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 :
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