期刊
COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE
卷 2013, 期 -, 页码 -出版社
HINDAWI LTD
DOI: 10.1155/2013/231916
关键词
-
资金
- National Natural Science Foundation of China [61070009]
- Fundamental Research Funds for the Central Universities [2012-YB-19]
- Nature Science Foundation of Hubei, China [2011CDC161]
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.
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