Side-Match Finite-State Vector Quantization with Adaptive Block Classification for Image Compression

概要

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In this article, an efficient vector quantization(VQ)scheme called side-match finite-state vector quantization with adaptive block classification is presented for image compression. It makes use of edge information contained in image in additional to the average values of blocks forming the image. In order to achieve low bit rate coding while preserving good quality images, neighboring blocks are utilized to predict the class of current block. Image blocks are mainly classified as edge blocks and non-edge blocks in this coding scheme. To improve the coding efficiency, edge blocks and non-edge blocks are further reclassified into different classes, respectively. Moreover, the number of bits for encoding an image is greatly reduced by foretelling the class of input block and applying small state codebook in corresponding class. The improvement of the proposed coding scheme is attractive as compared with other VQ techniques.
社団法人電子情報通信学会の論文
2000-08-25