A priori and adaptive Wiener filtering with joint transform correlators

We propose general, simple, and powerful means of extending the capabilities of conventional joint-transform-correlator systems to enable a priori or adaptive Wiener filtering as well as parametric Wiener filtering of patterns corrupted by colored noise. Adaptive estimation of the noise power spectral density distribution may be obtained from input power spectra information and provides great flexibility and real-time adaptivity to colored noise, resulting in improved correlation performance.