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28 March 1995 Iterative method for the design of SLM realizable minimum average correlation energy (MACE) filters
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Abstract
Design of optical pattern recognition filters taking into account the nonideal characteristics of the spatial light modulators on which the filters are implemented is an important research problem. In this paper, an iterative method is developed for the design of SLM constrained minimum average correlation energy (MACE) filters. The algorithm uses a relaxation algorithm in conjunction with Juday's minimum euclidean distance (MED) mapping technique in an iterative manner. The performance of the filter designed using this method was evaluated using computer simulations and the results are compared with a constrained MACE filter designed using a software based on a simulated annealing technique. The new software requires much less computer time than the simulated annealing based software providing comparable response. The time taken by the new algorithm is more than that for the MED mapped design; but, the new algorithm provides less deviation from the specified response for training images than the MED mapped design.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
P. Karivaratha Rajan and R. Ramakrishnan "Iterative method for the design of SLM realizable minimum average correlation energy (MACE) filters", Proc. SPIE 2490, Optical Pattern Recognition VI, (28 March 1995); https://doi.org/10.1117/12.205776
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