1 April 1988 Multiple Object Identification By Bipolar Joint Transform Correlation
Bahram Javidi, Souheil F. Odeh
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Abstract
We investigate the performance of a recently introduced bipolar joint transform image correlator when multiple reference objects and single and multiple targets are present at the input plane. The bipolar joint transform correlator uses nonlinearity at the Fourier plane to threshold the Fourier trans-forms' interference intensity to only two values, 1 and -1. The performance of the bipolar correlator is compared to the classical joint transform image correlator when multiple objects are present at the input plane. We show that the performance of the bipolar correlator is substantially superior to that of the classical joint transform image correlator in the areas of autocorrelation peak intensity, autocorrelation peak to sidelobe ratio, autocorrelation bandwidth, and discrimination sensitivity. It is shown that when multiple objects are present at the input plane, the classical joint transform image correlator produces large cross-correlation signals and poorly defined autocorrelation signals with large bandwidth. The large cross-correlation signals are comparable in intensity with the autocorrelation peak and can falsely indicate the presence of many targets. On the other hand, the bipolar joint transform image correlator produces well-defined autocorrelation signals with very low cross-correlation level. Computer simulations are used to test both types of correlators, and 3-D plots of the correlation functions are provided and discussed.
Bahram Javidi and Souheil F. Odeh "Multiple Object Identification By Bipolar Joint Transform Correlation," Optical Engineering 27(4), 274295 (1 April 1988). https://doi.org/10.1117/12.7976673
Published: 1 April 1988
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Cited by 49 scholarly publications.
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KEYWORDS
Joint transforms

Optical correlators

3D acquisition

Computer simulations

Correlation function

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