US 12,244,807 B2
Determining adaptive quantization matrices using machine learning for video coding
James Holland, Folsom, CA (US); Sang-hee Lee, San Jose, CA (US); Ximin Zhang, San Jose, CA (US); and Zhan Lou, Shanghai (CN)
Assigned to Intel Corporation, Santa Clara, CA (US)
Appl. No. 18/031,563
Filed by Intel Corporation, Santa Clara, CA (US)
PCT Filed Nov. 30, 2020, PCT No. PCT/US2020/062604
§ 371(c)(1), (2) Date Apr. 12, 2023,
PCT Pub. No. WO2022/115113, PCT Pub. Date Jun. 2, 2022.
Prior Publication US 2023/0412808 A1, Dec. 21, 2023
Int. Cl. H04N 7/12 (2006.01); G06N 20/00 (2019.01); H04N 19/126 (2014.01); H04N 19/149 (2014.01); H04N 19/172 (2014.01)
CPC H04N 19/126 (2014.11) [G06N 20/00 (2019.01); H04N 19/149 (2014.11); H04N 19/172 (2014.11)] 22 Claims
OG exemplary drawing
 
1. A system comprising:
a memory to store at least a portion of a current frame of a video sequence; and
one or more processors coupled to the memory, the one or more processors to:
determine an estimated quantization parameter (QP) for the current frame using the current frame and one or more frames subsequent to the current frame;
determine the estimated QP is a within a particular sub-range of a plurality of sub-ranges of an available QP range;
selecting a quantization matrix for the current frame from a plurality of available quantization matrices based on the estimated QP being within the particular sub-range;
encode the current frame using the selected quantization matrix to generate at least a portion of a bitstream;
determine a second estimated QP, greater than or less than the estimated QP, for a second frame of the video sequence temporally prior to the current frame, the second estimated QP corresponding to a second sub-range of the plurality of sub-ranges and a second quantization matrix; and
encode the second frame using the selected quantization matrix in response to the estimated QP for the current frame being a quantization matrix switching QP.