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Proceedings Paper

Estimating index of refraction for material identification in comparison to existing temperature emissivity separation algorithms
Author(s): Jacob A. Martin; Kevin C. Gross
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Paper Abstract

As off-nadir viewing platforms become increasingly prevalent in remote sensing, material identification techniques must be robust to changing viewing geometries. Current identification strategies generally rely on estimating reflectivity or emissivity, both of which vary with viewing angle. Presented here is a technique, leveraging polarimetric and hyperspectral imaging (P-HSI), to estimate index of refraction which is invariant to viewing geometry. Results from a quartz window show that index of refraction can be retrieved to within 0.08 rms error from 875-1250 cm-1 for an amorphous material. Results from a silicon carbide (SiC) wafer, which has much sharper features than quartz glass, show the index of refraction can be retrieved to within 0.07 rms error. The results from each of these datasets show an improvement when compared with a maximum smoothness TES algorithm.

Paper Details

Date Published: 4 May 2016
PDF: 12 pages
Proc. SPIE 9853, Polarization: Measurement, Analysis, and Remote Sensing XII, 98530N (4 May 2016); doi: 10.1117/12.2222971
Show Author Affiliations
Jacob A. Martin, Air Force Research Lab. (United States)
Kevin C. Gross, Air Force Research Lab. (United States)
Air Force Institute of Technology


Published in SPIE Proceedings Vol. 9853:
Polarization: Measurement, Analysis, and Remote Sensing XII
David B. Chenault; Dennis H. Goldstein, Editor(s)

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