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

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.

Journal

Title: Journal of Radars

Publisher: Chinese Academy of Sciences

Publication date (Electronic): 01 October 2015

Volume: 4

Issue: 5

Pages: 582-590

Affiliations

[1 ] School of Electronic Information, Wuhan University

[2 ] Radar Research Institute, Inner Mongolia University of Technology

Article

Doaj ID: 3db89d5968714c67903011d6ba1ab002

DOI: 10.12000/JR15073

License:

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/

Product

Self URI: http://radars.ie.ac.cn/CN/html/R15073.htm

Self URI (journal page): http://radars.ie.ac.cn/EN/volumn/home.shtml

Categories

Subject: Technology (General)

Subject: T1-995