Abstract

In this work we analyze a SAR (Synthetic Aperture Radar) region discrimination method based on the Geodesic Distance (GD) and the estimation of the parameters of a statistical model largely used for this kind of data. The statistical model used is the G0I distribution which is indexed by three parameters: the number of 1% Nominal level looks (L), a scale parameter, and a parameter related to the roughness or texture of the backscatter. This fact is one of there asons why the estimation of  receives a great deal of attention in the literature. This paper presents a new method to measure the separability between regions in SAR imagery using the geodesic distance presented by Rao in [?, ?] under the G0I distribution. In order to asses the performance of the texture discrimination method, a hypothesis test is used. We derived closed form for the GD between models that describe several practical situations, assuming the number of looks known, for same and different texture and for same and different scale [?]. The parameters, in each case, are estimated using the Maximum Likelihood method because we are specially interested in its asymptotic properties [?]