© 2019, Sociedad de Estadística e Investigación Operativa. The G distribution is widely used for monopolarized SAR image modeling because it can characterize regions with different degrees 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 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 distribution. We propose three tests based on the GD which combine the tests presented in Naranjo-Torres et al. (IEEE J Sel Top Appl Earth Obs Remote Sens 10(3):987–997, 2017), and we estimate their probability distributions using permutation methods.
A Generalized Gaussian Extension to the Rician Distribution for SAR Image Modeling
