VQ CODING FOR VIDEOPHONE APPLICATIONS ADOPTING KNOWLEDGE-BASED TECHNIQUES - IMPLEMENTATION ON PARALLEL ARCHITECTURES

An innovative algorithm is presented for the design and implementation of a self-adaptive vector quantizer for videophone coding. The codebook is organized in a binary tree structure capable to modify its topology and content in order to adaptively track the input varying statistics. The resulting tree structure is unbalanced, in the sense that some branches are extended more than others, depending on the input vector distribution, and therefore the suboptimality of tree structured VQ with respect to the full-search approach is greatly reduced. As it is known a priori that the class of input video data consists of a human head slowly moving against a static background, knowledge based segmentation of incoming frames can be efficiently performed. Exhaustive simulations have shown the effectiveness of the algorithm in standard CIF videophone sequences. Some procedures have been parallelized and implemented on a AT&T Pixel Machine for frame-rate coding. Results and comments on both the algorithm and the parallel implementation are presented.