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Proceedings Paper

Image coding using variable-rate classified side-match vector quantization
Author(s): Zhe-Ming Lu; Sheng-He Sun
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Paper Abstract

Vector quantization (VQ) is an attractive image compression technique. VQ utilizes the high correlations between neighboring pixels in a block, but disregards the high correlations between the adjacent blocks. Unlike VQ, Side match VQ (SMVQ) exploits codeword information of two encoded adjacent blocks, the upper and left blocks, to encode the current input vector. However, SMVQ doesn’t consider edge characteristics of the current input vector and its neighboring vectors at all. Variable-rate SMVQ has been proposed in the literature that 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 didn’t take the variance of the current input vector itself into account. Based on this, variable-rate SMVQ with a new block classifier called new CSMVQ is proposed. This classifier uses the variance of the input vector together with variances of its neighboring encoded blocks to encode the input vector. Experimental results show that new CSMVQ can obtain lower bit rate than VQ and old CSMVQ. Moreover, new CSMVQ can obtain higher image quality than SMVQ, old CSMVQ and VQ. In addition, new CSMVQ needs shorter encoding time than old CSMVQ.

Paper Details

Date Published: 19 January 2001
PDF: 8 pages
Proc. SPIE 4170, Image and Signal Processing for Remote Sensing VI, (19 January 2001); doi: 10.1117/12.413908
Show Author Affiliations
Zhe-Ming Lu, Harbin Institute of Technology (China)
Sheng-He Sun, Harbin Institute of Technology (China)

Published in SPIE Proceedings Vol. 4170:
Image and Signal Processing for Remote Sensing VI
Sebastiano Bruno Serpico, Editor(s)

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