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Communication Dans Un Congrès Année : 2009

Segmentation and Classification of Polarimetric SAR Data based on the KummerU Distribution

Résumé

Thinner spatial features can be observed from the high resolution of newly available spaceborne and airborne SAR images. Heterogeneous clutter models should be used to model the covariance matrix because each resolution cell contains only a small number of scatterers. In this paper, we focus on the use of a Fisher probability density function (pdf) to model the SAR clutter. First, the benefit of using such a pdf is exposed. Covariance matrix statistics are then analyzed in details. For a Fisher distributed texture, the covariance matrix follows a KummerU pdf. Asymptotic cases of this pdf are presented. Finally, the KummerU pdf is implemented in both hierarchical segmentation and classification algorithms. Segmentation and classification results are shown on both synthetic and real data.
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Dates et versions

hal-00371281 , version 1 (27-03-2009)

Identifiants

  • HAL Id : hal-00371281 , version 1

Citer

Olivier Harant, Lionel Bombrun, Michel Gay, Renaud Fallourd, Emmanuel Trouvé, et al.. Segmentation and Classification of Polarimetric SAR Data based on the KummerU Distribution. POLinSAR 2009 - 4th International Workshop on Science and Applications of SAR Polarimetry and Polarimetric Interferometry, Jan 2009, Frascati, Italy. pp.6. ⟨hal-00371281⟩
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