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

Shinfeng D. LIN  Shih-Chieh SHIE  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E83-D   No.8   pp.1671-1678
Publication Date: 2000/08/25
Online ISSN: 
DOI: 
Print ISSN: 0916-8532
Type of Manuscript: PAPER
Category: Image Processing, Image Pattern Recognition
Keyword: 
image compression,  classified vector quantization,  side-match finite-state vector quantization,  adaptive variable-rate coding,  

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Summary: 
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.