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Journal of Electronic Imaging

Training-based optimization of soft morphological filters
Author(s): Pertti T. Koivisto; Heikki Huttunen; Pauli Kuosmanen
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Paper Abstract

Soft morphological filters form a large class of nonlinear filters with many desirable properties. However, few design methods exist for these filters. This paper demonstrates how optimization schemes, simulated annealing and genetic algorithms, can be employed in the search for soft morphological filters having optimal performance in a given signal processing task. Furthermore, the properties of the achieved optimal soft morphological filters in different situations are analyzed.

Paper Details

Date Published: 1 July 1996
PDF: 23 pages
J. Electron. Imaging. 5(3) doi: 10.1117/12.242617
Published in: Journal of Electronic Imaging Volume 5, Issue 3
Show Author Affiliations
Pertti T. Koivisto, Univ. of Tampere (Finland)
Heikki Huttunen, Tampere Univ. of Technology (Finland)
Pauli Kuosmanen, Tampere Univ. of Technology (Finland)


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