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Optical Engineering

Background characterization techniques for target detection using scene metrics and pattern recognition
Author(s): Paul V. Noah; Meg A. Noah; John W. Schroeder; Julian A. Chernick
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Paper Abstract

The U.S. Army has a requirement to develop systems for the detection and identification of ground targets in a clutter environment. Autonomous Homing Munitions (AHM) using infrared, visible, millimeter wave and other sensors are being investigated for this application. Advanced signal processing and computational approaches using pattern recognition and artificial intelligence techniques combined with multisensor data fusion have the potential to meet the Army's requirements for next generation AHM. In a complex background scene the "problem" is as much one of clutter rejection as it is target detection. This work applies statistical pattern recognition approaches to background clutter characterization for target detection and identification. These techniques are used to evaluate a set of image metrics applied to infrared terrain clutter scenes.

Paper Details

Date Published: 1 March 1991
PDF: 5 pages
Opt. Eng. 30(3) doi: 10.1117/12.55807
Published in: Optical Engineering Volume 30, Issue 3
Show Author Affiliations
Paul V. Noah, ONTAR Corp. (United States)
Meg A. Noah, ONTAR Corp. (United States)
John W. Schroeder, ONTAR Corp. (United States)
Julian A. Chernick, U.S. Army (United States)


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