Fusion of Multi-Sensor Imagery for Night Vision: Color Visualization, Target Learning and Search

1 This work was sponsored by the U.S. Defense Advanced Research Projects Agency, under Air Force Contract F19628-95-C-0002. Opinions, interpretations, conclusions, and recommendations are those of the authors and not necessarily endorsed by the U.S. Air Force. 2 Present Address: MCIS Department, Jacksonville State University, Jacksonville, AL 36265, U.S.A. Abstract We present methods and results for fusion of imagery from multiple sensors to create a color night vision capability. The fusion system architectures are based on biological models of the spatial and opponentcolor processes in the human retina and visual cortex, implemented as shunting center-surround feed-forward neural networks. Real-time implementation of the dualsensor fusion system combines imagery from either a low-light CCD camera or a short-wave infrared camera, with thermal long-wave infrared imagery. Results are also shown for extensions of this fusion architecture to include imagery from all three of these sensors, Visible/SWIR/LWIR, as well as a four sensor system using Visible/SWIR/MWIR/LWIR cameras. We also demonstrate how results from these multi-sensor fusion systems are used as inputs to an interactive tool for target designation, learning, and search based on a Fuzzy ARTMAP neural network.