Multi-chromatic analysis of SAR images for target analysis (Contributo in atti di convegno)

Type
Label
  • Multi-chromatic analysis of SAR images for target analysis (Contributo in atti di convegno) (literal)
Anno
  • 2013-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1117/12.2028962 (literal)
Alternative label
  • Fabio Bovenga a, Dominique Derauw b, Christian Barbier b, Fabio Michele Rana a, Alberto Refice a, Nicola Veneziani a, Raffaele Vitulli c (2013)
    Multi-chromatic analysis of SAR images for target analysis
    in Proc. SPIE, SAR Image Analysis, Modeling, and Techniques XIII, Dresden, Germany, 23-26 Sept. 2013
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Fabio Bovenga a, Dominique Derauw b, Christian Barbier b, Fabio Michele Rana a, Alberto Refice a, Nicola Veneziani a, Raffaele Vitulli c (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • a Reseach National Council of Italy, ISSIA institute, Via Amendola 173, 70126 Bari, Italy. b Centre Spatial de Liège, Avenue du Pré-Aily, Angleur, Belgium. c ESA - ESTEC TEC/EDP, Noordwijk, The Netherlands. (literal)
Titolo
  • Multi-chromatic analysis of SAR images for target analysis (literal)
Abstract
  • Multi-Chromatic Analysis (MCA) of SAR images relays on exploring sub-band images obtained by processing portions of range spectrum located at different frequency positions. It has been applied to interferometric pairs for phase uwrapping and height computation. This work investigates two promising applications: the comparison between the frequency-persistent scatterers (PSfd) and the temporal-persistent scatterers (PS), and the use of inter-band coherence of a single SAR image for vessel detection. The MCA technique introduces the concept of frequency-stable targets, i.e. objects exhibiting stable radar returns across the frequency domain which is complementary to that of temporal stability at the base of PS interferometry. Both spotlight and stripmap TerraSAR-X images acquired on the Venice Lagoon have been processed to identify PSfd and PS. Different populations have been analyzed to evaluate the respective characteristics and the physical nature of PSfd and PS. Concerning the spectral coherence, it is derived by computing the coherence between sub-images of a single SAR acquisition. In the presence of a random distribution of surface scatterers, spectral coherence must be proportional to sub-band intersection of sub-images. This model is fully verified when observing measured spectral coherence on open see areas. If scatterers distribution departs from this distribution, as for manmade structures, spectral coherence is preserved. We investigated the spectral coherence to perform vessel detection on sea background by using spotlight images acquired on Venice Lagoon. Sea background tends to lead to very low spectral coherence while this latter is preserved on the targeted vessels, even for very small ones. A first analysis shows that all vessels observable in intensity images are easily detected in the spectral coherence images which can be used as a complementary information channel to constrain vessel detection. (literal)
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