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Proceedings Paper

A novel SAR fusion image segmentation method based on triplet Markov field
Author(s): Jiajing Wang; Shuhong Jiao; Zhenyu Sun
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Paper Abstract

Markov random field (MRF) has been widely used in SAR image segmentation because of the advantage of directly modeling the posterior distribution and suppresses the speckle on the influence of the segmentation result. However, when the real SAR images are nonstationary images, the unsupervised segmentation results by MRF can be poor. The recent proposed triplet Markov field (TMF) model is well appropriate for nonstationary SAR image processing due to the introduction of an auxiliary field which reflects the nonstationarity. In addition, on account of the texture features of SAR image, a fusion image segmentation method is proposed by fusing the gray level image and texture feature image. The effectiveness of the proposed method in this paper is demonstrated by a synthesis SAR image and the real SAR images segmentation experiments, and it is better than the state-of-art methods.

Paper Details

Date Published: 4 March 2015
PDF: 5 pages
Proc. SPIE 9443, Sixth International Conference on Graphic and Image Processing (ICGIP 2014), 944310 (4 March 2015); doi: 10.1117/12.2178776
Show Author Affiliations
Jiajing Wang, Harbin Engineering Univ. (China)
92677 Unit PLA (China)
Shuhong Jiao, Harbin Engineering Univ. (China)
Zhenyu Sun, Unit 91550 PLA (China)

Published in SPIE Proceedings Vol. 9443:
Sixth International Conference on Graphic and Image Processing (ICGIP 2014)
Yulin Wang; Xudong Jiang; David Zhang, Editor(s)

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