Efficient vector quantization using genetic algorithm

Hongwei Sun; Kwok Yan Lam; Siu Leung Chung; Weiming Dong; Ming Gu; Jiaguang Sun

doi:10.1007/s00521-004-0455-7

Efficient vector quantization using genetic algorithm

Hongwei Sun, Kwok Yan Lam, Siu Leung Chung, Weiming Dong, Ming Gu, Jiaguang Sun

Hong Kong Metropolitan University

Research output: Contribution to journal › Article › peer-review

24 Citations (Scopus)

Abstract

This paper proposes a new codebook generation algorithm for image data compression using a combined scheme of principal component analysis (PCA) and genetic algorithm (GA). The combined scheme makes full use of the near global optimal searching ability of GA and the computation complexity reduction of PCA to compute the codebook. The experimental results show that our algorithm outperforms the popular LBG algorithm in terms of computational efficiency and image compression performance.

Original language	English
Pages (from-to)	203-211
Number of pages	9
Journal	Neural Computing and Applications
Volume	14
Issue number	3
DOIs	https://doi.org/10.1007/s00521-004-0455-7
Publication status	Published - Sept 2005

Keywords

Genetic algorithm
Image compression
Principal component analysis
Vector quantization

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10.1007/s00521-004-0455-7

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AB - This paper proposes a new codebook generation algorithm for image data compression using a combined scheme of principal component analysis (PCA) and genetic algorithm (GA). The combined scheme makes full use of the near global optimal searching ability of GA and the computation complexity reduction of PCA to compute the codebook. The experimental results show that our algorithm outperforms the popular LBG algorithm in terms of computational efficiency and image compression performance.

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Efficient vector quantization using genetic algorithm

Abstract

Keywords

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