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.
Hyper-spectral data modelling by non-Gaussian statistical distributions
Acito N;CORSINI, GIOVANNI;DIANI, MARCO
2004-01-01
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.File in questo prodotto:
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