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Proceedings Paper

Optimal generalized weighted-order-statistic filters
Author(s): Lin Yin; Jaakko T. Astola; Yrjo A. Neuvo
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Paper Abstract

In this paper generalize weighted order statistic (GWOS) filters are introduced. As a subclass of generalized stack filters, GWOS filters can be implemented using a sorting operation in the real domain. Based on the relationship between GWOS filters and neural networks, two efficient adaptive algorithms are derived for finding optimal GWOS filters under the mean absolute error (MAE) and the mean squared error (MSE) criteria. Simulation results in image processing demonstrate that GWOS filters, like generalized stack filters, can suppress both impulsive noise and Gaussian noise more effectively than standard stack filters.

Paper Details

Date Published: 1 November 1991
PDF: 12 pages
Proc. SPIE 1606, Visual Communications and Image Processing '91: Image Processing, (1 November 1991); doi: 10.1117/12.50359
Show Author Affiliations
Lin Yin, Tampere Univ. of Technology (Finland)
Jaakko T. Astola, Tampere Univ. of Technology (Finland)
Yrjo A. Neuvo, Tampere Univ. of Technology (Finland)


Published in SPIE Proceedings Vol. 1606:
Visual Communications and Image Processing '91: Image Processing
Kou-Hu Tzou; Toshio Koga, Editor(s)

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