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Proceedings Paper

Fusion of 2- /3- /4-sensor imagery for visualization, target learning, and search
Author(s): David A. Fay; Allen M. Waxman; Mario Aguilar; David B. Ireland; Joseph P. Racamato; W. D. Ross; William W. Streilein; Michael I. Braun
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Paper Abstract

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.

Paper Details

Date Published: 23 June 2000
PDF: 10 pages
Proc. SPIE 4023, Enhanced and Synthetic Vision 2000, (23 June 2000); doi: 10.1117/12.389334
Show Author Affiliations
David A. Fay, MIT Lincoln Lab. (United States)
Allen M. Waxman, MIT Lincoln Lab. (United States)
Mario Aguilar, MIT Lincoln Lab. (United States)
David B. Ireland, MIT Lincoln Lab. (United States)
Joseph P. Racamato, MIT Lincoln Lab. (United States)
W. D. Ross, MIT Lincoln Lab. (United States)
William W. Streilein, MIT Lincoln Lab. (United States)
Michael I. Braun, MIT Lincoln Lab. (United States)


Published in SPIE Proceedings Vol. 4023:
Enhanced and Synthetic Vision 2000
Jacques G. Verly, Editor(s)

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