Wavelet-based multi-view video coding with joint best basis wavelet packets
An approach to scalable multi-view video coding with joint best basis wavelet packets is examined in this paper. A 4-D wavelet transform is used to decorrelate the multi-view video data temporally, view-directionally, and spatially for efficient scalable compression. Motion compensated temporal filtering (MCTF) is used for temporal, and disparity compensated view filtering (DCVF) for view- directional decomposition. Adaptive wavelet packets as a generalized wavelet decomposition are presented for spatial decomposition. Two algorithms to find the best basis wavelet packets are evaluated and compared with classical dyadic wavelet transform: a low complexity entropy based best basis search and a search algorithm in a rate-distortion framework. In both cases, the joint best basis is determined for a group of frames rather than for each frame individually. Therefore, the rate to spend for the tree description is minimal while advantage is taken of the similarity of frames within a temporal-view-directional subband.