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Proceedings Paper

Bayesian theoretical approach to nonlinear joint-transform correlation
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Paper Abstract

We propose a bayesian approach adapted to practical target detection and location tasks where the spectral density of a Gaussian additive noise is unknown. We demonstrate that the nonlinear joint-transform correlation, which is frequency used in optical correlators, is an accurate approximation of this optimal bayesian processor. This results constitutes a theoretical support for the use of nonlinearities in optical correlators.

Paper Details

Date Published: 19 August 1997
PDF: 7 pages
Proc. SPIE 3101, New Image Processing Techniques and Applications: Algorithms, Methods, and Components II, (19 August 1997); doi: 10.1117/12.281277
Show Author Affiliations
Philippe Refregier, Ecole Nationale Superieure de Physique de Marseille (France)
Francois Goudail, Ecole Nationale Superieure de Physique de Marseille (France)


Published in SPIE Proceedings Vol. 3101:
New Image Processing Techniques and Applications: Algorithms, Methods, and Components II

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