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Article Dans Une Revue IEEE Journal of Selected Topics in Signal Processing Année : 2011

Displacement Estimation by Maximum Likelihood Texture Tracking

Résumé

This paper presents a novel method to estimate displacement by maximum-likelihood (ML) texture tracking. The observed polarimetric synthetic aperture radar (PolSAR) data-set is composed by two terms: the scalar texture parameter and the speckle component. Based on the Spherically Invariant Random Vectors (SIRV) theory, the ML estimator of the texture is computed. A generalization of the ML texture tracking based on the Fisher probability density function (pdf) modeling is introduced. For random variables with Fisher distributions, the ratio distribution is established. The proposed method is tested with both simulated PolSAR data and spaceborne PolSAR images provided by the TerraSAR-X (TSX) and the RADARSAT-2 (RS-2) sensors.
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Dates et versions

hal-00638868 , version 1 (07-11-2011)

Identifiants

Citer

Olivier Harant, Lionel Bombrun, Gabriel Vasile, Laurent Ferro-Famil, Michel Gay. Displacement Estimation by Maximum Likelihood Texture Tracking. IEEE Journal of Selected Topics in Signal Processing, 2011, 5 (3), pp.567-576. ⟨10.1109/JSTSP.2010.2100365⟩. ⟨hal-00638868⟩
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