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Proceedings Paper

A segmentation-based approach to SAR change detection and mapping
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Paper Abstract

The potentials of SAR sensors in change detection applications have been recently strengthened by the high spatial resolution and the short revisit time provided by the new generation SAR-based missions, such as COSMO- SkyMed, TerraSAR-X, and RadarSat 3. Classical pixel-based change detection methods exploit first-order statistics variations in multitemporal acquisitions. Higher-order statistics may improve the reliability of the results, while plain object-based change detection are rarely applied to SAR images due to the low signal-to-noise ratio which characterizes 1-look VHR SAR image products. The paper presents a hybrid approach considering both a pixel-based selection of likely-changed pixels and a segmentation-driven step based on the assumption that structural changes correspond to some clusters in a multiscale amplitude/texture representation. Experiments on simulated and true SAR image pairs demonstrate the advantages of the proposed approach.

Paper Details

Date Published: 18 October 2016
PDF: 10 pages
Proc. SPIE 10004, Image and Signal Processing for Remote Sensing XXII, 1000410 (18 October 2016); doi: 10.1117/12.2242565
Show Author Affiliations
Andrea Garzelli, Univ. degli Studi di Siena (Italy)
Claudia Zoppetti, Univ. degli Studi di Siena (Italy)

Published in SPIE Proceedings Vol. 10004:
Image and Signal Processing for Remote Sensing XXII
Lorenzo Bruzzone; Francesca Bovolo, Editor(s)

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