Video Coding using Perceptually Weighted Vector Zerotrees and Adaptive Vector Quantization

A new system for intraframe coding of video is described. This system combines zerotrees of vectors of wavelet coefficients and the generalized-threshold-replenishment (GTR) technique for adaptive vector quantization (AVQ). A data structure, the vector zerotree (VZT), is introduced to identify trees of insignificant vectors, i.e., those vectors of wavelet coefficients in a dyadic subband decomposition that are to be coded as zero. GTR coders are then applied to each subband to efficiently code the significant vectors by way of adapting to their changing statistics. Both VZT generation and GTR coding are based upon minimization of criteria involving both rate and distortion. In addition, perceptual performance is improved by invoking simple, perceptually motivated weighting in both the VZT and the GTR coders. Our experimental findings indicate that the described VZTGTR system handles dramatic changes in image statistics, such as those due to a scene change, more efficiently than a scalar zerotree technique employing a nonadaptive scalar quantizer.