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