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Proceedings Paper

Large Capacity Phase-Only Encoded Smart Correlators
Author(s): Bahram Javidi
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Paper Abstract

Major limitations to the successful application of optical pattern recognition systems have usually been the memory requirements necessary for realistic tasks and the implementation of such optical memory techniques. Here, we have considered the possibility of generating the NXN array of filters by using real-time computer generated holography where the Fourier transforms of the NXN reference image are produced in the computer. The NXN array of Fourier transform holograms are converted to phase-only encoded filters by utilizing the phase function of the Fourier transform elements of the array. The phase-only encoded NXN array is written onto a spatial light modulator for pattern recognition applications. Thus, a phase-only encoded correlator with high storage capacity is produced. An important feature of the proposed technique is the ability to update or change each element of the NXN filter array in real-time independent of the other members of the filter set. This feature does not exist in the previous large memory correlation techniques since the filters were stored on film and to change a member of the array required a new synthesis of the entire array. We shall study the performance of the proposed binary capacity correlator by determining the peak to sidelobe ratio and the bandwidth of the resulting correlation signals. The effects of phase-encoding and the finite space-bandwidth product of each element of the array will be studied. The effects of overlapping terms at the filter plane contributing to cross talk will also be investigated. Both binary phase-only encoding and continuous phase-only encoding are investigated and the results are compared to the multiplexed classical matched filters.

Paper Details

Date Published: 12 October 1988
PDF: 11 pages
Proc. SPIE 0956, Piece Recognition and Image Processing, (12 October 1988); doi: 10.1117/12.947691
Show Author Affiliations
Bahram Javidi, Michigan State University (United States)


Published in SPIE Proceedings Vol. 0956:
Piece Recognition and Image Processing
Wayne Wiitanen, Editor(s)

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