Presentation + Paper
18 October 2016 A segmentation-based approach to SAR change detection and mapping
Author Affiliations +
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
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
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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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Synthetic aperture radar

Image segmentation

Feature extraction

Device simulation

Computer simulations

Detection and tracking algorithms

Lawrencium

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