Optimal generalized weighted-order-statistic filters

Lin Yin; Jaakko T. Astola; Yrjo A. Neuvo

doi:10.1117/12.50359

1 November 1991 Optimal generalized weighted-order-statistic filters

Lin Yin, Jaakko T. Astola, Yrjo A. Neuvo

Proceedings Volume 1606, Visual Communications and Image Processing '91: Image Processing; (1991) https://doi.org/10.1117/12.50359
Event: Visual Communications, '91, 1991, Boston, MA, United States

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.

Citation Download Citation

Lin Yin, Jaakko T. Astola, and Yrjo A. Neuvo "Optimal generalized weighted-order-statistic filters", Proc. SPIE 1606, Visual Communications and Image Processing '91: Image Processing, (1 November 1991); https://doi.org/10.1117/12.50359

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