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Proceedings Paper

Comparative study of filtering techniques for binary nonhomogeneous images
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Paper Abstract

In this paper we compare the performance of linear and nonlinear filters on binary images. The maximum-likelihood ratio test (MLRT) processor is optimal for detection. We generalize it and use it for location. It is thus well suited as an upper reference with which we compare the performance of the other filters. We present the maximum likelihood ratio approximation (MLRA) and we compare the MLRA and the nonlinear joint transform correlator (NLJTC) with the MLRT. By having a look at the impulse responses of these processors we can explain the similarities in performance. We also compare the MLRT with classical linear filters, such as the optimal trade- off (OT) filter and the classical matched filter (CMF). We show that the automatic regularization given by the binary noise makes the CMF perform almost as good as the MLRT. The OT filter can be regularized through the choice of the tuning parameter and it also shows almost as good performance as the MLRT.

Paper Details

Date Published: 9 March 1999
PDF: 9 pages
Proc. SPIE 3715, Optical Pattern Recognition X, (9 March 1999); doi: 10.1117/12.341328
Show Author Affiliations
Henrik J. Sjoberg, Royal Institute of Technology (Sweden)
Francois Goudail, Ecole Nationale Superieure de Physique de Marseille (France)
Philippe Refregier, Ecole Nationale Superieure de Physique de Marseille (France)

Published in SPIE Proceedings Vol. 3715:
Optical Pattern Recognition X
David P. Casasent; Tien-Hsin Chao, Editor(s)

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