Self-adaptive evolutionary algorithm for multispectral remote sensing image clustering

Dongxia Chang; Xianda Zhang

doi:10.1117/12.749691

15 November 2007 Self-adaptive evolutionary algorithm for multispectral remote sensing image clustering

Dongxia Chang, Xianda Zhang

Proceedings Volume 6787, MIPPR 2007: Multispectral Image Processing; 678702 (2007) https://doi.org/10.1117/12.749691
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

Abstract

In this paper, a self-adaptive evolutionary clustering algorithm is presented. This algorithm uses the evolutionary programming (EP) to search the optimal clustering and bases on the principles of the K-means algorithm. The proposed self-adaptive evolutionary (SAEP) clustering algorithm self-adapts the vector of the step size appropriate for each parent. This is different from other genetic-based algorithms. The algorithm can minimize the degeneracy in the evolutionary process. The experimental results show that the KSAE clustering algorithm is efficient in the unsupervised classification of the multispectral remote sensing image.

Citation Download Citation

Dongxia Chang and Xianda Zhang "Self-adaptive evolutionary algorithm for multispectral remote sensing image clustering", Proc. SPIE 6787, MIPPR 2007: Multispectral Image Processing, 678702 (15 November 2007); https://doi.org/10.1117/12.749691

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