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Proceedings Paper

Joint Transform Correlation With The Synthetic Estimation Filter
Author(s): Stanley E. Monroe; Richard D. Juday; Jerome Knopp
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Paper Abstract

The synthetic estimation filter (SEF) combines a set of input images into a much smaller set of filters. Those input images correspond to views of a known object taken with a variety of values of the pose parameter to be estimated. The response of the filter to variations in the pose parameter is tailored so that estimation can be done to a precision considerably finer than the intervals between filters in the pose space. We here extend the technique to the joint transform correlator; as a reference we use the composite image from which the SEF is conventionally calculated. Precautions are necessary for practical reasons. For example, the SEF algorithm may call for negative values in the image, an unrealizable condition with amplitude encoding, whereas with phase-mostly filtering in the SEF, negative image values are easily accommodated.

Paper Details

Date Published: 5 February 1990
PDF: 8 pages
Proc. SPIE 1151, Optical Information Processing Systems and Architectures, (5 February 1990); doi: 10.1117/12.962228
Show Author Affiliations
Stanley E. Monroe, Lockheed Engineering and Science Company (United States)
Richard D. Juday, NASA Johnson Space Center (United States)
Jerome Knopp, The University of Missouri-Columbia (United States)

Published in SPIE Proceedings Vol. 1151:
Optical Information Processing Systems and Architectures
Bahram Javidi, Editor(s)

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