Presentation + Paper
4 October 2023 Sub-block-based motion vector refinement of AVM
Mohammed Golam Sarwer, Jianle Chen, Debargha Mukherjee
Author Affiliations +
Abstract
This paper improves the inter prediction method of AOMedia Video Model (AVM) by introducing a sub-block based motion vector (MV) refinement method. In the proposed method, if a block is coded as a compound mode with bidirectional reference frame, MVs of the blocks are refined before producing the final prediction. In the proposed method, at first a predicted block is divided into number of non-overlapping sub-blocks. Then, for each sub-block, offset motion vectors are searched by minimizing the sum of absolute differences (SAD) between two predicted signals P0 and P1 (Assume, P0 and P1 are the predicted blocks from reference 0 and 1, respectively ). To simplify the searching process, instead of full search, a two-step integer search is proposed. At the first step, 9 offset MVs are searched ( initial MV and 8 neighbors ). The offset which produces minimum SAD in first step is selected as the center for the second step. In the second step, additional searching is conducted around the best offset found from the first step. A block level flag is conditionally signaled in the bitstream to indicate if the proposed method is used or not. The proposed method is implemented in AVM reference software research-v4.0.0. The simulation results show the proposed method can achieve -0.47% (YUV) and 0.90% (VMAF) BDRate gain as compared to AVM research-v4.0.0.
Conference Presentation
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Mohammed Golam Sarwer, Jianle Chen, and Debargha Mukherjee "Sub-block-based motion vector refinement of AVM", Proc. SPIE 12674, Applications of Digital Image Processing XLVI, 126740O (4 October 2023); https://doi.org/10.1117/12.2681766
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KEYWORDS
Optical flow

Video

Video compression

Interpolation

Tunable filters

Video coding

Displays

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