US 12,477,127 B2
Video coding using multi-model linear model
Xianglin Wang, Beijing (CN); Hong-Jheng Jhu, Beijing (CN); and Yi-Wen Chen, Beijing (CN)
Assigned to BEIJING DAJIA INTERNET INFORMATION TECHNOLOGY CO., LTD., Beijing (CN)
Filed by BEIJING DAJIA INTERNET INFORMATION TECHNOLOGY CO., LTD., Beijing (CN)
Filed on May 13, 2024, as Appl. No. 18/662,823.
Application 18/662,823 is a continuation of application No. 17/438,334, granted, now 12,015,791, previously published as PCT/US2020/022086, filed on Mar. 11, 2020.
Claims priority of provisional application 62/817,419, filed on Mar. 12, 2019.
Prior Publication US 2024/0298013 A1, Sep. 5, 2024
This patent is subject to a terminal disclaimer.
Int. Cl. H04N 19/186 (2014.01); H04N 19/105 (2014.01); H04N 19/132 (2014.01); H04N 19/176 (2014.01); H04N 19/42 (2014.01)
CPC H04N 19/186 (2014.11) [H04N 19/105 (2014.11); H04N 19/132 (2014.11); H04N 19/176 (2014.11); H04N 19/42 (2014.11)] 17 Claims
OG exemplary drawing
 
1. A method for predicting a chroma block of a video signal, comprising:
obtaining video pictures, wherein the video pictures are partitioned into a plurality of coding units (CUs), each of the CU includes the chroma block and a corresponding luma block;
obtaining a plurality of reconstructed luma samples of the luma block, a plurality of reconstructed neighboring luma samples, and a plurality of reconstructed neighboring chroma samples, respectively;
selecting, from the plurality of reconstructed neighboring luma samples and the plurality of reconstructed neighboring chroma samples, a group of reference luma samples and a group of reference chroma samples, wherein each reference luma sample corresponds to a respective reference chroma sample; wherein selecting the group of reference luma samples and the group of reference chroma samples includes selecting every other luma samples from the plurality of reconstructed neighboring luma samples and every other chroma samples from the plurality of reconstructed neighboring chroma samples;
computing a threshold luma value from the plurality of reconstructed neighboring luma samples, and a threshold chroma value from the plurality of reconstructed neighboring chroma samples;
determining a maximum luma value and a minimum luma value from the group of the reference luma samples, wherein the threshold luma value is between the minimum luma value and the maximum luma value;
generating a multi-model linear model including a first linear model between the minimum luma value and the threshold luma value, and a second linear model between the threshold luma value and the maximum luma value; and
predicting the chroma block from the luma block using the multi-model linear model.