A metrological spectral difference space for the statistical modelling of hyperspectral images
Chapter
Accepted version
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Åpne
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https://hdl.handle.net/11250/2648956Utgivelsesdato
2019Metadata
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Originalversjon
http://dx.doi.org/10.1109/IGARSS.2019.8898666Sammendrag
Answering to metrological constraints typically required in the context of industrial and medical applications, a spectral difference space is introduced in this work. In this space, an acquired hyperspectral data is treated as measurements. Then, modelling the spectral difference space as multivariate Normal laws, a Gaussian mixture model is used in a classification task of remote sensing images. An encouraging result is obtained, comparing the proposed space with a data-driven one. Moreover, it offers a starting point in developing a directly interpretable spectral analysis tools.