Abstract:In this manuscript we investigate on the statistical
modeling of hyper-spectral data. Accurately modeling real data is
of paramount importance in the design of optimal classification
or detection strategies and in evaluating their performances. In
the work three non-Gaussian models are considered and their
capability in characterizing the statistical behavior of real data is
discussed with reference to a data set acquired by the
Multispectral Infrared and Visible Imaging Spectrometer
(MIVIS) sensor
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