¹School of Sciences, Wuhan University of Technology, Wuhan 430070, Hubei, China
²School of Public Administration, China University of Geosciences, Wuhan 430074, Hubei, China

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Abstract—Some stochastic optimization methods, such as Particle Swarm Optimization Algorithms (PSO) and Genetic Algorithms (GA), have been used to solve the color image quantization. Differential Evolution Algorithm (DE) is one of the powerful stochastic optimization methods. Few researches have been done for using DE to solve the color image quantization. This paper proposes a DE-based color image quantization algorithm. In the proposed algorithm, a better colormap is designed by using DE to update some randomly initialized candidate colormaps. Numerical experiments are conducted on a set of commonly used test images. The experimental results show that the proposed algorithm is practicable, and it has better performance than the color image quantization algorithm using PSO.

Index Terms—Color Image Quantization, Differential Evolution, Particle Swarm Optimization.

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Cite: Qinghua Su, Sidian Guo, Zhangcan Huang, Zhongbo Hu, "Color Image Quantization Algorithm Based on Differential Evolution," Journal of Software vol. 8, no. 12, pp. 3035-3041, 2013.