Cart (Loading....) | Create Account
Close category search window

Linear combination of weighted order statistic filters: canonical structure and optimal design

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Song, J. ; Dept. of Electr. Eng., Korea Adv. Inst. of Sci. & Technol., Seoul, South Korea ; Yong Hoon Lee

A new class of filters, called linear combination of weighted order statistic (LWOS) filters, is introduced. This filter is a combination of L-filters and weighted order statistic (WOS) filters. Based on the observation that this filter possesses the threshold decomposition property, a representation of LWOS filters, named the canonical representation, is developed. It is shown that most nonrecursive filters having the threshold decomposition property can be thought of as special cases of the canonical LWOS filter. This result indicates that this class of LWOS filters encompasses a variety of filters which include median-type nonlinear filters and linear FIR filters. A procedure for designing an optimal canonical LWOS filter under the mean square error (MSE) criterion has been developed. The optimization of LWOS filters yields an FIR Wiener filter when the input is zero-mean Gaussian and a median-type nonlinear filter for non-Gaussian inputs. Experimental results in image restoration are presented to compare the relative performances of the LWOS and existing filters

Published in:

Circuits and Systems II: Analog and Digital Signal Processing, IEEE Transactions on  (Volume:43 ,  Issue: 5 )

Date of Publication:

May 1996

Need Help?

IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.