A segmentation-based approach to SAR change detection and mapping

Andrea Garzelli; Claudia Zoppetti

doi:10.1117/12.2242565

18 October 2016 A segmentation-based approach to SAR change detection and mapping

Andrea Garzelli, Claudia Zoppetti

Proceedings Volume 10004, Image and Signal Processing for Remote Sensing XXII; 1000410 (2016) https://doi.org/10.1117/12.2242565
Event: SPIE Remote Sensing, 2016, Edinburgh, United Kingdom

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.

Conference Presentation

Citation Download Citation

Andrea Garzelli and Claudia Zoppetti "A segmentation-based approach to SAR change detection and mapping", Proc. SPIE 10004, Image and Signal Processing for Remote Sensing XXII, 1000410 (18 October 2016); https://doi.org/10.1117/12.2242565

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