Multiresolution template matching using an optical correlator
Cofer, Rufus H.
Foor, Wesley E.
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Infrared imagery of 512 × 512 pixels was processed with 128 × 128 arrays by computer simulation of an optical correlator using various correlation filters. Pyramidal processing using binary phase-only filters (BPOFs), synthetic discriminant function (SDF) filters, and feature-based filters was used to process an entire image in parallel at different resolutions. Results showed that both SDF and feature-based filters were more robust to the effects of thresholding input imagery than BPOFs. The feature-based filters offered a range of performance by setting a parameter to different values. As the value of the parameter was changed, correlation peaks within the training set became more consistent and broader. The feature-based filters were more useful than both the SDF and simple BPOFs for recognizing objects outside the training set. Furthermore, the feature-based filter was more easily calculated and trained than an SDF filter.