Paper
22 August 1988 Two Variants Of The Optical Correlation Process
Robert R. Kallman
Author Affiliations +
Abstract
Simulations of the standard optical correlation process show that difficulties arise if the inputs are realistically modeled to be an aperture in a plane. These difficulties are especially grave if the inputs are targets in a background with substantial amplitude. Simple examples show that these difficulties cannot be solved by edge enhancement techniques or by suppression of low frequency terms in the Fourier plane. The purpose of this paper is to give two new variants of the standard optical correlation process which solve this aperture problem. This assertion is empirically supported by a great deal of testing over numerous data sets. These two variants are to be used with phase-only or binary filters implemented in an addressable spatial light modulator in the Fourier plane. Each variant requires its own careful nonstandard design of the phase-only filters. The direct construction of phase-only filters developed previously by the author can and must be used to make filters suitable for these variants. Simulations suggest that the resulting filters can be packed with a great deal of information, are stable under perturbations in the training set, have a very low false alarm rate, and are extremely insensitive to backgrounds consisting of high variance, high mean, Gaussian or uniform noise. These two variants give superior results even when targets are in a zero or low amplitude background.
© (1988) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Robert R. Kallman "Two Variants Of The Optical Correlation Process", Proc. SPIE 0938, Digital and Optical Shape Representation and Pattern Recognition, (22 August 1988); https://doi.org/10.1117/12.976574
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Cited by 2 scholarly publications.
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KEYWORDS
Detection and tracking algorithms

Phase only filters

Signal to noise ratio

Fourier transforms

Optical correlators

Image filtering

Optical pattern recognition

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