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Proceedings Paper

Design of an optimal-weighted MACE filter realizable with arbitrary SLM constraints
Author(s): Jin Ge; P. Karivaratha Rajan
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Paper Abstract

A realizable optimal weighted minimum average correlation energy (MACE) filter with arbitrary spatial light modulator (SLM) constraints is presented. The MACE filter can be considered as the cascade of two separate stages. The first stage is the prewhitener which essentially converts colored noise to white noise. The second stage is the conventional synthetic discriminant function (SDF) which is optimal for white noise, but which uses training vectors subjected to the prewhitening transformation. So the energy spectrum matrix is very important for filter design. New weight function we introduce is used to adjust the correlation energy to improve the performance of MACE filter on current SLMs. The action of the weight function is to emphasize the importance of the signal energy at some frequencies and reduce the importance of signal energy at some other frequencies so as to improve correlation plane structure. The choice of weight function which is used to enhance the noise tolerance and reduce sidelobes is related to a priori pattern recognition knowledge. An algorithm which combines an iterative optimal technique with Juday's minimum Euclidean distance (MED) method is developed for the design of the realizable optimal weighted MACE filter. The performance of the designed filter is evaluated with numerical experiments.

Paper Details

Date Published: 15 March 1996
PDF: 12 pages
Proc. SPIE 2752, Optical Pattern Recognition VII, (15 March 1996); doi: 10.1117/12.235670
Show Author Affiliations
Jin Ge, Tennessee Technological Univ. (United States)
P. Karivaratha Rajan, Tennessee Technological Univ. (United States)


Published in SPIE Proceedings Vol. 2752:
Optical Pattern Recognition VII
David P. Casasent; Tien-Hsin Chao, Editor(s)

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