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Proceedings Paper

Near real-time expectation-maximization algorithm: computational performance and passive millimeter wave imaging field test results
Author(s): William R. Reynolds; Denise Talcott; John W. Hilgers
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Paper Abstract

A new iterative algorithm (EMLS) via the expectation maximization method is derived for extrapolating a non- negative object function from noisy, diffraction blurred image data. The algorithm has the following desirable attributes; fast convergence is attained for high frequency object components, is less sensitive to constraint parameters, and will accommodate randomly missing data. Speed and convergence results are presented. Field test imagery was obtained with a passive millimeter wave imaging sensor having a 30.5 cm aperture. The algorithm was implemented and tested in near real time using field test imagery. Theoretical results and experimental results using the field test imagery will be compared using an effective aperture measure of resolution increase. The effective aperture measure, based on examination of the edge-spread function, will be detailed.

Paper Details

Date Published: 29 July 2002
PDF: 13 pages
Proc. SPIE 4719, Infrared and Passive Millimeter-wave Imaging Systems: Design, Analysis, Modeling, and Testing, (29 July 2002); doi: 10.1117/12.477446
Show Author Affiliations
William R. Reynolds, Signature Research, Inc. (United States)
Denise Talcott, Signature Research, Inc. (United States)
John W. Hilgers, Signature Research, Inc. (United States)

Published in SPIE Proceedings Vol. 4719:
Infrared and Passive Millimeter-wave Imaging Systems: Design, Analysis, Modeling, and Testing
Roger Appleby; Roger Appleby; David A. Wikner; Gerald C. Holst; David A. Wikner, Editor(s)

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