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Novel Change Detection in SAR Imagery Using Local Connectivity

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5 Author(s)
Wan, H. L. ; The Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi'an, China ; Jung, C. ; Hou, B. ; Wang, G. T.
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Most change-detection techniques in synthetic aperture radar (SAR) imagery are based on the analysis of the difference image with a pixel-level decision approach. However, the pixel-level decision approach would cause a noisy change-detection map, with holes in connected regions and jagged boundaries. In this letter, we propose a novel change-detection method to deal with the problem of the pixel-level decision approach by considering local connectivity. We first get an initial change-detection result with an improved Gustafson–Kessel clustering algorithm using local spatial information and then refine the initial result through region-of-interest extraction and consideration of local connectivity of changed areas. Experimental results on real SAR image data sets demonstrate that the proposed method outperforms the related ones for change detection.

Published in:

Geoscience and Remote Sensing Letters, IEEE  (Volume:10 ,  Issue: 1 )