Estimating index of refraction for material identification in comparison to existing temperature emissivity separation algorithms

Jacob A. Martin; Kevin C. Gross

doi:10.1117/12.2222971

4 May 2016 Estimating index of refraction for material identification in comparison to existing temperature emissivity separation algorithms

Jacob A. Martin, Kevin C. Gross

Author Affiliations +

Proceedings Volume 9853, Polarization: Measurement, Analysis, and Remote Sensing XII; 98530N (2016) https://doi.org/10.1117/12.2222971
Event: SPIE Commercial + Scientific Sensing and Imaging, 2016, Baltimore, MD, United States

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.

Citation Download Citation

Jacob A. Martin and Kevin C. Gross "Estimating index of refraction for material identification in comparison to existing temperature emissivity separation algorithms", Proc. SPIE 9853, Polarization: Measurement, Analysis, and Remote Sensing XII, 98530N (4 May 2016); https://doi.org/10.1117/12.2222971

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