Adaptive Temporal Trajectory Filtering for Video Compression
Most in-loop filters currently being employed in video compression algorithms use spatial information from a single frame of the video sequence only. In this paper, a new filter is introduced and investigated that combines both spatial and temporal information to provide subjective and objective quality improvement. The filter only requires a small overhead on slice level while using the temporal information conveyed in the bit stream to reconstruct the individual motion trajectory of every pixel in a frame at both encoder and decoder. This information is then used to perform pixel-wise adaptive motion-compensated temporal filtering. It is shown that the filter performs better than the state-of-the-art codec H.264/AVC over a large range of sequences and bit rates. Additionally, the filter is compared with another, Wiener-based in-loop filtering approach and a complexity analysis of both algorithms is conducted.