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Proceedings Paper

A effective immune multi-objective algorithm for SAR imagery segmentation
Author(s): Dongdong Yang; Licheng Jiao; Maoguo Gong; Xiaoyun Si
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Paper 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.

Paper Details

Date Published: 30 October 2009
PDF: 8 pages
Proc. SPIE 7494, MIPPR 2009: Multispectral Image Acquisition and Processing, 74942B (30 October 2009); doi: 10.1117/12.832363
Show Author Affiliations
Dongdong Yang, Xidian Univ. (China)
Licheng Jiao, Xidian Univ. (China)
Maoguo Gong, Xidian Univ. (China)
Xiaoyun Si, Xidian Univ. (China)

Published in SPIE Proceedings Vol. 7494:
MIPPR 2009: Multispectral Image Acquisition and Processing
Faxiong Zhang; Faxiong Zhang, Editor(s)

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