al’s invention of linear model chroma intra prediction for video coding and Du et al’s invention of non-linear mapping based filter with filter shape configuration to include Hu et al's usage of repetitive padding, because the example techniques may result in better quality filtering and/or better performance of video encoder and video decoder (Hu et al.; [0074]).
Regarding claim 17 (Original), Zhang et al. and Du et al. teach the apparatus of claim 10.
But Zhang et al. or Du et al. do not explicitly teach padding for unavailable luma and chroma samples.
However, Hu et al., in the same field of endeavor (Abstract), teach a decoding system/method where padding is used for unavailable luma and chroma samples (Hu et al.; [0012]; [0154]; Fig. 12 shows that the unavailable luma and chroma samples become available after padding).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to combine Zhang et al’s invention of linear model chroma intra prediction for video coding and Du et al’s invention of non-linear mapping based filter with filter shape configuration to include Hu et al's usage of padding, because the example techniques may result in better quality filtering and/or better performance of video encoder and video decoder (Hu et al.; [0074]).
Regarding claim 18 (Original), Zhang et al. and Du et al. teach the apparatus of claim 17.
But Zhang et al. or Du et al. do not explicitly teach padding is performed by padding repetitions of values of available luma and chroma samples for the unavailable luma and chroma samples.
However, Hu et al., in the same field of endeavor (Abstract), teach a decoding system/method where padding is performed by padding repetitions of values of available luma and chroma samples for the unavailable luma and chroma samples (Hu et al.; [0012]; [0154]; Fig. 12 shows that the unavailable luma and chroma samples become available after repetitive padding).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to combine Zhang et al’s invention of linear model chroma intra prediction for video coding and Du et al’s invention of non-linear mapping based filter with filter shape configuration to include Hu et al's usage of repetitive padding, because the example techniques may result in better quality filtering and/or better performance of video encoder and video decoder (Hu et al.; [0074]).
Claims 21-22 are rejected under 35 U.S.C. 103 as being unpatentable over Zhang et al. (US PGPub 2018/0077426 A1) in view of Du et al. (US PGPub 2022/0182680 A1) and further in view of Zhang et al. (“MULTIPLE LINEAR REGRESSION FOR HIGH EFFICIENCY VIDEO INTRA CODING”), hereinafter Zhang2.
Regarding claim 21 (New), Zhang et al. and Du et al. teach the method of claim 1.
Although, Zhang et al. teach that video encoder may scan the transform coefficients, producing a one-dimensional vector from the two-dimensional matrix including the quantized transform coefficients (Zhang et al.; [0072]), but Zhang et al. or Du et al. fail to teach that the parameters of the regression model is derived based on a pseudo inverse matrix calculation.
However, Zhang2, in the same field of endeavor (Abstract), teach MLR for video coding where it uses a pseudo inverse matrix calculation for deriving the parameters of regression model (Zhang2; Page 1833, Section 2.2, Eqns. 1-4; Eqn. 4 shows the regression model parameter β^ derivation which is shows as β^ = (XTX)-1XTy, where β^ contains all the regression model coefficients and (XTX)-1XT represents the pseudo inverse matrix).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to combine Zhang et al’s invention of linear model chroma intra prediction for video coding and Du et al’s invention of non-linear mapping based filter with filter shape configuration to include Zhang2's usage of pseudo inverse matrix calculation, because multiple linear regression tries to predict the current block on top
of best intra prediction by combining interpolating and linear regression (Zhang2; Page 1834; Section 3.1).
Regarding claim 22 (New), Zhang et al. and Du et al. teach the apparatus of claim 10.
Although, Zhang et al. teach that video encoder may scan the transform coefficients, producing a one-dimensional vector from the two-dimensional matrix including the quantized transform coefficients (Zhang et al.; [0072]), but Zhang et al. or Du et al. fail to teach that the parameters of the regression model is derived based on a pseudo inverse matrix calculation.
However, Zhang2, in the same field of endeavor (Abstract), teach MLR for video coding where it uses a pseudo inverse matrix calculation for deriving the parameters of regression model (Zhang2; Page 1833, Section 2.2, Eqns. 1-4; Eqn. 4 shows the regression model parameter β^ derivation which is shows as β^ = (XTX)-1XTy, where β^ contains all the regression model coefficients and (XTX)-1XT represents the pseudo inverse matrix).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to combine Zhang et al’s invention of linear model chroma intra prediction for video coding and Du et al’s invention of non-linear mapping based filter with filter shape configuration to include Zhang2's usage of pseudo inverse matrix calculation, because multiple linear regression tries to predict the current block on top
of best intra prediction by combining interpolating and linear regression (Zhang2; Page 1834; Section 3.1).
Response to Arguments
Applicant’s arguments with respect to claim(s) have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
"Effective Chroma Subsampling and Luma Modification for RGB Full-Color Images Using the Multiple Linear Regression Technique" - Chung et al., Received April 22, 2020, accepted May 25, 2020, date of publication June 4, 2020, date of current version July 7, 2020.
“MOST PROBABLE MODE LIST CONSTRUCTION FOR MATRIX-BASED INTRA PREDICTION” – Deng et al., US PGPub 2021/0321090 A1.
“DOWNSAMPLING PROCESS FOR LINEAR MODEL PREDICTION MODE” – Zhang et al., US PGPub 2016/0277762 A1.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MAINUL HASAN whose telephone number is (571)272-0422. The examiner can normally be reached on MON-FRI: 10AM-6PM, Alternate FRIDAYS, EST.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, JAY PATEL can be reached on (571)272-2988. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/Mainul Hasan/
Primary Examiner, Art Unit 2485
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