Comparing Samples from the G^0 Distribution using a Geodesic Distance
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The G^0 distribution is widely used for monopolarized SAR image modeling because it can characterize regions with different degree of texture accurately. It is indexed by three parameters: the number of looks (which can be estimated for the whole image), a scale parameter and a texture parameter. This paper presents a new proposal for comparing samples from the G^0 distribution using a Geodesic Distance (GD) as a measure of dissimilarity between models. The objective is quantifying the difference between pairs of samples from SAR data using both local parameters (scale and texture) of the G^0 distribution. We propose three tests based on the GD which combine the tests presented in GeodesicDistanceGI0JSTARS, and we estimate their probability distributions using permutation methods.
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