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Proceedings Paper

Polarimetric phenomenology in the reflective regime: a case study using polarized hyperspectral data
Author(s): Mark Gibney
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Paper Abstract

Understanding the phenomenology of polarimetric data is necessary if we want to obtain the maximum benefit when we exploit that data. To first order, polarimetric phenomenology is driven by two things; the target material type (specular or diffuse) and the illuminating source (point (sun) or extended (body emission)). Polarimetric phenomenology can then be broken into three basic categories; ([specular material/sun source], [diffuse/sun], [specular/body]) where we have assigned body emission to the IR passband where materials are generally specular. The task of interest determines the category of interest since the task determines the dominant target material and the illuminating source (eg detecting diffuse targets under trees in VNIR = [diffuse/sun] category). In this paper, a specific case study for the important [diffuse/sun] category will be presented. For the reflective regime (0.3 – 3.0um), the largest polarimetric signal is obtained when the sun illuminates a significant portion of the material BRDF lobe. This naturally points us to problems whose primary target materials are diffuse since the BRDF lobe for specular materials is tiny (low probability of acquiring on the BRDF lobe) and glinty (high probability of saturating the sensor when on lobe). In this case study, we investigated signatures of solar illuminated diffuse paints acquired by a polarimetric hyperspectral sensor. We will discuss the acquisition, reduction and exploitation of that data, and use it to illustrate the primary characteristics of reflective polarimetric phenomenology.

Paper Details

Date Published: 4 May 2016
PDF: 12 pages
Proc. SPIE 9853, Polarization: Measurement, Analysis, and Remote Sensing XII, 98530M (4 May 2016); doi: 10.1117/12.2222848
Show Author Affiliations
Mark Gibney, Harris Corp. (United States)


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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