Prosecution Insights
Last updated: May 29, 2026
Application No. 18/737,844

METHOD AND APPARATUS FOR CROSS-COMPONENT PREDICTION FOR VIDEO CODING

Non-Final OA §102§103
Filed
Jun 07, 2024
Priority
Dec 09, 2021 — provisional 63/287,898 +1 more
Examiner
KIR, ALBERT
Art Unit
2485
Tech Center
2400 — Computer Networks
Assignee
BEIJING DAJIA INTERNET INFORMATION TECHNOLOGY CO., LTD.
OA Round
2 (Non-Final)
68%
Grant Probability
Favorable
2-3
OA Rounds
9m
Est. Remaining
84%
With Interview

Examiner Intelligence

Grants 68% — above average
68%
Career Allowance Rate
346 granted / 512 resolved
+9.6% vs TC avg
Strong +17% interview lift
Without
With
+16.6%
Interview Lift
resolved cases with interview
Typical timeline
2y 8m
Avg Prosecution
22 currently pending
Career history
543
Total Applications
across all art units

Statute-Specific Performance

§101
0.5%
-39.5% vs TC avg
§103
82.6%
+42.6% vs TC avg
§102
11.3%
-28.7% vs TC avg
§112
2.2%
-37.8% vs TC avg
Black line = Tech Center average estimate • Based on career data from 512 resolved cases

Office Action

§102 §103
DETAILED ACTION The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . This office action is a response to an application filed on 11/11/2025, in which claims 1-26 are pending and ready for examination. Response to Amendment Claims 21-26 are newly added. Response to Argument Applicant's arguments filed on 11/11/2025 have been fully considered but they are not persuasive. With respect to claims rejected under 35 USC 102, 103, the Applicant argues, see Pg. 10 of filed Remarks on 11/11/2025, that Rath does not teach “classifying a luma sample … based on edge information …”, “predicting the chroma sample by applying … linear models corresponding to the classified sample group …” by asserting that Rath only teaches using depth information to perform CCLM which is different from using luma information to classify a luma sample based on edge information. Examiner cannot concur. As already taught in Para. [0165-167], it is stated that edge information is used to determine/classify luma having the corresponding CCLM models for chroma components, wherein edge information is determined in accordance with depth information which is determined using luma information, see Para. [0138], and thus edge information is determined using luma information. Thus, the Applicant’s argument is moot. Claim Rejections - 35 USC § 102 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. 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)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention. Claims 1, 3, 6-8, 10, 13-15, 17, 20, 24, 26 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Rath (WO 2023057501 A1). Regarding claim 1, Rath discloses a method for decoding video data, comprising (Rath; Fig. 7-8, Para. [0155]. A video decoding system/method is used for video coding.): obtaining a video block of the video data from a bitstream (Rath; Fig. 7-8, Para. [0155]. A video block is obtained from a bitstream.); classifying a luma sample corresponding to a chroma sample of the video block into one of a plurality of sample groups based on edge information of the luma sample, wherein the luma sample is obtained from one or more of luma samples of the video block (Rath; Para. [0165-168]. A luma sample corresponding to a chroma sample is classified into one of different groups in accordance with edge information, wherein a luma sample is obtained from one or more of luma samples of a block, wherein edge information is used to determine/classify luma having the corresponding CCLM models for chroma components, wherein edge information is determined in accordance with depth information which is determined using luma intensity information, see Para. [0138], and thus edge information is determined using luma intensity information.); and predicting the chroma sample by applying one of a plurality of linear prediction models corresponding to the classified sample group to the luma sample (Rath; Para. [0165-167]. A chroma sample is predicted by using one of different linear prediction models for a classified sample group of a luma sample.). Regarding claim 3, Rath discloses wherein each of the plurality of sample groups corresponds to a different linear prediction model of the plurality of linear prediction models (Rath; Para. [0167]. Each of different sample groups corresponds to a different linear model of different models.). Regarding claim 6, Rath discloses classifying neighboring luma samples around the video block into the plurality of sample groups based on edge information of the neighboring luma samples (Rath; Para. [0166-168]. Neighbor luma samples are classified/grouped into different groups in accordance with edge information of neighboring luma samples, also see Para. [0140].); and wherein each of the plurality of linear prediction models is derived from neighboring luma samples classified into a sample group corresponding to that linear prediction model and neighboring chroma samples corresponding to the neighboring luma samples classified into the sample group (Rath; Para. [0166-168]. Each of different linear models is determined from neighbor luma samples grouped into a group for a linear model and neighboring chroma samples corresponding to a neighboring sample grouped into a sample group.). Regarding claim 7, Rath discloses wherein the luma sample is obtained by either one of: down-sampling more than one of the luma samples of the video block corresponding to the chroma sample; or retrieving one of the luma samples of the video block that is at a collocated position with the chroma sample (Rath; Para. [0166]. A luma sample is obtained by at least retrieving one of luma samples of a video block that is co-located with a chroma sample.). Claims 8, 10, 13-14 are directed to a computer system, comprising: one or more processors; and one or more storage devices storing computer-executable instructions that, when executed, cause the one or more processors to be configured to perform a sequence of processing steps corresponding to the same as claimed in claims 1, 3, 6-7, and are rejected for the same reason of anticipation as outlined above. Claims 15, 17, 20 are directed to a non-transitory computer readable medium, storing a bitstream to be decoded by acts comprising a sequence of processing steps corresponding to the same as claimed in claims 1, 3, 6, and are rejected for the same reason of anticipation as outlined above. Regarding claim 24, Rath discloses a method for storing a bitstream, comprising (Rath; Fig. 7-8, Para. [0155]. A video decoding system/method is used for video coding.): performing the following steps to generate a bitstream: obtaining a video block of the video data from a video frame (Rath; Fig. 7-8, Para. [0155]. A video block is obtained from a bitstream.); classifying a luma sample corresponding to a chroma sample of the video block into one of a plurality of sample groups corresponding to plurality of linear prediction models respectively, based on intensity value of the luma sample, wherein the luma sample is obtained from one or more of luma samples of the video block (Rath; Para. [0165-168]. A luma sample corresponding to a chroma sample is classified into one of different groups in accordance with edge information, wherein a luma sample is obtained from one or more of luma samples of a block, wherein edge information is used to determine/classify luma having the corresponding CCLM models for chroma components, wherein edge information is determined in accordance with depth information which is determined using luma intensity information, see Para. [0138], and thus edge information is determined using luma intensity information.); and predicting the chroma sample by applying one of a plurality of linear prediction models corresponding to the classified sample group to the luma sample (Rath; Para. [0165-167]. A chroma sample is predicted by using one of different linear prediction models for a classified sample group of a luma sample.); and storing the bitstream (Rath; Para. [0083]. Bitstream is stored.), wherein the bitstream is to be decoded by the decoding method according to claim 1 (Rath; See remarks regarding claim 1 above.). Regarding claim 26, Rath discloses a method for transmitting a bitstream, comprising (Rath; Fig. 7-8, Para. [0155]. A video coding system/method is used for video coding and transmitting, also see Fig. 4.): performing the following steps to generate a bitstream: obtaining a video block of the video data from a video frame (Rath; Fig. 7-8, Para. [0155]. A video block is obtained from a bitstream.); classifying a luma sample corresponding to a chroma sample of the video block into one of a plurality of sample groups corresponding to plurality of linear prediction models respectively, based on intensity value of the luma sample, wherein the luma sample is obtained from one or more of luma samples of the video block (Rath; Para. [0165-168]. A luma sample corresponding to a chroma sample is classified into one of different groups in accordance with edge information, wherein a luma sample is obtained from one or more of luma samples of a block, wherein edge information is used to determine/classify luma having the corresponding CCLM models for chroma components, wherein edge information is determined in accordance with depth information which is determined using luma intensity information, see Para. [0138], and thus edge information is determined using luma intensity information.); and predicting the chroma sample by applying one of a plurality of linear prediction models corresponding to the classified sample group to the luma sample (Rath; Para. [0165-167]. A chroma sample is predicted by using one of different linear prediction models for a classified sample group of a luma sample.); and transmitting the bitstream (Rath; Para. [0083]. Bitstream is transmitted.), wherein the bitstream is to be decoded by the decoding method according to claim 1 (Rath; See remarks regarding claim 1 above.). Claim Rejections - 35 USC § 103 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. 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 2, 4-5, 9, 11-12, 16, 18-19, 21-23, and 25 are rejected under 35 U.S.C. 103 as being unpatentable over Rath (WO 2023057501 A1) in view of Zhao (WO 2019026721 A1). Regarding claim 2, Rath discloses the classifying the luma sample into the one of the plurality of sample groups (Rath; See remarks regarding claim 1 above.). But Rath does not specifically disclose wherein the classifying the luma sample into the one of the plurality of sample groups is further based on intensity value of the luma sample. However, Zhao wherein the classifying the luma sample into the one of the plurality of sample groups is further based on intensity value of the luma sample (Zhao; Para. [0048]. A luma sample is classified into one of different groups in accordance with intensity of a luma sample.). Therefore, it would have been obvious to a person with ordinary skill in the pertinent before the effective filing date of the claimed invention to modify the video coding system of Rath to adapt a sample edge classification, by incorporating Zhao’s teaching wherein sample edges are classified using edge strength, for the motivation to enable video block filtering (Zhao; Abstract.). Regarding claim 4, modified Rath teaches wherein the edge information comprises a direction and a strength of an edge of the luma sample (Zhao; Para. [0048]. Edge information includes a direction and a strength of an edge for a luma sample.). Regarding claim 5, modified Rath teaches wherein the classifying the luma sample into the one of the plurality of sample groups comprises: classifying the luma sample into the one of the plurality of sample groups based on a strength of an edge along one direction for the luma sample (Zhao; Para. [0048]. Luma samples are classified into one of different groups in accordance with a strength along one direction.). Regarding claim 21, modified Rath teaches the video block is encoded in a 4:4:4 chroma format (Zhao; Para. [0013]. A video block is coded in a 4:4:4 format.). Claims 9, 11-12, 22 are directed to a computer system, comprising: one or more processors; and one or more storage devices storing computer-executable instructions that, when executed, cause the one or more processors to be configured to perform a sequence of processing steps corresponding to the same as claimed in claims 2, 4-5, 21 and are non-patentable over the prior art for the same reason as previously indicated. Claims 16, 18-19, 23 are directed to a non-transitory computer readable medium, storing a bitstream to be decoded by acts comprising a sequence of processing steps corresponding to the same as claimed in claims 2, 4-5, 21, and are non-patentable over the prior art for the same reason as previously indicated. Regarding claim 25, modified Rath teaches the video block is encoded in a 4:4:4 chroma format (Zhao; Para. [0013]. A video block is coded in a 4:4:4 format.). Conclusion The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Du (US Pub. 20210195182 A1) teaches a video coding system that performs adaptive cross-component filtering. Jhu (US Pub. 20250227278 A1) teaches a video coding system that performs cross-component prediction for video coding. Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a). A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action. Any inquiry concerning this communication or earlier communications from the examiner should be directed to ALBERT KIR whose telephone number is (571)272-6245. The examiner can normally be reached Monday - Friday, 8:30am - 5:00pm. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jay Patel can be reached at (571) 272-2988. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /ALBERT KIR/ Primary Examiner, Art Unit 2485
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Prosecution Timeline

Jun 07, 2024
Application Filed
Aug 12, 2025
Non-Final Rejection mailed — §102, §103
Nov 11, 2025
Response Filed
Jan 02, 2026
Final Rejection mailed — §102, §103
Feb 26, 2026
Response after Non-Final Action

Precedent Cases

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Prosecution Projections

2-3
Expected OA Rounds
68%
Grant Probability
84%
With Interview (+16.6%)
2y 8m (~9m remaining)
Median Time to Grant
Moderate
PTA Risk
Based on 512 resolved cases by this examiner. Grant probability derived from career allowance rate.

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