NDLI: Generalized Mean-Median Filtering for Robust Frequency-Selective Applications

Content Provider	IEEE Xplore Digital Library
Author	Aysal, T.C. Barner, K.E.
Copyright Year	1991
Abstract	Huber proposed the P_epsi family of epsi-contaminated normal distributions to model environments characterized by heavy-tailed distributions. Based on this two-component mixture distribution, mean-median (MEM) filters were proposed. The MEM filter output is a combination of the sample mean and the sample median, where observation samples are weighted uniformly. This property of MEM filters constrains them to the class of smoothers lacking frequency-selective filtering capabilities. This paper extends MEM filtering to the weighted sum-median (WSM) filtering structure admitting real-valued weights, thereby enabling more general filtering characteristics, i.e, bandpass and high-pass filtering. The proposed filter structure is also well motivated from a presented maximum likelihood (ML) estimate analysis under epsi-contaminated statistics. The ML analysis demonstrates the need for a combination of weighted sum (WS) and weighted median (WM) type filters for processing of signals corrupted by epsi-contaminated noise. The WSM filter is statistically analyzed through the determination of filter output variance and breakdown probability. The combination parameter alpha is optimized to minimize the filter output variance, which is a measure of noise attenuation capability. Moreover, filter design procedures that yield a desired spectral response are detailed. Finally, the proposed WSM filter structure is tested utilizing signal processing applications including low-pass, bandpass, and high-pass filtering and image processing applications including image sharpening and denoising, evaluating and comparing the WSM filter performance to that of the WS, WM, and MEM filters
Sponsorship	IEEE Signal Processing Society
Starting Page	937
Ending Page	948
Page Count	12
File Size	2009061
File Format	PDF
ISSN	1053587X
Volume Number	55
Issue Number	3
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-03-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Filtering Robustness Frequency Band pass filters Maximum likelihood estimation Signal processing Gaussian distribution Statistical analysis Signal analysis Analysis of variance weighted median $\epsilon$ -contaminated maximum likelihood estimate mixed-filtering nonlinear filtering weighted mean
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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