Adaptive FIR-WOS hybrid filtering

Author

Yin, Lin ; Neuvo, Yrjö

Author_Institution

Dept. of Electr. Eng., Tampere Univ. of Technol., Finland

Volume

6

fYear

1992

fDate

10-13 May 1992

Firstpage

2637

Abstract

Through the combination of linear finite impulse response (FIR) filters and weighted order statistic (WOS) filters, the authors introduce a new class of nonlinear filters called FIR-WOS hybrid (FWH) filters. This class of filters, including FIR filters, WOS filters, and various kinds of FIR median hybrid (FMH) filters, consists of a few linear FIR subfilters and a WOS filter operated over the outputs of the subfilters. Motivated by the backpropagation algorithm used in neural networks, an adaptive algorithm is derived in the binary domain for determining optimal FWH filters under the mean absolute error criterion. Simulation results in image processing demonstrate that adaptive FWH filters perform as well as linear filters in Gaussian noise and better than adaptive WOS filters in impulsive noise

Keywords

adaptive filters; digital filters; filtering and prediction theory; image processing; Gaussian noise; adaptive algorithm; adaptive hybrid filtering; binary domain; finite impulse response; image processing; impulsive noise; linear FIR filters; linear FIR subfilters; mean absolute error criterion; median hybrid filters; nonlinear filters; weighted order statistic; Adaptive algorithm; Adaptive filters; Backpropagation algorithms; Filtering; Finite impulse response filter; Gaussian noise; Image processing; Neural networks; Nonlinear filters; Statistics;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 1992. ISCAS '92. Proceedings., 1992 IEEE International Symposium on

Conference_Location

San Diego, CA

Print_ISBN

0-7803-0593-0

Type

conf

DOI

10.1109/ISCAS.1992.230679

Filename

230679