학술논문

Noise suppression for shape-gain vector quantization by index assignment using ant colony systems
Document Type
Conference
Source
Fourth International Conference on Information, Communications and Signal Processing, 2003 and the Fourth Pacific Rim Conference on Multimedia. Proceedings of the 2003 Joint Information, communications and signal processing and multimedia 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. 1:235-238 Vol.1 2003
Subject
Computing and Processing
Signal Processing and Analysis
Communication, Networking and Broadcast Technologies
Noise shaping
Vector quantization
Image coding
Image quality
Ant colony optimization
Working environment noise
Costs
Error correction codes
Data compression
Shape
Language
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.