Robust Hyperspectral Targeting and Reacquisition Software

ABSTRACT:Hyperspectral imaging (HSI) sensors have the unique ability to identify objects based on the spectral signatures of their surface materials. Movements of designated targets could be detected using images collected hours to days after they move. Many targets of interest, such as vehicles, have specular (non-Lambertian) surfaces with multiple materials and surface angles. This complexity, combined with possible changing atmospheric/illumination conditions and viewing geometries, can cause the observed target spectral signatures to fluctuate considerably, making detection and/or reacquisition challenging. The goal of this R&D by Spectral Sciences, Inc. and the Rochester Institute of Technology is to develop novel algorithms and software to extract, predict, and account for these signature variations and thus advance the state of the art in hyperspectral detection and identification. The software would incorporate reflectance and BRDF databases, a reflectance calculation module, and a detection module. In addition, Phase II will feature a new field data collect focused on validating the target BRDF modeling and detection algorithms. The Phase II software package will be embedded in a copy of the popular ENVI software package as a prelude to transitioning the software to a Phase III commercial product for the private sector, government agencies, and academia. BENEFIT:The software would bring enhanced performance to hyperspectral target detection and identification in military and homeland security applications, including border and perimeter surveillance, site monitoring, and search and rescue. Platforms include UAVs and spaceborne systems. Potential civilian remote sensing applications are in the areas of agriculture, mineral prospecting, land management, drug interdiction, disaster preparedness, and disaster damage assessment. Potential applications in medical hyperspectral imaging include detection of pathogens, biotoxins, and disease processes.