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      Change Detection of High Resolution SAR Images by the Fusion of Coherent/Incoherent Information

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          Abstract

          Aiming at detecting the change regions of high resolution Synthetic Aperture Radar (SAR) images, we propose to use the Dempster-Shafer (D-S) evidence theory to fuse coherent/incoherent features from sensors that form an integral part of the system. First, we use the Simple Linear Iterative Clustering (SLIC) segmentation algorithm to implement multi-scale joint segmentation for multi-temporal SAR images. Second, we extract multiple intensity and coherence difference features on each segment level by SLIC using mean operator to complete the fusion of multi-scale features to get the multi-feature difference mapped by a ratio operator. Finally, we fuse the multi-feature difference maps to get the final change detection result using the D-S evidence theory. The experimental results in our study prove the effectiveness of our proposed computational algorithm.

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          Author and article information

          Journal
          Journal of Radars
          Chinese Academy of Sciences
          01 October 2015
          : 4
          : 5
          : 582-590
          Affiliations
          [1 ] School of Electronic Information, Wuhan University
          [2 ] Radar Research Institute, Inner Mongolia University of Technology
          Article
          3db89d5968714c67903011d6ba1ab002
          10.12000/JR15073

          This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

          Categories
          Technology (General)
          T1-995

          Remote sensing, Electrical engineering

          High resolution SAR, Fusion, Evidence theory, Change detection

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