EURASIP Journal on Applied Signal Processing 
Volume 2002 (2002), Issue 1, Pages 105-114
doi:10.1155/S1110865702000392

M-Estimators of Roughness and Scale for 𝒢A 0-Modelled SAR Imagery

Oscar H. Bustos,1 María Magdalena Lucini,1 and Alejandro C. Frery2

 1Facultad de Matemática, Astronomía y Física, Universidad Nacional de Córdoba, Ciudad Universitaria, Córdoba 5000, Argentina
2Centro de Informática, Universidade Federal de Pernambuco, CP 7851, Recife 50732-970, PE, Brazil
Received 31 July 2001; Revised 10 October 2001

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 𝒢A 0 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.