Improved content adaptive update weight control in motion-compensated temporal filtering
In this paper, we present a content-adaptive chrominance and motion vector correlation-based update step for scalable video coding. It takes advantage of the chrominance information in the video sequence and the correlation of motion vectors (MVs) of the neighboring blocks as well as the correlation of the derived update MVs in the low-pass frames to improve the update step of lifting-based motion-compensated temporal filtering (MCTF). We further enhance our proposed method via an efficient content adaptive analysis. Experimental results show that the proposed algorithm improves the visual quality of the reconstructed video sequences at different bit rates and resolutions