Optimized Non-local In-Loop Filter for Video Coding

Abstract

In order to compensate the shortcomings of existing in-loop filters only based on local correlation in video coding standards, many non-local based loop filters with high coding performance and computational complexity are proposed. In this paper, we propose a fast block matching algorithm, adaptive two-step block matching algorithm, based on our previous work, structure-driven adaptive non-local filter (SANF) which is computationally intensive because of the high complexity of block matching and singular value decomposition (SVD). Our proposed algorithm based on image spatial statistical characteristics utilizes fixed template to select adaptive number of similar blocks according to image content, which can reduce up to 75.2% search candidates compared to exhaustive search in SANF and the adaptive determination strategy can remove blocks with less relation to reference block in similar block group which have little help for compression performance, and the remove of them can reduce the computational complexity of SVD. Our proposed optimization algorithm can save encoding and decoding time significantly with negligible performance loss, which achieves 70.7%, 84.4%, 80.82% and 81.95% decoding time saving with only 0.13%, 0.05%, 0.13% and 0.15% increases of BD-rate for AI, RA, LDB and LDP configurations, respectively compared to original SANF in JEM-7.0.