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

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish
Article number8610278
Pages (from-to)997-1001
Number of pages5
JournalIEEE Geoscience and Remote Sensing Letters
Volume16
Issue number6
DOIs
Publication statusPublished - 1 Jun 2019
Externally publishedYes

Keywords

  • Detection
  • M-estimators
  • Wishart distribution
  • nonlocal (NL) means
  • polarimetric synthetic aperture radar (PolSAR)

Fingerprint

Dive into the research topics of 'M-NL: Robust NL-Means Approach for PolSAR Images Denoising'. Together they form a unique fingerprint.

Cite this