This paper proposes an approach for freight traffic surveillance by using very high geometrical resolution SAR images. The approach takes advantage of 3 concepts: i) multiscale representation for a preliminary detection of areas showing significant changes in backscattering between the two images (hot spots); ii) exploitation of prior information about typical usage of zones of interest in the area under control; and iii) definition of features and change detectors optimized for an effective detection of specific changes in each zone of interest. In order to illustrate the effectiveness of the proposed approach, two data sets that defines a freight traffic surveillance problem were considered. Each of them is made up of a pair of multitemporal VHR SAR images acquired by the COSMO-SkyMed constellation in spotlight mode. Experimental results point out the effectiveness of the proposed approach. © 2012 IEEE.

Freight traffic surveillance in VHR SAR images by multiscale information extraction

Bovolo, Francesca;Marin, Carlo;Bruzzone, Lorenzo
2012-01-01

Abstract

This paper proposes an approach for freight traffic surveillance by using very high geometrical resolution SAR images. The approach takes advantage of 3 concepts: i) multiscale representation for a preliminary detection of areas showing significant changes in backscattering between the two images (hot spots); ii) exploitation of prior information about typical usage of zones of interest in the area under control; and iii) definition of features and change detectors optimized for an effective detection of specific changes in each zone of interest. In order to illustrate the effectiveness of the proposed approach, two data sets that defines a freight traffic surveillance problem were considered. Each of them is made up of a pair of multitemporal VHR SAR images acquired by the COSMO-SkyMed constellation in spotlight mode. Experimental results point out the effectiveness of the proposed approach. © 2012 IEEE.
2012
2012 Tyrrhenian Workshop on Advances in Radar and Remote Sensing (TyWRRS)
Usa
ACM/IEEE
9781467324427
9781467324434
Bovolo, Francesca; Marin, Carlo; Bruzzone, Lorenzo
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/34483
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