A effective immune multi-objective algorithm for SAR imagery segmentation

Dongdong Yang; Licheng Jiao; Maoguo Gong; Xiaoyun Si

doi:10.1117/12.832363

30 October 2009 A effective immune multi-objective algorithm for SAR imagery segmentation

Dongdong Yang, Licheng Jiao, Maoguo Gong, Xiaoyun Si

Proceedings Volume 7494, MIPPR 2009: Multispectral Image Acquisition and Processing; 74942B (2009) https://doi.org/10.1117/12.832363
Event: Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, 2009, Yichang, China

Abstract

A novel and effective immune multi-objective clustering algorithm (IMCA) is presented in this study. Two conflicting and complementary objectives, called compactness and connectedness of clusters, are employed as optimization targets. Besides, adaptive ranks clone, variable length chromosome crossover operation and k-nearest neighboring list based diversity holding strategies are featured by the algorithm. IMCA could automatically discover the right number of clusters with large probability. Seven complicated artificial data sets and two widely used synthetic aperture radar (SAR) imageries are used for test IMCA. Compared with FCM and VGA, IMCA has obtained good and encouraging clustering results. We believe that IMCA is an effective algorithm for solving these nine problems, which should deserve further research.

Citation Download Citation

Dongdong Yang, Licheng Jiao, Maoguo Gong, and Xiaoyun Si "A effective immune multi-objective algorithm for SAR imagery segmentation", Proc. SPIE 7494, MIPPR 2009: Multispectral Image Acquisition and Processing, 74942B (30 October 2009); https://doi.org/10.1117/12.832363

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