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Proceedings Paper

Detection of unresolved target tracks in infrared imagery
Author(s): Sarah A. Rajala; Loren W. Nolte; James V. Aanstoos
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Paper Abstract

Two methods for detecting dim, unresolved target tracks in infrared imagery are presented. Detecting such targets in a sequence of noisy images is very challenging from the standpoint of algorithm design as well as detection performance evaluation. Since the signal-to-noise ratio per pixel is very low (a dim target) and the target is unresolved (of spatial extent less than a pixel), one must rely on integration over target tracks which span over many image frames. In addition, since there is a large amount of uncertainty as to the pattern and location of target tracks, good algorithms must consider a large number of possibilities. The first method is based on a generalization of the Hough transform-based algorithm using the Radon transform. The second approach is an extension of a detection theory algorithm to 3-D. Both algorithms use a 3-D volume of spatial-temporal data.

Paper Details

Date Published: 1 November 1991
PDF: 12 pages
Proc. SPIE 1606, Visual Communications and Image Processing '91: Image Processing, (1 November 1991); doi: 10.1117/12.50334
Show Author Affiliations
Sarah A. Rajala, North Carolina State Univ. (United States)
Loren W. Nolte, Duke Univ. (United States)
James V. Aanstoos, Research Triangle Institute (United States)

Published in SPIE Proceedings Vol. 1606:
Visual Communications and Image Processing '91: Image Processing
Kou-Hu Tzou; Toshio Koga, Editor(s)

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