Abstract
Harsh Environment Applied Technology (HEAT) has developed a ground-based forward-looking multispectral data collection system mounted on a rugged All Terrain Vehicle (ATV) to allow recording imagery while moving over rough terrain. The image data collected from multiple bands of the Electro-Optical/Infrared (EO/IR) spectrum is used to aid image fusion algorithm development for applications such as night vision goggles. The existing system consists of VNIR, SWIR, and LWIR cameras mounted on a ruggedized Pan/Tilt, a rack-mount PC with frame grabbers to capture digital images, and a 4 TB RAID for real-time image storage. The system can also record meteorological data and GPS information synchronized with the imagery. HEAT has developed a methodology for algorithm development using imagery and other important parameters about the scene of interest. The imagery collected by the data collection system during field exercises is stored in a database of imagery; the imagery can then be replayed into a model running in MATLAB on a desktop PC in the lab. The synchronized raw imagery and meteorological data would be provided as inputs to the model. The model is used to develop image fusion algorithms to display the best possible fused image to human eyes. Also, target identification algorithms are developed and optimized for best probability of detection with lowest false alarm rate. The optimized algorithms for both displaying to the human eyes and to computer aided target tracking can then be ported to a rugged Field Programmable Gate Array (FPGA)-based system to deploy in the real world environment. Sample raw imagery input from the cameras into the data collection system will be shown. Examples of fused imagery created by the fusion algorithms will also be shown.