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Binary encoding of gray scale nonlinear joint transform correlators.

B Javidi, Q Tang

|August 12, 2010

Summary

This summary is machine-generated.

This study introduces a nonlinear joint transform correlator that uses a multiple level threshold function to create a binary joint power spectrum. This method enhances pattern recognition capabilities by applying nonlinear transformations.

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Area of Science:

Optics and Photonics
Information Technology

Background:

Joint transform correlators (JTCs) are optical pattern recognition systems.
Nonlinearity is crucial for improving JTC performance.

Purpose of the Study:

To present a novel nonlinear joint transform correlator (NJTC).
To explore the effect of various nonlinear transformations on the joint power spectrum.

Main Methods:

The proposed system utilizes a multiple level threshold function.
The joint power spectrum is transformed by varying degrees of nonlinearity.
The transformed spectrum is binarized for processing.

Main Results:

The binarized joint power spectrum effectively represents transformed data.
Nonlinear transformations enhance discrimination capabilities in JTCs.
The system demonstrates robust pattern recognition.

Conclusions:

The developed NJTC offers an effective approach for optical pattern recognition.
Binarization of the nonlinear joint power spectrum is a viable strategy.
This technique holds promise for advanced optical information processing.