Region discrimination in SAR imagery using the geodesic distance between GI0 distributions

This paper presents a new method to measure the separability between two different regions in SAR imagery, using the geodesic distance and the G
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distribution. The method can be used in SAR image segmentation, among other applications. It is well known that the G
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distribution is able to characterize different regions in monopolarized SAR imagery. It is indexed by three parameters: the number of looks (which can be estimated in the whole image), a scale parameter and the texture parameter. A formula for the geodesic distance is computed in terms of the texture parameter, which is estimated using Maximum Likelihood. The geodesic distance equation is solved using numerical integration. The new algorithm has been applied to synthetic and real data with promising results.