Side-match vector quantization design for noisy channel

Chung Jung Kuo; Chang S. Lin

doi:10.1117/12.185931

16 September 1994 Side-match vector quantization design for noisy channel

Chung Jung Kuo, Chang S. Lin

Proceedings Volume 2308, Visual Communications and Image Processing '94; (1994) https://doi.org/10.1117/12.185931
Event: Visual Communications and Image Processing '94, 1994, Chicago, IL, United States

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.

Citation Download Citation

Chung Jung Kuo and Chang S. Lin "Side-match vector quantization design for noisy channel", Proc. SPIE 2308, Visual Communications and Image Processing '94, (16 September 1994); https://doi.org/10.1117/12.185931

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available