Abstract
A 4-D wavelet-based transform is used for efficient and scalable compression of multi-view video data. It is composed of a 1-D temporal wavelet transform, namely Motion Compensated Temporal Filtering (MCTF), a 1-D view-directional wavelet transform, namely Disparity Compensated View Filtering (DCVF), and a 2-D spatial transform. The latter is the subject of study in this paper. Whereas usually fixed isotropic wavelet or wavelet packet transforms have been used in the past for the spatial decomposition of the temporal-view-directional highpass bands, we now introduce the usage of adaptive anisotropic wavelet packet transforms as a generalization of wavelet and wavelet packet transforms. An efficient algorithm to adaptively find the rate-distortion optimal joint anisotropic basis for temporal-view-directional multi-view video subbands is derived. It is shown that the adaptive anisotropic transform performs best, compared with conventional wavelet or wavelet packet transforms.
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