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Computational Intelligence and Neuroscience
Volume 2013 (2013), Article ID 231916, 8 pages
Research Article

Color Image Quantization Algorithm Based on Self-Adaptive Differential Evolution

1School of Mathematics and Statistic, Hubei Engineering University, Xiaogan, Hubei 432000, China
2School of Sciences, Wuhan University of Technology, Wuhan, Hubei 430070, China

Received 17 March 2013; Accepted 13 June 2013

Academic Editor: Daoqiang Zhang

Copyright © 2013 Qinghua Su and Zhongbo Hu. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Differential evolution algorithm (DE) is one of the novel stochastic optimization methods. It has a better performance in the problem of the color image quantization, but it is difficult to set the parameters of DE for users. This paper proposes a color image quantization algorithm based on self-adaptive DE. In the proposed algorithm, a self-adaptive mechanic is used to automatically adjust the parameters of DE during the evolution, and a mixed mechanic of DE and -means is applied to strengthen the local search. The numerical experimental results, on a set of commonly used test images, show that the proposed algorithm is a practicable quantization method and is more competitive than -means and particle swarm algorithm (PSO) for the color image quantization.