Share Email Print

Proceedings Paper

Adaptive multistage weighted order-statistic filters for image restoration
Author(s): Lin Yin; Jaakko T. Astola; Yrjo A. Neuvo
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

In this paper multistage weighted order statistic (MWOS) filters are introduced. With the aid of threshold decomposition, it is shown that any MWOS filter in real domain corresponds to a multistage threshold logic gate, or a multilayer perceptron in binary domain, which can be viewed as another representation of a stack filter. The MWOS filter requires much fewer parameters to represent a stack filter than the truth table of the positive Boolean function. An adaptive filtering algorithm, named as constrained backpropagation (CBP) algorithm, is developed for finding the optimal MWOS filters under the mean absolute error (MAE) criterion. The CBP algorithm is the same as the backpropagation algorithm used in multilayer perceptrons except the positivity of the parameters of MWOS filters, equal to the stacking property of stack filters, is imposed. Simulation results on image restoration are provided to compare the performance of the adaptive MWOS filters and the adaptive stack filters.

Paper Details

Date Published: 1 April 1991
PDF: 12 pages
Proc. SPIE 1451, Nonlinear Image Processing II, (1 April 1991); doi: 10.1117/12.44327
Show Author Affiliations
Lin Yin, Tampere Univ. of Technology (Finland)
Jaakko T. Astola, Tampere Univ. (Finland)
Yrjo A. Neuvo, Tampere Univ. of Technology (Finland)

Published in SPIE Proceedings Vol. 1451:
Nonlinear Image Processing II
Edward R. Dougherty; Gonzalo R. Arce; Charles G. Boncelet Jr., Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?