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21 November 2012 Unsupervised change detection in very high spatial resolution COSMO-Skymed SAR images
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In this work we propose two pixel-wise change detection techniques for unsupervised network infrastructure monitoring in SAR imagery applications. The first algorithm is inspired by a well known algorithm, named RX, proposed to deal with anomaly detection in optical images. The second algorithm is a statistical based procedure, which exploits a nonparametric approach for estimating the probability density function of the image pair. In order to test and validate the proposed methods, we analyze a spot light amplitude COSMO-SkyMed image pair at one-meter spatial resolution acquired on a complex urban scenario. Experimental results obtained on the available dataset are presented and discussed.
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Nicola Acito, Salvatore Resta, Marco Diani, Giovanni Corsini, and Alessandro Rossi "Unsupervised change detection in very high spatial resolution COSMO-Skymed SAR images", Proc. SPIE 8536, SAR Image Analysis, Modeling, and Techniques XII, 853602 (21 November 2012);

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