Order statistics in digital image processing

  • Pitas I
  • Venetsanopoulos A
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Abstract

A family of nonlinear filters based on order statistics is
presented. A mathematical tool derived through robust estimation theory,
order statistics has allowed engineers to develop nonlinear filters with
excellent robustness properties. These filters are well suited to
digital image processing because they preserve the edges and the fine
details of an image much better than conventional linear filters. The
probabilistic and deterministic properties of the best known and most
widely used filter in this family, the median filter, are discussed. In
addition, the authors consider filters that, while not based on order
statistics, are related to them through robust estimation theory. A
table that ranks nonlinear filters under a variety of performance
criteria is included. Most of the topics treated are very active
research areas, and the applications are varied, including HDTV,
multichannel signal processing of geophysical and ECG/EEG data, and a
variety of telecommunications applications

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Authors

  • I. Pitas

  • a.N. Venetsanopoulos

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