M-estimators of roughness and scale for \({\mathcal G}_A^0\)-modelled SAR imagery
type: Item
instance of: scholarly article
title: M-estimators of roughness and scale for \({\mathcal G}_A^0\)-modelled SAR imagery
zbMATH Open document ID: 0995.68174
DOI: 10.1155/S1110865702000392
author: María Magdalena Lucini
author: Alejandro C. Frery
author: Oscar Bustos
published in: EURASIP Journal on Applied Signal Processing
publication date: 2002-05-15T00:00:00Z
review text: Summary: The \({\mathcal G}^0_A\) distribution is assumed as the universal model for multilook amplitude SAR imagery data under the multiplicative model. This distribution has two unknown parameters related to the roughness and the scale of the signal, that can be used in image analysis and processing. It can be seen that maximum likelihood and moment estimators for its parameters can be influenced by small percentages of ``outliers''; hence, it is of outmost importance to find robust estimators for these parameters. One of the best-known classes of robust techniques is that of M-estimators, which are an extension of the maximum likelihood estimation method. In this work we derive the M-estimators for the parameters of the \({\mathcal G}^0_A\) distribution, and compare them with maximum likelihood estimators with a Monte-Carlo experience. It is checked that this robust technique is superior to the classical approach under the presence of corner reflectors, a common source of contamination in SAR images. Numerical issues are addressed, and a practical example is provided.
Mathematics Subject Classification ID: 68U10
zbMATH DE Number: 1742292
zbMATH Keywords: M-estimators
zbMATH Keywords: multilook amplitude SAR imagery
zbMATH Keywords: maximum likelihood
MaRDI profile type: Publication
full work available at URL: s1110865702000392
OpenAlex ID: W1994548278
description: scientific article; zbMATH DE number 1742292