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 .
Claims 7, 18, 22, 26 and 30-31 have been amended. Claims 8-10, 12, 19-20, 23-14, and 27-29 have been cancelled. Claims 1-7, 11, 13-18, 21-22, 25-26, and 30-31 are pending for examination.
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 03/27/2025; 11/25/2025; 01/13/2026; 05/11/2026 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-5, 7, 11, 13-14, 16, 25 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Misra (On Cross Component Adaptive Loop Filter for Video Compression - 2019).
Regarding claim 1, Misra teaches a video coding and decoding loop filtering method, comprising:
filtering a reconstructed picture of a current picture by using a first filter, so as to obtain a first reconstructed video unit (figure 2: SAO Luma);
filtering the reconstructed picture by using a second filter, so as to obtain a second reconstructed video unit (figure 2: SAO Cb/Cr);
determining a filter coefficient according to neighborhood information contained in a convolution template of the first reconstructed video unit (CC-ALF cCb/Cr is a filter using a diamond shape convolution template) and the second reconstructed video unit (ALF Chroma is a filter using a diamond shape convolution template), wherein the neighborhood information is information of neighboring pixel points around a pixel point in the convolution template (- the diamond shape convolution template comprises the center point and neighbouring sample positions. section Ill.A. Filter shape and precision: ''.As for the regular ALF case, the shape of the CC-ALF filter is a diamond instead of a square ....); and
filtering, based on the convolution template and the filter coefficient, the first reconstructed video unit and the second reconstructed video unit to obtain a third reconstructed video unit (figure 2: the final filtered chroma value Cb/Cr is obtained).
Regarding claim 2, Misra teaches the method according to claim 1, wherein the determining a filter coefficient according to neighborhood information contained in a convolution template of the first reconstructed video unit and the second reconstructed video unit comprises:
for each pixel point in a video unit of the reconstructed picture and a video unit of an original picture, determining a difference between the pixel point at each neighborhood position in the convolution template and each pixel point, multiplying the differences respectively to obtain a first pixel product, and determining a difference between the pixel point of the video unit of the original picture and the pixel point of the video unit of the reconstructed picture to obtain a covariance; and
determining, based on a Wiener filtering method, the filter coefficient according to the covariance ((" a Wiener filtering method"): implicit feature, since the Wiener filtering method is the procedure used for determining the ALF filter coefficeints, see section Introduction page 1 column 1: " ... The ALF process was proposed for standardization in [1 ], [2] and derived from earlier work on adaptive interpolation filters [3]. ... ", see references [1] and [2] that mention Wiener filtering.).
Regarding claim 3, Misra teaches the method according to claim 2, wherein the video unit of the reconstructed picture comprises a reconstructed picture, or a slice, or a coding block, or a coding tree block ((" ... wherein the video unit of the reconstructed picture comprises a reconstructed picture, or a slice, or a coding block, or a coding tree block."): implicit feature, since figure 2 discloses filtering for block based video compression standards.).
Regarding claim 4, Misra teaches the method according to claim 1, wherein the filtering, based on the convolution template and the filter coefficient, the first reconstructed video unit and the second reconstructed video unit to obtain a third reconstructed video unit (("performing Sample Adaptive Offset (SAO) loop filtering on the reconstructed picture ... "): see figure 2: SAO.) comprises at least one of the following:
performing, based on the convolution template, filtering processing on a luma component of the first reconstructed video unit and the second reconstructed video unit according to the filter coefficient (figure 2: SAO Luma);
performing, based on the convolution template, filtering processing on a first chroma component of the first reconstructed video unit and the second reconstructed video unit according to the filter coefficient (figure 2: SAO Cb/Cr); and
performing, based on the convolution template, filtering processing on a second chroma component of the first reconstructed video unit and the second reconstructed video unit according to the filter coefficient (figure 2: SAO Cb/Cr).
Regarding claim 5, Misra teaches the method according to claim 1, wherein the filtering a reconstructed picture of a current picture by using a first filter comprises:
performing Deblocking Filter (DBF) on the reconstructed picture; or
performing Sample Adaptive Offset (SAO) loop filtering on the reconstructed picture; or
performing DBF and SAO loop filtering on the reconstructed picture; or
performing Luma Mapping with Chroma Scaling (LMCS) processing on the reconstructed picture (Adaptive Offset (SAO) [II. FILTERING OPERATION]).
Regarding claim 7, Misra teaches the method according to claim 1, further comprising:
determining a first loss between a pixel of a video unit of the reconstructed picture and a pixel of an original picture after filtering according to the first reconstructed video unit, the second reconstructed video unit, and the filter coefficient;
determining a second loss between the pixel of the video unit of the reconstructed picture and the pixel of the original picture before filtering according to the first reconstructed video unit, the second reconstructed video unit, and the filter coefficient; and
determining whether to perform Cross-Component Adaptive (CCA) filtering on the video unit of the current picture according to the first loss and the second loss (the ALF filtering involves a diamond shape filter with a center sample position and neighbour sample positions. The ALF is calculated according to the formula shown in the paragraph under figure 1. This formula can be rearranged mathematically to a form that corresponds to the claim. Moreover, the final result in D1 is the sum of two ALF filters (CC-ALF and ALF Chroma).);
or, the method further comprising:
determining a first loss between a pixel of a video unit of the reconstructed picture and a pixel of an original picture after filtering according to the first reconstructed video unit, the second reconstructed video unit, and the filter coefficient;
filtering through a preset filter coefficient, and determining a third loss between the pixel of the video unit of the reconstructed picture and the pixel of the original picture after filtering according to the first reconstructed video unit, the second reconstructed video unit, and the filter coefficient; and
according to the first loss and the third loss, determining to perform filtering processing through the filter coefficient, or determining to perform filtering processing through the preset filter coefficient;
or, the method further comprising:
determining a first loss between a pixel of a video unit of the reconstructed picture and a pixel of an original picture after filtering according to the first reconstructed video unit, the second reconstructed video unit, and the filter coefficient;
determining a second loss between the pixel of the video unit of the reconstructed picture and the pixel of the original picture before filtering according to the first reconstructed video unit, the second reconstructed video unit, and the filter coefficient;
filtering the video unit of the current picture according to the filter coefficient of the neighboring video unit of the video unit of the current picture, and determining a fourth loss between the pixel of the video unit of the reconstructed picture and the pixel of the original picture after filtering; and
determining, according to the first loss, the second loss, and the fourth loss, the filter coefficient used by the video unit of the current picture, and performing filtering processing according to the determined filter coefficient; or,
the method further comprising:
determining a first loss between a pixel of a video unit of the reconstructed picture and a pixel of an original picture after filtering according to the first reconstructed video unit, the second reconstructed video unit, and the filter coefficient;
determining a second loss between the pixel of the video unit of the reconstructed picture and the pixel of the original picture before filtering according to the first reconstructed video unit, the second reconstructed video unit, and the filter coefficient; and
determining whether to filter the video unit of the current picture according to the first loss and the second loss, recalculating the filter coefficient for the video unit with filtering turned on, again determining whether to filter according to the first loss and the second loss, and confirming whether to filter the video unit of the current picture after repeating N times.
Regarding claim 11, Misra teaches the method according to claim 1, wherein the filtering, based on the convolution template and the filter coefficient, the first reconstructed video unit and the second reconstructed video unit to obtain a third reconstructed video unit comprises:
calculating, based on the first reconstructed video unit, a difference between a central pixel point and a neighborhood pixel point of the convolution template, and multiplying the difference by the filter coefficient of a corresponding position of the neighborhood pixel point to obtain a first result; at the same time, calculating, based on the second reconstructed video unit, the difference between the central pixel point and the neighborhood pixel point of the convolution template, and multiplying the difference by the filter coefficient of the corresponding position of the neighborhood pixel point to obtain a second result; and
adding the first result, the second result, and the second reconstructed video unit, and then performing rounding processing to obtain the third reconstructed video unit (the ALF filtering involves a diamond shape filter with a center sample position and neighbour sample positions. The ALF is calculated according to the formula shown in the paragraph under figure 1. This formula can be rearranged mathematically to a form that corresponds to the claim. Moreover, the final result in D1 is the sum of two ALF filters (CC-ALF and ALF Chroma).).
Regarding claim 13, Misra teaches a video decoding method, comprising:
acquiring a bit stream containing a coded video sequence, and obtaining loop filtering control information corresponding to a loop filtering mode, wherein the loop filtering control information comprises a filter coefficient (Fig. 2);
filtering a reconstructed picture of a current picture by using a first filter, so as to acquire a first reconstructed video unit (figure 2: SAO Luma);
filtering the reconstructed picture of the current picture by using a second filter, so as to acquire a second reconstructed video unit (figure 2: SAO Cb/Cr);
filtering, based on a convolution template of the first reconstructed video unit (CC-ALF cCb/Cr is a filter using a diamond shape convolution template) and the second reconstructed video unit (ALF Chroma is a filter using a diamond shape convolution template), and the filter coefficient, the first reconstructed video unit and the second reconstructed video unit to obtain a third reconstructed video unit (figure 2: the final filtered chroma value Cb/Cr is obtained).
Regarding claim 14, Misra teaches the method according to claim 13, wherein the filtering a reconstructed picture of a current picture by using a first filter comprises:
performing Deblocking Filter (DBF) on the reconstructed picture; or
performing Sample Adaptive Offset (SAO) loop filtering on the reconstructed picture; or
performing DBF and SAO loop filtering on the reconstructed picture; or
performing Luma Mapping with Chroma Scaling (LMCS) processing on the reconstructed picture (Adaptive Offset (SAO) [II. FILTERING OPERATION]).
Regarding claim 16, Misra teaches the method according to claim 13, wherein the filtering, based on the convolution template and the filter coefficient, the first reconstructed video unit and the second reconstructed video unit to obtain a third reconstructed video unit comprises:
calculating, based on the first reconstructed video unit, a difference between a central pixel point and a neighborhood pixel point of the convolution template, and multiplying the difference by the filter coefficient of a corresponding position of the neighborhood pixel point to obtain a first result; at the same time, calculating, based on the second reconstructed video unit, the difference between the central pixel point and the neighborhood pixel point of the convolution template, and multiplying the difference by the filter coefficient of the corresponding position of the neighborhood pixel point to obtain a second result; and
adding the first result, the second result, and the second reconstructed video unit, and then performing rounding processing to obtain the third reconstructed video unit (the ALF filtering involves a diamond shape filter with a center sample position and neighbour sample positions. The ALF is calculated according to the formula shown in the paragraph under figure 1. This formula can be rearranged mathematically to a form that corresponds to the claim. Moreover, the final result in D1 is the sum of two ALF filters (CC-ALF and ALF Chroma).).
Regarding claim 25, Misra teaches the method according to claim 13, further comprising: filtering the video unit with the loop filtering mode turned on by using the loop filtering mode according to the video unit filtering coefficient absolute value and the video unit filtering coefficient sign (alf_cc_cb_coeff_abs; alf_cc_cb_coeff_sign).
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 6, 15, 17-18, 21-22, 26, and 30-21 are rejected under 35 U.S.C. 103 as being unpatentable over Misra in view of IKAI (US 20210021820 A1).
Regarding claim 6, Misra teaches the method according to claim 1. Misra does not explicitly teach the following limitations, however, in an analogous art, IKAI teaches wherein the filtering the reconstructed picture by using a second filter, so as to obtain a second reconstructed video unit comprises:
performing neural network loop filtering on the reconstructed picture to obtain the second reconstructed video unit; or
performing neural network loop filtering on the reconstructed picture, and performing weighted summation on a neural network loop filtering result and the first reconstructed video unit, so as to obtain the second reconstructed video unit; or
performing neural network loop filtering on the reconstructed picture, and scaling the neural network loop filtering result according to an original picture, so as to obtain the second reconstructed video unit; or
performing other loop filtering except the neural network loop filtering on the reconstructed picture to obtain the second reconstructed video unit, wherein the other loop filtering comprises at least one of the following: DBF, SAO loop filtering, and LMCS ([0198] In this manner, in the loop filter 107f, the neural network included in the filtering processing unit 1071f includes multiple layers in each of which the filter is applied).
It would have been obvious for a person of ordinary skill in the art, before the effective filling date of the claimed invention, to take the teachings of IKAI and apply them to Misra. One would be motivated as such as image quality of the filtered image can be enhanced (IKAI: [0164]).
Regarding claim 15, Misra teaches the method according to claim 13. Misra does not explicitly teach the following limitations, however, in an analogous art, IKAI teaches wherein the filtering the reconstructed picture by using a second filter, so as to obtain a second reconstructed video unit comprises:
performing neural network loop filtering on the reconstructed picture to obtain the second reconstructed video unit; or
performing neural network loop filtering on the reconstructed picture, and performing weighted summation on a neural network loop filtering result and the first reconstructed video unit, so as to obtain the second reconstructed video unit; or
performing neural network loop filtering on the reconstructed picture, and scaling the neural network loop filtering result according to an original picture, so as to obtain the second reconstructed video unit; or
performing other loop filtering except the neural network loop filtering on the reconstructed picture to obtain the second reconstructed video unit,
wherein the other loop filtering comprises at least one of the following: DBF, SAO loop filtering, and LMCS. ([0198] In this manner, in the loop filter 107f, the neural network included in the filtering processing unit 1071f includes multiple layers in each of which the filter is applied).
It would have been obvious for a person of ordinary skill in the art, before the effective filling date of the claimed invention, to take the teachings of IKAI and apply them to Misra. One would be motivated as such as image quality of the filtered image can be enhanced (IKAI: [0164]).
Regarding claim 17, Misra teaches the method according to claim 13. Misra does not explicitly teach the following limitations, however, in an analogous art, IKAI teaches wherein the loop filtering information comprises at least one of the following:
a sequence-level filtering switch flag, configured to indicate that the loop filtering mode is turned on or turned off for a video sequence where a current video frame is located (Fig. 4: [0151] The filter ON/OFF determination unit 1173 refers the source image input to the image coding apparatus 11, and controls whether or not to apply a filter in the loop filter 107. );
a filtered picture-level flag, configured to indicate whether loop filtering model information appears in picture header information or in slice header information ([0227] The loop filter configuration unit 117m includes a filter coefficient predictor 1175 in addition to the filter coefficient coder 1172 and the filter ON/OFF determination unit 1173 described above.); and
loop filtering model structure information, configured to indicate that the loop filtering is performed on a video unit to which the loop filtering mode is applied (Fig .6).
It would have been obvious for a person of ordinary skill in the art, before the effective filling date of the claimed invention, to take the teachings of IKAI and apply them to Misra. One would be motivated as such as image quality of the filtered image can be enhanced (IKAI: [0164]).
Regarding claim 18, Misra in view of IKAI teaches the method according to claim 17. Misra does not explicitly teach the following limitations, however, in an analogous art, IKAI teaches determining a value of the sequence-level filtering switch flag; and
when the value of the sequence-level filtering switch flag is a first value, determining to enable the loop filtering for the current coded video sequence, and when the value of the sequence-level filtering switch flag is a second value, determining to not enable the loop filtering for the current coded video sequence, wherein the first value is different from the second value ([0151] The filter ON/OFF determination unit 1173 refers the source image input to the image coding apparatus 11, and controls whether or not to apply a filter in the loop filter 107. Further, the filter ON/OFF determination unit 1173 may also refer to a filtered decoded image output by the filter operation unit 10722, and control whether or not to apply a filter in the loop filter 107.);
or, the method further comprising:
determining a value of the filtered picture-level flag; and
when the value of the filtered picture-level flag is a third value, determining that the loop filtering model information appears in a picture header, and when the value of the filtered picture-level flag is a fourth value, determining that the loop filtering model information appears in a slice header, wherein the third value is different from the fourth value.
It would have been obvious for a person of ordinary skill in the art, before the effective filling date of the claimed invention, to take the teachings of IKAI and apply them to Misra. One would be motivated as such as image quality of the filtered image can be enhanced (IKAI: [0164]).
Regarding claim 21, Misra in view of IKAI teaches the method according to claim 17. Misra teaches wherein the loop filtering model structure information comprises at least one of the following:
a video unit filtering switch flag, configured to indicate that the loop filtering mode is turned on or turned off for the video unit; a video unit component switch flag, configured to indicate that the loop filtering mode is turned on or turned off for a video unit component; a video unit block level filtering switch flag, configured to indicate that the loop filtering mode is turned on or turned off at each level in the video unit (sps_cc_alf_enabled_flag; alf_cc_cb_filter_flag; alf_cc_cr_filter_flag);
a video unit filtering coefficient absolute value, configured to indicate a filtering coefficient absolute value corresponding to each level in the video unit (alf_cc_cb_coeff_abs; alf_cc_cr_coeff_abs); and
a video unit filtering coefficient sign, configured to indicate a filtering coefficient sign corresponding to each level in the video unit (alf_cc_cb_coeff_sign);
wherein the video unit component comprises at least one of the following:
a luma component of the video unit;
a first chroma component of the video unit; and
a second chroma component of the video unit (alf_cc_cr_filter_flag).
Regarding claim 22, Misra in view of IKAI teaches the method according to claim 21. Misra teaches determining a value of the video unit filtering switch flag, and determining, according to the value, to enable the loop filtering or not enable the loop filtering for a current video unit (sps_cc_alf_enabled_flag);
or, the method further comprising:
determining a value of a luma component switch flag of the video unit, and determining, according to the value, to enable the loop filtering for the luma component of the current video unit, or not enable the loop filtering for the luma component of the current video unit;
determining a value of a first chroma component switch flag of the video unit, and determining, according to the value, to enable the loop filtering for the first chroma component of the current video unit, or not enable the loop filtering for the first chroma component of the current video unit; and
determining a value of a second chroma component switch flag of the video unit, and determining, according to the value, to enable the loop filtering for the second chroma component of the current video unit, or not enable the loop filtering for the second chroma component of the current video unit;
or, the method further comprising:
determining a value of the video unit block-level filtering switch flag, and determining, according to the value, to enable the loop filtering for a coding block in the video unit, or not enable the loop filtering for the coding block in the video unit.
Regarding claim 26, Misra in view of IKAI teaches the method according to claim 17. Misra teaches wherein the loop filtering model structure information further comprises:
a video unit block-level filter coefficient merge mode switch flag, configured to indicate whether to enable a coefficient merge mode for a coding block in the video unit and a component of the coding block; and
a video unit block-level filter coefficient merge mode type flag, configured to indicate a position of a neighboring coding block of the current coding block in the video unit, wherein the current coding block performs the loop filtering by using a filter coefficient of the neighboring coding block;
wherein a coding block component comprises at least one of the following: a luma component, a first chroma component, and a second chroma component
or, wherein the loop filtering model structure information further comprises:
a cross-component filtering mode switch flag, configured to indicate whether to enable a cross-component filtering mode for a coding block in the video unit and a component of the coding block or not (alf_cc_cb_filter_flag; alf_cc_cr_filter_flag).
Regarding claim 30, Misra teaches the method according to claim 1. Misra does not explicitly teach the following limitations, however, in an analogous art, IKAI teaches a non-transitory computer-readable storage medium, in which a computer program is stored, wherein when running, the computer program is configured to perform the method according to claim 1 ([0048] storage medium).
It would have been obvious for a person of ordinary skill in the art, before the effective filling date of the claimed invention, to take the teachings of IKAI and apply them to Misra. One would be motivated as such as image quality of the filtered image can be enhanced (IKAI: [0164]).
Regarding claim 31, Misra teaches the method according to claim 1. Misra does not explicitly teach the following limitations, however, in an analogous art, IKAI teaches electronic apparatus, comprising a memory and a processor, wherein the memory stores a computer program, and the processor is configured to execute the computer program, so as to perform the method according to claim 1 (computer system [0243]).
It would have been obvious for a person of ordinary skill in the art, before the effective filling date of the claimed invention, to take the teachings of IKAI and apply them to Misra. One would be motivated as such as image quality of the filtered image can be enhanced (IKAI: [0164]).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to HESHAM K ABOUZAHRA whose telephone number is (571)270-0425. The examiner can normally be reached M-F 8-5.
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/HESHAM K ABOUZAHRA/ Primary Examiner, Art Unit 2486
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