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Two-dimensional acousto-optic (AO) correlators differ from frequency plane correlators in that multiplying, shifting, and adding, rather than Fourier transforming are used to obtain the correlations. Thus, manu of the available composite filter design techniques are not aimed at designing filters for use in AO correlators because they yield frequency-domain functions. In this paper, a method is introduced for designing filter impulse responses of arbitrary extent for implementation on AO correlators. These filters are designed to yield sharp correlation peaks. Simulation results are included to illustrate the viability of the proposed approach. Also included are some initial results from the first successful use of gray-scale composite filters on an AO correlator.

SNR expressions are derived for four different correlators in which, respectively, (1) the input and template are gray-scale signals, (2) the template signal is binarized, (3) the input is binarized, and (4) both signals are binarized. These expressions can be used with any reference image to quantify the loss of SNR due to binarization. The present results indicate that SNR loss due to binarization is not severe, allowing a relaxation of linearity and dynamic range requirements.

Optical correlators utilizing spatially incoherent light are examined and compared with coherent correlators. Frequency and image domain optical correlator architectures are discussed. The effect of speckle noise and input noise is examined. Simplified linear systems and Fourier transform descriptions of incoherent processors are provided. Simulation results are presented to quantitatively compare the performance of coherent and incoherent systems processing inputs containing additive noise. We consider pattern recognition correlator applications, rather than imaging systems in which the SNR of incoherent systems is better. For pattern recognition applications, SNR, PSR, and discrimination effects are very different as we show.

There has been a growing interest recently in the use of Phase-Only Filters (POFs) and Binary Phase-Only Filters (BPOFs) for optical pattern recognition. While BPOFs can be obtained by binarizing the phase of the classical matched filters, one wonders if the filter performance can be improved by allowing more phase levels. This paper provides a theoretical analysis of the increase in output Signal-to-Noise Ratio (SNR) as the number of phase levels is increased.

Complex ternary matched filters (CTMFs) can be implemented optically using detour phase and a single ternary spatial light modulator or a Mach-Zehnder arrangement and two ternary signal light modulators. In this paper, we present the design of CTMFs that yield high signal-tonoise ratios (SNRs) and show with the help of simulation examples that their performance (in the sense of SNRs) is close to that of optimal matched filters.

Recently, much attention has been paid to designing correlation filters that provide distortion-invariant pattern recognition. However, optical correlators can also be used to estimate the orientation and scale change in the object being observed. This paper presents two new methods for designing correlation filters that are aimed at determining the in-plane rotation and scale changes present in the input image (relative to a reference image). These methods assume that a known object is present in the input plane and that its rotation and scale are to be estimated. The first method is capable of determining both rotation and scale changes simultaneously. The second method assumes that the scale is fixed and estimates only the in-plane rotation. Both methods should prove useful in applications in which one needs to estimate the object orientation. Several simulation results are included to quantify the estimation accuracies and the computational complexities of the two methods.

An important task in many vision applications is that of rapidly estimating the orientation of an object with respect to some frame of reference. Because of their speed and parallel processing capabilities, optical correlators should prove valuable in this application. This paper considers two algorithms for object orientation estimation based on optical correlations and presents some initial simulation results.