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Sean Archer

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Proceedings Article | 21 May 2015 Paper

Empirical measurement and model validation of infrared spectra of contaminated surfaces

Sean Archer, Michael Gartley, John Kerekes, Bogdon Cosofret, Jay Giblin

Proceedings Volume 9472, 947215 (2015) https://doi.org/10.1117/12.2177683

KEYWORDS: Aluminum, Bidirectional reflectance transmission function, Contamination, Statistical modeling, Sensors, Data modeling, Temperature metrology, Infrared radiation, Thermal modeling, Digital imaging

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Liquid-contaminated surfaces generally require more sophisticated radiometric modeling to numerically describe surface properties. The Digital Imaging and Remote Sensing Image Generation (DIRSIG) Model utilizes radiative transfer modeling to generate synthetic imagery. Within DIRSIG, a micro-scale surface property model (microDIRSIG) was used to calculate numerical bidirectional reflectance distribution functions (BRDF) of geometric surfaces with applied concentrations of liquid contamination. Simple cases where the liquid contamination was well described by optical constants on optically at surfaces were first analytically evaluated by ray tracing and modeled within microDIRSIG. More complex combinations of surface geometry and contaminant application were then incorporated into the micro-scale model. The computed microDIRSIG BRDF outputs were used to describe surface material properties in the encompassing DIRSIG simulation. These DIRSIG generated outputs were validated with empirical measurements obtained from a Design and Prototypes (D&P) Model 102 FTIR spectrometer. Infrared spectra from the synthetic imagery and the empirical measurements were iteratively compared to identify quantitative spectral similarity between the measured data and modeled outputs. Several spectral angles between the predicted and measured emissivities differed by less than 1 degree. Synthetic radiance spectra produced from the microDIRSIG/DIRSIG combination had a RMS error of 0.21-0.81 watts/(m²−sr−μm) when compared to the D&P measurements. Results from this comparison will facilitate improved methods for identifying spectral features and detecting liquid contamination on a variety of natural surfaces.

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