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Proceedings Paper

Polarimetric assist to HSI atmospheric compensation and material identification
Author(s): Mark Gibney
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Paper Abstract

In this effort, we investigated how polarimetric HyperSpectral Imaging (pHSI) data might benefit specified Material Identification of diffuse materials in the VNIR. The experiment compared paint reflectivities extracted from polarimetric hyperspectral data acquired in the field to a database of truth reflectivities measured in the lab. Both the polarimetric hyperspectral data and the reflectivities were acquired using an Ocean Optics spectrometer which was polarized using a fast filter wheel loaded with high extinction polarizers. During the experiment, we discovered that the polarized spectra from the polarimetric hyper spectral data could be used to estimate the relative spectral character of the field source (the exo-atmospheric sun plus the atmosphere). This benefit, which strongly parallels the QUAC atmospheric correction method, relies on the natural spectral flatness of the polarized spectrum that originates in the spectral flatness of the index of refraction in the reflective regime. Using this estimate of the field source, excellent estimates of the paint reflectivities (matching 10 paint reflectivities to ≤ 0.5% RSS) were obtained. The impact of atmospheric upwell on performance was then investigated using these ground based polarimetric hyper spectral data in conjunction with modeled atmospheric path effects. The path effects were modeled using the high fidelity Polarimetry Phenomenology Simulation (PPS) plate model developed by AFRL, which includes polarized Modtran. We conclude with a discussion of actual and potential applications of this method, and how best to convert an existing VNIR HSI sensor into a pHSI sensor for an airborne Proof Of Concept experiment.

Paper Details

Date Published: 17 May 2016
PDF: 17 pages
Proc. SPIE 9840, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXII, 98401P (17 May 2016); doi: 10.1117/12.2222824
Show Author Affiliations
Mark Gibney, Harris Corp. (United States)

Published in SPIE Proceedings Vol. 9840:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXII
Miguel Velez-Reyes; David W. Messinger, Editor(s)

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