New class of order statistic filters for running median estimation

  • Authors:

  • Risto Suoranta;Kari-Pekka Estola

  • Affiliations:

  • Machine Automation Laboratory, Technical Research Centre of Finland, Tampere, Finland;Electronics Laboratory, Technical Research Centre of Finland, Oulu, Finland

  • Venue:
  • ICASSP'93 Proceedings of the 1993 IEEE international conference on Acoustics, speech, and signal processing: digital speech processing - Volume III
  • Year:
  • 1993

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Abstract

In this paper a new low variance median estimator is presented. New order statistic based estimator is derived applying set theoretic approach. It is shown that the proposed Subset Averaged Median Estimate (SAME) shares many good properties with both mean and median operator. Properties COP the new OS-filter are controlled with two parameters: the window length L and the subset size q. A good noise attenuation together with robust behavior can be obtained by selecting appropriate subset length q. Numerical studies shows that SAME filter outperforms ordinary median filter in noise attenuation when applied to signals with various noise characteristics including Laplacian and Gaussian noise.