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Proceedings Paper

Statistical moments based methods for detecting sub-pixel target tracks in large image sequences
Author(s): Christoph C. Borel; David J. Bunker; Lori A. Mahoney
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Paper Abstract

This paper reviews and compares the performance of several methods to detect target tracks in image sequences. The targets are assumed to be sub-pixel or not resolved by the imaging system, and moving over a static background. To process the resulting large amount of data requires simple, fast and robust processing methods to quickly find and display tracks of moving targets in a single image. An object moving through a pixel in a scene will momentarily perturb the pixel intensity signal, introducing a change of both skewness and kurtosis in the intensity histogram relative to an undisturbed pixel. Numerical experiments show that for Gaussian and Poisson distributed system noise higher order moments (<2) perform better than second order detectors.

Paper Details

Date Published: 19 June 2014
PDF: 9 pages
Proc. SPIE 9089, Geospatial InfoFusion and Video Analytics IV; and Motion Imagery for ISR and Situational Awareness II, 90890U (19 June 2014); doi: 10.1117/12.2050004
Show Author Affiliations
Christoph C. Borel, Air Force Institute of Technology (United States)
David J. Bunker, Air Force Institute of Technology (United States)
Lori A. Mahoney, National Geospatial-Intelligence Agency (United States)


Published in SPIE Proceedings Vol. 9089:
Geospatial InfoFusion and Video Analytics IV; and Motion Imagery for ISR and Situational Awareness II
Matthew F. Pellechia; Kannappan Palaniappan; Shiloh L. Dockstader; Paul B. Deignan; Peter J. Doucette; Donnie Self, Editor(s)

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