Background clutter database models derived by stochastic means

Aaron Wilkosz; Bryan L. Williams; Steve Motz

doi:10.1117/12.352939

14 July 1999 Background clutter database models derived by stochastic means

Aaron Wilkosz, Bryan L. Williams, Steve Motz

Proceedings Volume 3699, Targets and Backgrounds: Characterization and Representation V; (1999) https://doi.org/10.1117/12.352939
Event: AeroSense '99, 1999, Orlando, FL, United States

Abstract

A statistical approach to background clutter modeling is described. A top-level description is given of a model used to generate spatial elements and thermal IR maps of high- resolution 3D background databases. The model employs fractional geometry techniques supplemented with a modified version of the random midpoint displacement. As input the model requires a material class map and a descriptor file containing information about the material classes identified in the class map. A stochastic interpolation scheme is used to generate high-resolution 3D background databases that display spatial correlation features that correlate well with empirical data.

Citation Download Citation

Aaron Wilkosz, Bryan L. Williams, and Steve Motz "Background clutter database models derived by stochastic means", Proc. SPIE 3699, Targets and Backgrounds: Characterization and Representation V, (14 July 1999); https://doi.org/10.1117/12.352939

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