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Change detection in SAR images using structure similarity and parametric kernel graph cuts
Author(s): Xiongmei Zhang; Zhaoxiang Yi; Mei Yang; Lianfeng Wang
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Paper Abstract

In this paper, a novel approach to change detection in synthetic aperture radar (SAR) images based on structure similarity (SSIM) and parametric kernel graph cuts is presented. Firstly, the SSIM is imported into change detection and a difference image constructed method based on SSIM is proposed. And then, the changed and unchanged pixels are identified from the difference image by the parametric kernel graph cuts algorithm. Experimental results obtained on real SAR images demonstrate the effectiveness of the proposed method.

Paper Details

Date Published: 21 July 2017
PDF: 5 pages
Proc. SPIE 10420, Ninth International Conference on Digital Image Processing (ICDIP 2017), 104201B (21 July 2017); doi: 10.1117/12.2282049
Show Author Affiliations
Xiongmei Zhang, Xi’an Research Institute of High Technology (China)
Zhaoxiang Yi, Xi'an Research Institute of High Technology (China)
Mei Yang, Army 96616 (China)
Lianfeng Wang, Xi'an Research Institute of High Technology (China)


Published in SPIE Proceedings Vol. 10420:
Ninth International Conference on Digital Image Processing (ICDIP 2017)
Charles M. Falco; Xudong Jiang, Editor(s)

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