Debiased Opto-electronic Joint Transform Correlator for Enhanced Real-Time Pattern Recognition

Abstract

Opto-electronic joint transform correlators (OJTCs) use a focal plane array (FPA) to detect the joint power spectrum (JPS) of two input images, projecting it onto a spatial light modulator (SLM) to be optically Fourier transformed. The JPS is composed of two self-intensities and two conjugate-products, where only the latter produce the cross-correlation. However, the self-intensity terms are typically much stronger than the conjugate-products, producing a bias that consumes most of the available bit-depth on the FPA and SLM. Here we propose and demonstrate, through simulation and experiment, a debiased OJTC (DOJTC) that electronically pre-processes the JPS to remove the self-intensity terms before sending it to the SLM, thereby enhancing the quality of the cross-correlation result. We show that under some conditions the DOJTC yields a nearly two orders of magnitude improvement in the signal-to-noise ratio compared to an OJTC.