DocumentCode :
409842
Title :
Noise suppression for shape-gain vector quantization by index assignment using ant colony systems
Author :
Shieh, C.S. ; Pan, J.S. ; Su, C.J. ; Laio, B.Y.
Author_Institution :
Dept. of Electron. Eng., Kaohsiung Univ. of Appl. Sci., Taiwan
Volume :
1
fYear :
2003
fDate :
15-18 Dec. 2003
Firstpage :
235
Abstract :
A pioneer work on index assignment using ant colony systems for shape-gain vector quantization is presented in this paper. SGVQ, descended from VQ, is well recognized as a highly efficient compression method, with which encoding speed is greatly improved without serious degradation in image quality. Our work focuses on the transmission of indices in noisy environment. In order to minimize the impact of channel noise, we use ant colony systems to find out a suitable index assignment. With our approach, channel distortion can be substantially reduced without incurring extra cost such as that in error-detection code and error-correction code.
Keywords :
cooperative systems; error correction codes; error detection codes; image coding; image denoising; vector quantisation; ant colony systems; channel distortion; error-correction code; error-detection code; image quality; index assignment; noise suppression; shape-gain vector quantization; Ant colony optimization; Costs; Data compression; Error correction codes; Image coding; Image quality; Noise shaping; Shape; Vector quantization; Working environment noise;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information, Communications and Signal Processing, 2003 and Fourth Pacific Rim Conference on Multimedia. Proceedings of the 2003 Joint Conference of the Fourth International Conference on
Print_ISBN :
0-7803-8185-8
Type :
conf
DOI :
10.1109/ICICS.2003.1292450
Filename :
1292450
Link To Document :
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