New class of order statistic filters for running median estimation

Risto Suoranta, Kari-Pekka Estola

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

3 Citations (Scopus)

Abstract

A novel low variance median estimator is presented. This order statistic based estimator is derived by means of a set-theoretic approach. It is shown that the proposed subset average median estimate (SAME) shares many good properties with both the mean and the median operator. Properties of this filter are controlled with two parameters: the window length and the subset size q. A good noise attenuation together with robust behavior can be obtained by selecting an appropriate subset length q. Numerical studies show that SAME filter outperforms the ordinary median filter in noise attenuation when is is applied to signals with various noise characteristics including Laplacian and Gaussian noise.
Original languageEnglish
Title of host publication1993 IEEE International Conference on Acoustics, Speech, and Signal Processing
Place of PublicationPiscataway
PublisherIEEE Institute of Electrical and Electronic Engineers
Number of pages4
ISBN (Print)0-7803-0946-4, 0-7803-7402-9
DOIs
Publication statusPublished - 1993
MoE publication typeA4 Article in a conference publication
Event1993 International Conference on Acoustics, Speech and Signal Processing - Minneapolis, United States
Duration: 27 Apr 199330 Apr 1993

Publication series

SeriesProceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing
ISSN1520-6149

Conference

Conference1993 International Conference on Acoustics, Speech and Signal Processing
Country/TerritoryUnited States
CityMinneapolis
Period27/04/9330/04/93

Keywords

  • statistics
  • Gaussian noise
  • size control
  • noise robustness

Fingerprint

Dive into the research topics of 'New class of order statistic filters for running median estimation'. Together they form a unique fingerprint.

Cite this