Adaptive Facet Reflection Modeling

Abstract

Calculating the reflected irradiances produced by a specularly reflecting object at many observation points is computationally intensive, the total computational load proportional to the product of the number of facets times the number of observation points. In order to capture specular glints at all observation points, it is necessary to finely discretize the surface of the object into a large number of facets. This can result in a massive number of computations. The computational load can be reduced by approximating the surface of the object by curved triangular facets modeled as either quadric surfaces or point-normal triangles. Starting with a coarse discretation of the surface, a finer representation can be produced by subdividing the initial facets. For a single observation point, only a small fraction of the surface contributes to the specular glint; therefore only a few facets need to be significantly subdivided for accurate computations. By adaptively subdividing, the number of facets required per observation point is greatly reduced, resulting in fewer computations and thus increased overall computational speed. The speed increase is illustrated for a cylindrical object and different angular widths of the specular peak. As the width decreases, adaptive faceting increases the computational savings.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2010
Accession Number
ADA534752

Entities

People

  • Albert Bailey
  • Edward Early
  • Paul Kennedy
  • Robert J. Thomas

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Air Force
  • Air Force Research Laboratories
  • Computations
  • Directed Energy Weapons
  • Distribution Functions
  • Energy
  • Geometry
  • High Energy Lasers
  • Intensity
  • Lasers
  • Light Sources
  • Materials
  • Military Research
  • Observation
  • Observers
  • Reflection
  • Triangles

Fields of Study

  • Physics

Readers

  • Applied Combinatorial Optimization and Logic Circuit Design.
  • Graph Algorithms and Convex Optimization.
  • Spectroscopy.