Side-match finite-state vector quantization with adaptive block classification for image compression

In this article, an efficient Vector quantization (VQ) scheme called side-m atch finite-state vector quantization with adaptive block classification is presented for image compression. It makes use of edge information containe d 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 imag es, neighboring blocks are utilized to predict the class of current block. Image blocks are mainly classified as edge blocks and non-edge blocks in th is coding scheme. To improve the coding efficiency, edge blocks and nea-edg e blocks are further reclassified into different classes, respectively. Mor eover, the number of bits for encoding an image is greatly reduced by foret elling the class of input block and applying small state codebook in corres ponding class. The improvement of the proposed coding scheme is attractive as compared with other VQ techniques.