US 12,425,603 B2
Methods and apparatuses for prediction refinement with optical flow
Xiaoyu Xiu, San Diego, CA (US); Yi-Wen Chen, San Diego, CA (US); Xianglin Wang, San Diego, CA (US); Shuiming Ye, San Diego, CA (US); Tsung-Chuan Ma, San Diego, CA (US); and Hong-Jheng Jhu, San Diego, CA (US)
Assigned to BEIJING DAJIA INTERNET INFORMATION TECHNOLOGY CO., LTD., Beijing (CN)
Filed by BEIJING DAJIA INTERNET INFORMATION TECHNOLOGY CO., LTD., Beijing (CN)
Filed on Jun. 27, 2024, as Appl. No. 18/755,670.
Application 18/755,670 is a continuation of application No. 17/510,328, filed on Oct. 25, 2021, granted, now 12,052,426.
Application 17/510,328 is a continuation of application No. PCT/US2020/030155, filed on Apr. 27, 2020.
Claims priority of provisional application 62/838,939, filed on Apr. 25, 2019.
Prior Publication US 2024/0348792 A1, Oct. 17, 2024
Int. Cl. H04N 19/137 (2014.01); H04N 19/105 (2014.01); H04N 19/132 (2014.01); H04N 19/176 (2014.01)
CPC H04N 19/137 (2014.11) [H04N 19/105 (2014.11); H04N 19/132 (2014.11); H04N 19/176 (2014.11)] 6 Claims
OG exemplary drawing
 
1. A method of bi-directional optical flow (BDOF) for encoding a video signal, comprising:
obtaining a first reference picture and a second reference picture associated with a video block, wherein the first reference picture is before a current picture and the second reference picture is after the current picture in display order;
obtaining first prediction samples of the video block from the first reference picture;
obtaining second prediction samples of the video block from the second reference picture;
obtaining padded prediction samples, and obtaining horizontal and vertical gradient values of the first prediction samples and the second prediction samples based on the padded prediction samples, comprising:
deriving rows and columns of prediction samples outside the video block for the first prediction samples;
deriving rows and columns of prediction samples outside the video block for the second prediction samples; and
obtaining horizontal and vertical gradient values of the first prediction samples and the second prediction samples based on the derived rows and columns of prediction samples,
wherein deriving the rows and columns of the prediction samples further comprises:
deriving a first part of prediction samples from integer reference samples in the reference picture left to a fractional sample position, and deriving a second part of prediction samples from integer reference samples in the reference picture above a fractional sample position; or
deriving a third part of prediction samples from integer reference samples in the reference picture that are closest to a fractional sample position in a horizontal direction, and deriving a fourth part of prediction samples from integer reference samples in the reference picture that are closest to a fractional sample position in a vertical direction;
obtaining motion refinements for samples in the video block based on the horizontal and vertical gradient values; and
obtaining bi-prediction samples of the video block based on the motion refinements.