Adaptive optical correlation using neural network approaches

David L. Flannery; Steven C. Gustafson

doi:10.1117/12.59847

1 April 1992 Adaptive optical correlation using neural network approaches

David L. Flannery, Steven C. Gustafson

Author Affiliations +

Proceedings Volume 10262, Optical Pattern Recognition: A Critical Review; 1026203 (1992) https://doi.org/10.1117/12.59847
Event: Critical Reviews, 1991, San Jose, CA, United States

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.

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David L. Flannery and Steven C. Gustafson "Adaptive optical correlation using neural network approaches", Proc. SPIE 10262, Optical Pattern Recognition: A Critical Review, 1026203 (1 April 1992); https://doi.org/10.1117/12.59847

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