Hyperspectral imaging sensors operating in the visual, near IR, and thermal IR bands are sufficiently advanced to become a standard component of surveillance sensor suites. The output of these sensors contains a wealth of spectral and spatial information that can improve target detection and recognition performance. However, the large volume and complex features of hyperspectral data are challenges to automatic target recognition (ATR) algorithm development, and a simulation of hyperspectral sensing is therefore essential in evaluating algorithm performance. This paper describes the Infrared Hyperspectral Scene Simulation (IRHSS), an accurate, non-real-time large-scene simulation tool for hyperspectral imagers operating in the thermal IR bands. The simulation contains models for target and background spectral radiance, atmospheric propagation, and sensor processing. It uses a new hyperspectral version of the Multi-service Electro-optical Signature (MuSES) model to compute scene temperatures and hyperspectral radiances. IRHSS is able to handle very large terrain and feature databases by selective use of radiation view factors. It provides end-to-end simulation starting with scene models built from COTS simulation databases with faceted terrain and targets, and optional overlays of visual high-resolution texture imagery. IRHSS can be run as a standalone application via its Windows-based graphical user interface (GUI) or as a plug-in to existing software using the IRHSS application programming interface (API). Some screen images of the IRHSS GUI and example hyperspectral image cubes generated by IRHSS are included herein.

Date Published: 14 April 2008
PDF: 11 pages
Proc. SPIE 6966, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIV, 69661N (14 April 2008); doi: 10.1117/12.777845

Published in SPIE Proceedings Vol. 6966:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIV
Sylvia S. Shen; Paul E. Lewis, Editor(s)