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Proceedings Paper

Sparse representation-based spectral clustering for SAR image segmentation
Author(s): Xiangrong Zhang; Zhengli Wei; Jie Feng; Licheng Jiao
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Paper Abstract

A new method, sparse representation based spectral clustering (SC) with Nyström method, is proposed for synthetic aperture radar (SAR) image segmentation. Different from the conventional SC, this proposed technique is developed by using the sparse coefficients which obtained by solving l1 minimization problem to construct the affinity matrix and the Nyström method is applied to alleviate the segmentation process. The advantage of our proposed method is that we do not need to select the scaling parameter in the Gaussian kernel function artificially. We apply the proposed method, k-means and the classic spectral clustering algorithm with Nyström method to SAR image segmentation. The results show that compared with the other two methods, the proposed method can obtain much better segmentation results.

Paper Details

Date Published: 23 November 2011
PDF: 6 pages
Proc. SPIE 8006, MIPPR 2011: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications, 800608 (23 November 2011); doi: 10.1117/12.901531
Show Author Affiliations
Xiangrong Zhang, Xidian Univ. (China)
Zhengli Wei, Xidian Univ. (China)
Jie Feng, Xidian Univ. (China)
Licheng Jiao, Xidian Univ. (China)


Published in SPIE Proceedings Vol. 8006:
MIPPR 2011: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications
Faxiong Zhang; Faxiong Zhang, Editor(s)

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