Abstract
The Wiener filter (WF), which has been used extensively for image restoration and signal processing, is employed for robust optical pattern recognition and classification. The WF is formulated to incorporate the in-class image (to be detected) and the out-of-class noise image (to be rejected) into a single step filter construction. It is compared with the classical matched filter (CMF) and phase-only filter (POF), demonstrating a superior discriminatory capability. The WF is incorporated into a synthetic discriminant function (SDF); correlation results show that it is tolerant to image distortion. With a 30 ° out of plane rotation between training set images, the WF SDF achieves a 100% success rate in discriminating one class of images from another. The CMF SDF and POF SDF fail to achieve 100% discrimination even at rotation increments of 15 °.
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