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23 June 2000 Fusion of 2- /3- /4-sensor imagery for visualization, target learning, and search
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We present recent work on methods for fusion of imagery from multiple sensors for night vision capability. The fusion system architectures are based on biological models of the spatial and opponent-color processes in the human retina and visual cortex. The real-time implementation of the dual-sensor fusion system combines imagery from either a low-light CCD camera (developed at MIT Lincoln Laboratory) or a short-wave infrared camera (from Sensors Unlimited, Inc.) With thermal long-wave infrared imagery (from a Lockheed Martin microbolometer camera). Example results are shown for an extension of the fusion architecture to include imagery from all three of these sensors as well as imagery from a mid- wave infrared imager (from Raytheon Amber Corp.). We also demonstrate how the results from these multi-sensor fusion systems can be used as inputs to an interactive tool for target designation, learning, and search based on a Fuzzy ARTMAP neural network.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
David A. Fay, Allen M. Waxman, Mario Aguilar, David B. Ireland, Joseph P. Racamato, W. D. Ross, William W. Streilein, and Michael I. Braun "Fusion of 2- /3- /4-sensor imagery for visualization, target learning, and search", Proc. SPIE 4023, Enhanced and Synthetic Vision 2000, (23 June 2000);

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