Prosecution Insights
Last updated: April 19, 2026
Application No. 18/858,190

METHOD AND DEVICE FOR ENCODING/DECODING IMAGE ON BASIS OF CONVOLUTIONAL CROSS-COMPONENT MODEL (CCCM) PREDICTION, AND RECORDING MEDIUM FOR STORING BITSTREAM

Final Rejection §102§103
Filed
Oct 18, 2024
Examiner
KIR, ALBERT
Art Unit
2485
Tech Center
2400 — Computer Networks
Assignee
LG Electronics Inc.
OA Round
2 (Final)
67%
Grant Probability
Favorable
3-4
OA Rounds
2y 6m
To Grant
84%
With Interview

Examiner Intelligence

Grants 67% — above average
67%
Career Allow Rate
332 granted / 498 resolved
+8.7% vs TC avg
Strong +18% interview lift
Without
With
+17.5%
Interview Lift
resolved cases with interview
Typical timeline
2y 6m
Avg Prosecution
45 currently pending
Career history
543
Total Applications
across all art units

Statute-Specific Performance

§101
6.0%
-34.0% vs TC avg
§103
47.0%
+7.0% vs TC avg
§102
24.3%
-15.7% vs TC avg
§112
13.7%
-26.3% vs TC avg
Black line = Tech Center average estimate • Based on career data from 498 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 01/01/2026, in which claims 1-13 are pending and ready for examination. Response to Amendment Claims 6-7 are currently amended. Response to Argument Applicant's arguments filed 01/01/2026 have been fully considered but they are not persuasive. With respect to claims rejected under 35 USC 102, 103, the Applicant argues, see Pg. 7-8, that Lainema does not teach “determining a co-located luma sample … deriving at least one representative neighboring luma sample … generating a prediction sample of the current chroma sample based on the representative neighboring luma sample …” by asserting that Lainema only teaches generating and solving autocorrelation matrix and cross-correlation vector from neighboring luma and chroma samples and pre-regularizing matrix A, but nothing about deriving a representative neighboring luma sample and generating a prediction sample based on a representative neighboring luma sample and CCCM coefficients. Examiner cannot concur. As taught in Para. [0060-62], Lainema at least teaches using convolutional cross-component filter to predict blocks samples, wherein corresponding luma samples and their neighboring samples in the neighborhood are used as input to generate output of prediction samples of chroma block samples and their neighboring samples in the neighborhood, wherein the neighboring samples includes at least a representative sample. 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 1-5 and 12-13 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Lainema (US Pub. 20250220189 A1). Regarding claim 1, Lainema an image decoding method performed by an image decoding apparatus, the image decoding method comprising (Lainema; Fig. 1-2, Para. [0060]. An image decoding system/method is used to perform video coding.): deriving a convolutional cross-component model (CCCM) coefficient based on an intra prediction mode of a current chroma block being a CCCM mode (Lainema; Para. [0060-62]. A convolutional cross-component model coefficient is determined in accordance with a coding mode of a current chroma block being a CCCM mode.); determining a co-located luma sample in a co-located luma block corresponding to a current chroma sample in the current chroma block and neighboring luma samples of the co- located luma sample (Lainema; Para. [0060-62]. A convolutional cross-component filter is used to predict blocks samples, wherein corresponding luma samples and their neighboring samples in the neighborhood are used as input to generate output of prediction samples of chroma block samples and their neighboring samples in the neighborhood, wherein co-located luma samples and neighboring samples are determined. Co-located and neighboring luma samples of a co-located luma block are determined fir a current chroma sample.); deriving at least one representative neighboring luma sample based on the neighboring luma samples (Lainema; Para. [0060-62]. A convolutional cross-component filter is used to predict blocks samples, wherein corresponding luma samples and their neighboring samples in the neighborhood are used as input to generate output of prediction samples of chroma block samples and their neighboring samples in the neighborhood, wherein the neighboring samples includes at least a representative sample. At least one representative neighboring luma sample is determined in accordance with neighboring samples, also see Para. [0084].); and generating a prediction sample of the current chroma sample based on the representative neighboring luma sample and the CCCM coefficient (Lainema; Para. [0060-62]. A convolutional cross-component filter is used to predict blocks samples, wherein corresponding luma samples and their neighboring samples in the neighborhood are used as input to generate output of prediction samples of chroma block samples and their neighboring samples in the neighborhood, wherein the neighboring samples includes at least a representative sample. A prediction sample is generated for a current chroma sample in accordance with a representative neighboring sample and a CCCM samples.). Regarding claim 2, Lainema discloses the neighboring luma samples include at least one of left, right, top, bottom, top-left, top-right, bottom-left or bottom-right neighboring luma samples of the co-located luma sample (Lainema; Para. [0058]. A neighboring luma sample includes at least of a left and top luma samples.). Regarding claim 3, Lainema discloses the representative neighboring luma sample is derived based on an average of the neighboring luma samples (Lainema; Para. [0084]. A representative neighboring luma sample is determined in accordance with an average of neighboring luma samples.). Regarding claim 4, Lainema discloses the representative neighboring luma sample is derived by downsampling using the co-located luma sample and the neighboring luma samples (Lainema; Para. [0062]. A representative neighboring luma sample is determined by downsampling collocated luma samples and neighboring samples.). Regarding claim 5, Lainema discloses the determination of the neighboring luma samples or the derivation of the representative neighboring luma sample is performed based on side information signaled through a bitstream (Lainema; Para. [0058]. Neighboring or representative neighboring luma samples are determined in accordance with signaled information through a bitstream.). Claim 12 is directed to an image encoding method performed by an image encoding apparatus, the image encoding method comprising a sequence of processing steps corresponding to the same as claimed in claim 1 above, and is rejected for the same reason of anticipation outlined above. Claim 13 is directed to an image encoding method performed by an image encoding apparatus, the image encoding method comprising a sequence of processing steps corresponding to the same as claimed in claim 1 above, and is rejected for the same reason of anticipation outlined 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 6-11 are rejected under 35 U.S.C. 103 as being unpatentable over Lainema (US Pub. 20250220189 A1) in view of Astola (US Pub. 20250227239 A1). Regarding claim 6, Lainema discloses the representative neighboring luma (Lainema; See remarks regarding claim 1 above.). But it does not specifically disclose the representative neighboring luma sample includes a top representative neighboring luma sample, a bottom representative neighboring luma sample, a left representative neighboring luma sample, and a right representative neighboring luma sample of the co-located luma sample, wherein the top representative neighboring luma sample is derived based on at least one neighboring luma sample adjacent to the top of the co-located luma sample, wherein the bottom representative neighboring luma sample is derived based on at least one neighboring luma sample adjacent to the bottom of the co-located luma sample, wherein the left representative neighboring luma sample is derived based on at least one neighboring luma sample adjacent to the left of the co-located luma sample, and wherein the right representative neighboring luma sample is derived based on at least one neighboring luma sample adjacent to the right of the co-located luma sample. However, Astola teaches the representative neighboring luma sample includes a top representative neighboring luma sample, a bottom representative neighboring luma sample, a left representative neighboring luma sample, and a right representative neighboring luma sample of the co-located luma sample (Astola; Fig. 10-11, Para. [0222]. A representative neighbor luma sample includes an above, a bottom, a left, a right representative neighboring luma samples.), wherein the top representative neighboring luma sample is derived based on at least one neighboring luma sample adjacent to the top of the co-located luma sample (Astola; Fig. 10-11, Para. [0222]. An above representative neighboring luma sample is determined in accordance with a neighboring luma sample adjacent to a top of a collocated luma sample.), wherein the bottom neighboring luma sample is derived based on at least one neighboring luma sample adjacent to the bottom of the co-located luma sample (Astola; Fig. 10-11, Para. [0222]. A bottom representative neighboring luma sample is determined in accordance with a neighboring luma sample adjacent to a bottom of a collocated luma sample.), wherein the left representative neighboring luma sample is derived based on at least one neighboring luma sample adjacent to the left of the co-located luma sample (Astola; Fig. 10-11, Para. [0222]. A left representative neighboring luma sample is determined in accordance with a neighboring luma sample adjacent to a left of a collocated luma sample.), and wherein the right representative neighboring luma sample is derived based on at least one neighboring luma sample adjacent to the right of the co-located luma sample (Astola; Fig. 10-11, Para. [0222]. A right representative neighboring luma sample is determined in accordance with a neighboring luma sample adjacent to a right of a collocated 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 Lainema to adapt a cross-component mapping approach, by incorporating Astola’s teaching wherein samples at different locations of reference area are used for cross-component mapping, for the motivation to prediction chroma samples through convolution between samples of different channels (Astola; Abstract.). Regarding claim 7, modified Lainema further teaches the representative neighboring luma sample includes a horizontal representative neighboring luma samples, a vertical representative neighboring luma sample, a diagonal representative neighboring luma sample and an anti-diagonal representative neighboring luma sample (Astola; Fig. 10-11, Para. [0222]. A representative neighbor luma sample includes a horizontal, a vertical, a diagonal, and an anti-angle representative luma sample.), wherein the horizontal representative neighboring luma sample is derived based on at least one neighboring luma sample horizontally adjacent to the co-located luma sample (Astola; Fig. 10-11, Para. [0222]. A horizontal representative neighboring luma sample is determined in accordance with a neighboring luma sample horizontally adjacent to a collocated luma sample.), wherein the vertical representative neighboring luma sample is derived based on at least one neighboring luma sample vertically adjacent to the co-located luma sample (Astola; Fig. 10-11, Para. [0222]. A horizontal representative neighboring luma sample is determined in accordance with a neighboring luma sample vertically adjacent to a collocated luma sample.), wherein the diagonal representative neighboring luma sample is derived based on at least one neighboring luma sample diagonally adjacent to the co-located luma sample (Astola; Fig. 10-11, Para. [0222]. A horizontal representative neighboring luma sample is determined in accordance with a neighboring luma sample diagonally adjacent to a collocated luma sample.), and wherein the anti-diagonal representative neighboring luma sample is derived based on at least one neighboring luma sample anti-diagonally adjacent to the co-located luma sample (Astola; Fig. 10-11, Para. [0222]. A horizontal representative neighboring luma sample is determined in accordance with a neighboring luma sample anti-diagonally adjacent to a collocated luma sample.). Regarding claim 8, modified Lainema further teaches the current chroma block includes a first chroma block and a second chroma block, and wherein the CCCM coefficient for the first chroma block is derived independently from the CCCM coefficient for the second chroma block (Astola; Para. [0290]. A current chroma includes a first chroma block and a second chroma block, wherein a CCM.). Regarding claim 9, modified Lainema further discloses the current chroma block includes a first chroma block and a second chroma block, wherein CCCM prediction for the first chroma block is performed based on the co-located luma block, and wherein CCCM prediction for the second chroma block is performed based on the first chroma block (Astola; Para. [0290]. A current chroma includes a first chroma block and a second chroma block, werehin CCCM prediction for a first chroma block is performed in accordance with a collocated luma block, CCCM prediction for a second chroma block is performed in accordance with a first chroma block.). Regarding claim 10, modified Lainema discloses the deriving the CCCM coefficient comprises: determining a reference sample area (Lainema; Para. [0058-60]. Reference sample area is determined. Astola; Para. [0278, 287]. Reference sample area is determined.); and deriving a CCCM coefficient using at least one reference sample in the reference sample area (Lainema; Para. [0058-60]. A CCCM coefficient is determined using at least a reference sample in a reference sample area. Astola; Para. [0278, 287]. A CCCM coefficient is determined using at least a reference sample in a reference sample area.), and wherein the reference sample area is determined based on information about a CCCM mode (Lainema; Para. [0058-60]. A reference sample area is determined in accordance with information about a CCCM mode. Astola; Para. [0278, 287]. A reference sample area is determined in accordance with information about a CCCM mode.). Regarding claim 11, modified Lainema further teaches the CCCM mode includes a first mode and a second mode (Lainema; Para. [0058-60]. A CCCM mode includes a first mode and a second mode. Astola; Para. [0278, 287]. A CCCM mode includes a first mode and a second mode.), wherein the first mode is a mode that uses only an area adjacent to the top of the current chroma block and the co-located luma block as the reference sample area (Lainema; Para. [0058-60]. A first mode is used for area only adjacent to top of a current chroma block and collocated luma. Astola; Para. [0278, 287]. A first mode is used for area only adjacent to top of a current chroma block and collocated luma.), and wherein the second mode is a mode that uses only an area adjacent to the left of the current chroma block and the co-located luma block as the reference sample area (Lainema; Para. [0058-60]. A second mode is used for area only adjacent to left of a current chroma block and collocated luma. Astola; Para. [0278, 287]. A second mode is used for area only adjacent to left of a current chroma block and collocated luma.). Conclusion The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Hu (US Pub. 20210160513 A1) teaches a video coding system that performs chroma sample filtering using offset of collocated luma samples. Budagavi (US Pat. 10708622 B2) teaches a video coding system that performs adaptive loop filtering for video coding. THIS ACTION IS MADE FINAL. 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

Oct 18, 2024
Application Filed
Sep 27, 2025
Non-Final Rejection — §102, §103
Jan 01, 2026
Response Filed
Mar 18, 2026
Final Rejection — §102, §103 (current)

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

3-4
Expected OA Rounds
67%
Grant Probability
84%
With Interview (+17.5%)
2y 6m
Median Time to Grant
Moderate
PTA Risk
Based on 498 resolved cases by this examiner. Grant probability derived from career allow rate.

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