Paper
5 September 2014 Dynamic data driven bidirectional reflectance distribution function measurement system
Stephen E. Nauyoks, Sam Freda, Michael A. Marciniak
Author Affiliations +
Abstract
The bidirectional reflectance distribution function (BRDF) is a fitted distribution function that defines the scatter of light off of a surface. The BRDF is dependent on the directions of both the incident and scattered light. Because of the vastness of the measurement space of all possible incident and reflected directions, the calculation of BRDF is usually performed using a minimal amount of measured data. This may lead to poor fits and uncertainty in certain regions of incidence or reflection. A dynamic data driven application system (DDDAS) is a concept that uses an algorithm on collected data to influence the collection space of future data acquisition. The authors propose a DDD-BRDF algorithm that fits BRDF data as it is being acquired and uses on-the-fly fittings of various BRDF models to adjust the potential measurement space. In doing so, it is hoped to find the best model to fit a surface and the best global fit of the BRDF with a minimum amount of collection space.
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Stephen E. Nauyoks, Sam Freda, and Michael A. Marciniak "Dynamic data driven bidirectional reflectance distribution function measurement system", Proc. SPIE 9205, Reflection, Scattering, and Diffraction from Surfaces IV, 920502 (5 September 2014); https://doi.org/10.1117/12.2061485
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CITATIONS
Cited by 3 scholarly publications.
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KEYWORDS
Bidirectional reflectance transmission function

Data modeling

Particle swarm optimization

Particles

Sensors

Data acquisition

Light scattering

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