Open Access

M-Estimators of Roughness and Scale for https://static-content.springer.com/image/art%3A10.1155%2FS1110865702000392/MediaObjects/13634_2001_Article_823_IEq1_HTML.gif -Modelled SAR Imagery

  • Oscar H. Bustos1Email author,
  • MaríaMagdalena Lucini1 and
  • Alejandro C. Frery2
EURASIP Journal on Advances in Signal Processing20022002:297349

DOI: 10.1155/S1110865702000392

Received: 31 July 2001

Published: 14 January 2002

Abstract

The GA0 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 https://static-content.springer.com/image/art%3A10.1155%2FS1110865702000392/MediaObjects/13634_2001_Article_823_IEq2_HTML.gif 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.

Keywords

inference likelihood M-estimators Monte-Carlo method multiplicative model speckle synthetic aperture radar robustness

Authors’ Affiliations

(1)
Facultad de Matemática, Astronomía y Física, Universidad Nacional de Córdoba, Ciudad Universitaria
(2)
Centro de Informática, Universidade Federal de Pernambuco

Copyright

© Bustos et al. 2002