Quality adaptive trained filters for compression artifacts removal
Ling Shao, Jingnan Wang, Ihor O. Kirenko, Gerard de Haan · IEEE International Conference on Acoustics Speech and Signal Processing · 2008
A compression artifacts removal algorithm that is adaptive to the artifact visibility level of the input video signal is proposed. The artifact visibility is determined per frame by the ratio of the accumulated gradient on the block edges to that of the remaining area. The filtering of each video frame is optimized using a least mean square mechanism which trains on pairs of target images and decompressed images of similar quality as the input frame. Experimental results show that the proposed approach outperforms several methods in coding artifact reduction.