Image Coding Based on Classified Side-Match Vector Quantization

Zhe-Ming LU  Jeng-Shyang PAN  Sheng-He SUN  

IEICE TRANSACTIONS on Information and Systems   Vol.E83-D   No.12   pp.2189-2192
Publication Date: 2000/12/25
Online ISSN: 
Print ISSN: 0916-8532
Type of Manuscript: LETTER
Category: Image Processing, Image Pattern Recognition
image coding,  image processing,  vector quantization,  side-match vector quantization,  

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The classified side-match vector quantizer, CSMVQ, has already been presented for low-bit-rate image encoding. It exploits a block classifier to decide which class the input vector belongs to using the variances of the upper and left codewords. However, this block classifier doesn't take the variance of the current input vector itself into account. This letter presents a new CSMVQ in which a two-level block classifier is used to classify input vectors and two different master codebooks are used for generating the state codebook according to the variance of the input vector. Experimental results prove the effectiveness of the proposed CSMVQ.