Paper
13 June 2014 Long-wave infrared surface reflectance spectra retrieved from Telops Hyper-Cam imagery
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Abstract
Processing long-wave infrared (LWIR) hyperspectral imagery to surface emissivity or reflectance units via atmospheric compensation and temperature-emissivity separation (TES) affords the opportunity to remotely classify and identify solid materials with minimal interference from atmospheric effects. This paper describes an automated atmospheric compensation and TES method, called FLAASH®-IR (Fast Line-of-sight Atmospheric Analysis of Spectral Hypecubes-- Infrared), and its application to ground-to-ground imagery taken with the Telops Inc. Hyper-Cam interferometric hyperspectral imager. The results demonstrate that clean, quantitative surface spectra can be obtained, even with highly reflective (low emissivity) objects such as bare metal and in the presence of some illumination from the surroundings. In particular, the atmospheric compensation process suppresses the spectral features due to atmospheric water vapor and ozone, which are especially prominent in reflected sky radiance.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
S. M. Adler-Golden, P. Conforti, M. Gagnon, P. Tremblay, and Martin Chamberland "Long-wave infrared surface reflectance spectra retrieved from Telops Hyper-Cam imagery", Proc. SPIE 9088, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XX, 90880U (13 June 2014); https://doi.org/10.1117/12.2050446
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Cited by 20 scholarly publications.
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KEYWORDS
Reflectivity

Atmospheric modeling

Long wavelength infrared

Infrared imaging

Infrared radiation

Sensors

Algorithm development

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