Color image quantization algorithm based on self-adaptive differential Evolution

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Abstract

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 K -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 K -means and particle swarm algorithm (PSO) for the color image quantization. © 2013 Qinghua Su and Zhongbo Hu.

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Su, Q., & Hu, Z. (2013). Color image quantization algorithm based on self-adaptive differential Evolution. Computational Intelligence and Neuroscience, 2013. https://doi.org/10.1155/2013/231916

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