Comparing samples from the $${\mathcal {G}}^0$$G0 distribution using a geodesic distance

Alejandro C. Frery () and Juliana Gambini ()
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Alejandro C. Frery: Universidade Federal de Alagoas
Juliana Gambini: Instituto Tecnológico de Buenos Aires

TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, 2020, vol. 29, issue 2, No 6, 359-378

Abstract: Abstract The $${\mathcal {G}}^0$$G0 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 $${\mathcal {G}}^0$$G0 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 $${\mathcal {G}}^0$$G0 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.

Keywords: Geodesic distance; Dissimilarity measure; $${\mathcal {G}}^0$$ G 0 distribution; 62F10 Point estimation, 62F03 Hypothesis testing, 62F40 Bootstrap, jackknife and other resampling methods, 62G32 Statistics of extreme values; tail inference (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/s11749-019-00658-2

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