A speckle model to characterize low backscatter areas and areas with strong scatterers in marine SLC SAR images is presented. The model allows using high resolution speckled SAR images instead of dealing with multi-look SAR images where, at the expense of a poorer spatial resolution, the speckle is mitigated. The new approach is based on the use of the three parameters of the generalized K probability density function. This speckle model embodies the Rayleigh, the Rice and the K-distribution scattering scenes, which are descriptor of scenes dominated by Bragg scattering, scenes in which a dominant scatter is present and scenes with a non-Gaussian signal statistic, respectively. A large data-set of ERS 1/2 SLC SAR images, provided by the ESA under the Project CIP-2769, is employed. Results show the effectiveness of the approach.

A physically consistent stochastic model to observe oil spills and strong scatterers on SLC SAR images

Migliaccio Maurizio;Sorrentino Antonio.
2007-01-01

Abstract

A speckle model to characterize low backscatter areas and areas with strong scatterers in marine SLC SAR images is presented. The model allows using high resolution speckled SAR images instead of dealing with multi-look SAR images where, at the expense of a poorer spatial resolution, the speckle is mitigated. The new approach is based on the use of the three parameters of the generalized K probability density function. This speckle model embodies the Rayleigh, the Rice and the K-distribution scattering scenes, which are descriptor of scenes dominated by Bragg scattering, scenes in which a dominant scatter is present and scenes with a non-Gaussian signal statistic, respectively. A large data-set of ERS 1/2 SLC SAR images, provided by the ESA under the Project CIP-2769, is employed. Results show the effectiveness of the approach.
2007
component
speckle
SAR
sea
generalized K pdf
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/472445
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