Robust estimation of roughness parameter in SAR amplitude images

The precise knowledge of the statistical properties of
synthetic aperture radar (SAR) data plays a central role in image
processing and understanding. These properties can be used for
discriminating types of land uses and to develop specialized filters
for speckle noise reduction, among other applications. In this work
we assume the distribution G0
A as the universal model for multilook
amplitude SAR images under the multiplicative model. We study some
important properties of this distribution and some classical estimators
for its parameters, such as Maximum Likelihood (ML) estimators, but
they can be highly influenced by small percentages of ‘outliers’, i.e.,
observations that do not fully obey the basic assumptions. Hence, it is
important to find Robust Estimators. One of the best known classes of
robust techniques is that of M estimators, which are an extension of the
ML estimation method. We compare those estimation procedures by
means of a Monte Carlo experiment.