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Proceedings Paper

Unsupervised change detection in very high spatial resolution COSMO-Skymed SAR images
Author(s): Nicola Acito; Salvatore Resta; Marco Diani; Giovanni Corsini; Alessandro Rossi
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Paper Abstract

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.

Paper Details

Date Published: 21 November 2012
PDF: 9 pages
Proc. SPIE 8536, SAR Image Analysis, Modeling, and Techniques XII, 853602 (21 November 2012); doi: 10.1117/12.974663
Show Author Affiliations
Nicola Acito, Accademia Navale (Italy)
Salvatore Resta, Univ. di Pisa (Italy)
Marco Diani, Univ. di Pisa (Italy)
Giovanni Corsini, Univ. di Pisa (Italy)
Alessandro Rossi, Univ. di Pisa (Italy)

Published in SPIE Proceedings Vol. 8536:
SAR Image Analysis, Modeling, and Techniques XII
Claudia Notarnicola; Simonetta Paloscia; Nazzareno Pierdicca, Editor(s)

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