A novel hierarchical approach to change detection with very high resolution SAR images for surveillance applications

This paper proposes an approach to change detection in multitemporal very high geometrical resolution (VHR) SAR images for surveillance applications. 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. Here the proposed approach is designed for the solution of surveillance problems. A data set made up of a pair of multitemporal VHR SAR images acquired by the COSMO-SkyMed (CSK
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) constellation in spotlight mode on the commercial port of Livorno (Italy) was used. Experimental results point out the effectiveness of the proposed approach.