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SAR images are affected by speckle which is a coherent process modelled as a multiplicative noise. It makes the automatic image classification difficult. Thus, many methods have been developed to remove speckle from SAR images while preserving the useful information of the image such as texture. This paper presents an evaluation of texture extraction parameter estimation methods using Cramer-Rao lower...
In this paper we present two algorithms for information extraction from Single Look Complex (SLC) Synthetic Aperture Radar (SAR) images. The first algorithm is based on Tikhonov regularization with Total Variation (TV) and a Point-Based Feature (PBF) term. Based on the equivalence of Tikhonov and the Bayesian estimate, the second algorithm is a Maximum A Posteriori (MAP) estimation with a complex-valued...
The high complexity and the increased importance of geometry in growing resolution synthetic aperture radar (SAR) data in urban environments poses a limit on the usability of lattice-based scene models. Geometrical models based on marked point processes can be employed to provide better descriptions of the scene. A Gibbs potential based on a hierarchical Bayesian description of the direct model of...
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