DocumentCode
352385
Title
Fuzzy channel-optimized vector quantization for image coding
Author
Wen-Jyi Wang ; Lin, Chin-Tsai
Author_Institution
Dept. of Electr. Eng., Chung Yuan Christian Univ., Chung Li, Taiwan
Volume
6
fYear
2000
fDate
2000
Firstpage
1895
Abstract
A novel vector quantizer (VQ) design algorithm for noisy channels is presented in this paper. The algorithm, termed fuzzy channel-optimized vector quantizer (FCOVQ) design algorithm, performs the codeword training using an optimal fuzzy clustering technique where the channel noise is taken into account. In the existing crisp channel-optimized VQ (CCOVQ) design algorithms, the quantization accuracy is traded for less sensitivity to channel noise. However, because of utilizing the optimal fuzzy clustering process for VQ design, the FCOVQ algorithm can effectively reduce the sensitivity to channel noise while maintaining the quantization accuracy. Therefore, given the same noisy channel, the FCOVQ can have better rate-distortion performance than that of the CCOVQ techniques
Keywords
channel coding; fuzzy systems; image coding; rate distortion theory; vector quantisation; CCOVQ design algorithm; FCOVQ design algorithm; VQ design algorithm; channel noise; codeword training; crisp channel-optimized vector quantization; fuzzy channel-optimized vector quantization; image coding; noisy channels; optimal fuzzy clustering technique; quantization accuracy; rate-distortion performance; vector quantizer design algorithm; Algorithm design and analysis; Clustering algorithms; Cost function; Image coding; Noise reduction; Rate-distortion; Vector quantization;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech, and Signal Processing, 2000. ICASSP '00. Proceedings. 2000 IEEE International Conference on
Conference_Location
Istanbul
ISSN
1520-6149
Print_ISBN
0-7803-6293-4
Type
conf
DOI
10.1109/ICASSP.2000.859198
Filename
859198
Link To Document