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Proceedings Paper

Adaptive optical correlation using neural network approaches
Author(s): David L. Flannery; Steven C. Gustafson
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Paper Abstract

This paper reviews work on binary phase-only (BPOF) and ternary phase-amplitude (TPAF) correlation and highlights recent investigations of neural network approaches for augmenting correlation-based hybrid (optical/electronic) automatic target recognition systems. The theory and implementation of BPOF and TPAF correlation using available spatial light modulators is reviewed, including recent advances in smart TPAF formulations. Results showing the promise of neural networks for enhancing correlation system operation in the areas of estimating distortion parameters, adapting filters, and improving discrimination are presented and discussed.

Paper Details

Date Published: 1 April 1992
PDF: 21 pages
Proc. SPIE 10262, Optical Pattern Recognition: A Critical Review, 1026203 (1 April 1992); doi: 10.1117/12.59847
Show Author Affiliations
David L. Flannery, Univ. of Dayton Research Institute (United States)
Steven C. Gustafson, Univ. of Dayton Research Institute (United States)


Published in SPIE Proceedings Vol. 10262:
Optical Pattern Recognition: A Critical Review
Joseph L. Horner; Bahram Javidi, Editor(s)

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