Background characterization techniques for target detection using scene metrics and pattern recognition

Paul V. Noah; Meg A. Noah; John W. Schroeder; Julian A. Chernick

doi:10.1117/12.55807

1 March 1991 Background characterization techniques for target detection using scene metrics and pattern recognition

Paul V. Noah, Meg A. Noah, John W. Schroeder, Julian A. Chernick

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Optical Engineering, Vol. 30, Issue 3, (March 1991). https://doi.org/10.1117/12.55807

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.

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Paul V. Noah, Meg A. Noah, John W. Schroeder, and Julian A. Chernick "Background characterization techniques for target detection using scene metrics and pattern recognition," Optical Engineering 30(3), (1 March 1991). https://doi.org/10.1117/12.55807

Published: 1 March 1991

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