Share Email Print

Proceedings Paper

Side-match vector quantization design for noisy channel
Author(s): Chung Jung Kuo; Chang S. Lin
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

Side-match vector quantization is an attractive finite-state coding technique for images. This research shows that the side-match vector quantization is similar to catastrophic code where infinite number of decoding errors is caused by a finite number of channel errors. A 1D side- match vector quantization is first proposed to limit the error propagation across different row of blocks when the channel is noisy. Then three tests are proposed for noisy rows detection with minimum overhead information. These tests include the 1D side-match vector quantization decoding test, double-row test, and triple-row test. Finally, a modified Viterbi algorithm is proposed to decode the images encoded by the 1D side-match vector quantization.

Paper Details

Date Published: 16 September 1994
PDF: 10 pages
Proc. SPIE 2308, Visual Communications and Image Processing '94, (16 September 1994); doi: 10.1117/12.185931
Show Author Affiliations
Chung Jung Kuo, National Chung Cheng Univ. (Taiwan)
Chang S. Lin, National Chung Cheng Univ. (Taiwan)

Published in SPIE Proceedings Vol. 2308:
Visual Communications and Image Processing '94
Aggelos K. Katsaggelos, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?