Thermal infrared scene simulation for plume detection algorithm evaluation

Robert L. Sundberg; Steven Richtsmeier; Alexander Berk; Steven Adler-Golden; Marsha Fox; Raymond Haren

doi:10.1117/12.544887

13 August 2004 Thermal infrared scene simulation for plume detection algorithm evaluation

Robert L. Sundberg, Steven Richtsmeier, Alexander Berk, Steven Adler-Golden, Marsha Fox, Raymond Haren

Proceedings Volume 5416, Chemical and Biological Sensing V; (2004) https://doi.org/10.1117/12.544887
Event: Defense and Security, 2004, Orlando, Florida, United States

Abstract

This paper demonstrates the use of a high fidelity hyperspectral scene simulation tool, called MCScene, to generate realistic thermal infrared scenes that can be used for algorithm development efforts, such as gas plume detection algorithms. MCScene is based on a Direct Simulation Monte Carlo (DSMC) approach for modeling 3D atmospheric radiative transport, as well as spatially inhomogeneous surfaces including surface BRDF effects. Synthetic “groundtruth” is specified as surface and atmospheric property inputs, and it is practical to consider wide variations of these properties. The model includes treatment of land and ocean surfaces, 3D terrain and bathymetry, 3D surface objects, and effects of finite clouds with surface shadowing. The computed hyperspectral data cubes can supplement field validation data for algorithm development. Sample calculations presented in this paper include a thermal infrared simulation for a desert scene that includes a gas plume produced by an industrial complex. This scene was derived from an AVIRIS visible to SWIR HSI data collect over the Virgin Mountains in Nevada. The data has been extrapolated to the thermal IR and a representative industrial site and plume have been added to the scene.

Citation Download Citation

Robert L. Sundberg, Steven Richtsmeier, Alexander Berk, Steven Adler-Golden, Marsha Fox, and Raymond Haren "Thermal infrared scene simulation for plume detection algorithm evaluation", Proc. SPIE 5416, Chemical and Biological Sensing V, (13 August 2004); https://doi.org/10.1117/12.544887

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