$M$ -NL: Robust NL-Means Approach for PolSAR Images Denoising - CentraleSupélec Access content directly
Journal Articles IEEE Geoscience and Remote Sensing Letters Year : 2019

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

Abstract

This paper 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 non-local (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 to an advanced state of the art PolSAR denoising method, NL-SAR method [1]. 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, as in [2]. Finally, results for RADARSAT-2 PolSAR data are presented.
Fichier principal
Vignette du fichier
final_version.pdf (9.34 Mo) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-02186186 , version 1 (29-02-2020)

Identifiers

Cite

Gordana Draskovic, Frédéric Pascal, Florence Tupin. $M$ -NL: Robust NL-Means Approach for PolSAR Images Denoising. IEEE Geoscience and Remote Sensing Letters, 2019, 16 (6), pp.997-1001. ⟨10.1109/LGRS.2018.2889275⟩. ⟨hal-02186186⟩
102 View
139 Download

Altmetric

Share

Gmail Facebook X LinkedIn More