Statistical modeling of spatial distortion in hyperspectral calibration
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Published on: February 23, 2017
Edisanter Lo1, Augustus W Fountain, John Ingram
1Department of Mathematical Sciences, Susquehanna University, Selinsgrove, Pennsylvania 17870, USA.
Abstract:
This paper describes a statistically based efficient algorithm for the laboratory spectral calibration of a low-resolution terrestrial hyperspectral imaging camera operating in the visible range. Didymium oxide is used as a wavelength standard. The observed periodic spatial distortion in the wavelength abscissa of the hypercube is removed automatically through statistical modeling and the calibration of the wavelength abscissa is determined using a numerical method. The performance and cost of this algorithm in removing the spatial distortion are assessed quantitatively.
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