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M-NL: Robust NL-Means Approach for PolSAR Images Denoising

  • L2S, CNRS, Univ Paris-Sud
  • Université Paris-Saclay

Résultats de recherche: Contribution à un journalArticleRevue par des pairs

Résumé

This letter proposes a new method for polarimetric synthetic aperture radar (PolSAR) denoising. More precisely, it seeks to address a new statistical approach for weights computation in nonlocal (NL) approaches. The aim is to present a simple criterion using M -estimators and to detect similar pixels in an image. A binary hypothesis test is used to select similar pixels which will be used for covariance matrix estimation together with associated weights. The method is then compared with an advanced state-of-the-art PolSAR denoising method named NL-SAR. The filter performances are measured by a set of different indicators, including relative errors on incoherent target decomposition parameters, coherences, polarimetric signatures, and edge preservation on a set of simulated PolSAR images. Finally, results for RADARSAT-2 PolSAR data are presented.

langue originaleAnglais
Numéro d'article8610278
Pages (de - à)997-1001
Nombre de pages5
journalIEEE Geoscience and Remote Sensing Letters
Volume16
Numéro de publication6
Les DOIs
étatPublié - 1 juin 2019
Modification externeOui

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