Volume 4 Issue 5
Nov.  2015
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Article Navigation >  Journal of Radars  > 2015  >  4(5): 582-590
Yang Xiang-li, Xu De-wei, Huang Ping-ping, Yang Wen. Change Detection of High Resolution SAR Images by the Fusion of Coherent/Incoherent Information[J]. Journal of Radars, 2015, 4(5): 582-590. doi: 10.12000/JR15073
Citation: Yang Xiang-li, Xu De-wei, Huang Ping-ping, Yang Wen. Change Detection of High Resolution SAR Images by the Fusion of Coherent/Incoherent Information[J]. Journal of Radars, 2015, 4(5): 582-590. doi: 10.12000/JR15073
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Change Detection of High Resolution SAR Images by the Fusion of Coherent/Incoherent Information

DOI: 10.12000/JR15073
  • 1.

    (School of Electronic Information, Wuhan University, Wuhan 430072, China)

  • 2.

    (Radar Research Institute, Inner Mongolia University of Technology, Hohhot 010051, China)

Funds:

The National Natural Sciences Foundation of China (61271401, 61461040), and the Program for Young Talents of Science and Technology in Universities of Inner Mongolia Autonomous Region (NJYT-14-B09)

  • Received Date: 2015-06-10
  • Rev Recd Date: 2015-08-21
  • Publish Date: 2015-10-28
    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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