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Proceedings Paper

Atmospheric radiance interpolation for the modeling of hyperspectral data
Author(s): Perry Fuehrer; Glenn Healey; Brian Rauch; David Slater; Anthony Ratkowski
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Paper Abstract

The calibration of data from hyperspectral sensors to spectral radiance enables the use of physical models to predict measured spectra. Since environmental conditions are often unknown, material detection algorithms have emerged that utilize predicted spectra over ranges of environmental conditions. The predicted spectra are typically generated by a radiative transfer (RT) code such as MODTRANTM. Such techniques require the specification of a set of environmental conditions. This is particularly challenging in the LWIR for which temperature and atmospheric constituent profiles are required as inputs for the RT codes. We have developed an automated method for generating environmental conditions to obtain a desired sampling of spectra in the sensor radiance domain. Our method provides a way of eliminating the usual problems encountered, because sensor radiance spectra depend nonlinearly on the environmental parameters, when model conditions are specified by a uniform sampling of environmental parameters. It uses an initial set of radiance vectors concatenated over a set of conditions to define the mapping from environmental conditions to sensor spectral radiance. This approach enables a given number of model conditions to span the space of desired radiance spectra and improves both the accuracy and efficiency of detection algorithms that rely upon use of predicted spectra.

Paper Details

Date Published: 15 April 2008
PDF: 12 pages
Proc. SPIE 6966, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIV, 69661O (15 April 2008); doi: 10.1117/12.778393
Show Author Affiliations
Perry Fuehrer, HyperTech Systems (United States)
Glenn Healey, HyperTech Systems (United States)
Brian Rauch, HyperTech Systems (United States)
David Slater, HyperTech Systems (United States)
Anthony Ratkowski, Air Force Research Lab. (United States)

Published in SPIE Proceedings Vol. 6966:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIV
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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