Change detection in SAR images using structure similarity and parametric kernel graph cuts

Xiongmei Zhang; Zhaoxiang Yi; Mei Yang; Lianfeng Wang

doi:10.1117/12.2282049

21 July 2017 Change detection in SAR images using structure similarity and parametric kernel graph cuts

Xiongmei Zhang, Zhaoxiang Yi, Mei Yang, Lianfeng Wang

Proceedings Volume 10420, Ninth International Conference on Digital Image Processing (ICDIP 2017); 104201B (2017) https://doi.org/10.1117/12.2282049
Event: Ninth International Conference on Digital Image Processing (ICDIP 2017), 2017, Hong Kong, China

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.

Citation Download Citation

Xiongmei Zhang, Zhaoxiang Yi, Mei Yang, and Lianfeng Wang "Change detection in SAR images using structure similarity and parametric kernel graph cuts", Proc. SPIE 10420, Ninth International Conference on Digital Image Processing (ICDIP 2017), 104201B (21 July 2017); https://doi.org/10.1117/12.2282049

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