Median Filters

  • I. Pitas
  • A. N. Venetsanopoulos
Chapter
Part of the The Springer International Series in Engineering and Computer Science book series (SECS, volume 84)

Abstract

A major approach to nonlinear filtering is based on robust estimation and especially on local L-estimators, i.e., on order statistics. The main advantage of this approach is its computational simplicity and speed. Filters based on order statistics.usually have good behavior in the presence of additive white Gaussian noise and long-tailed additive noise. They have good edge preservation properties and they can become adaptive. Thus, they are suitable in a variety of applications where classical linear filters fail, notably in digital image filtering. The best known and most widely used filter based on order statistics is the median filter. Originally, the median was widely used in statistics. It was introduced by Tukey in time series analysis in 1970. Later on, the median filter and its modifications have found numerous applications in digital image processing [2,3,13], in digital image analysis [15,46], in digital TV applications [44,47], in speech processing and coding [20,23], in cepstral analysis [45], and in various other applications. The reason for its success is its good performance and computational simplicity. The theoretical analysis of its deterministic and statistical properties has started at the end of the seventies. A description of the early theoretical results can be found in three very good review chapters in edited books, namely in [4,13,21]. The material of this chapter is based on the recently published results, as well as in the classical work described in [4, 13,21].

Keywords

Median Filter Impulse Noise Impulsive Noise Average Filter Root Signal 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 1990

Authors and Affiliations

  • I. Pitas
    • 1
  • A. N. Venetsanopoulos
    • 2
  1. 1.Aristotelian University of ThessalonikiGreece
  2. 2.University of TorontoCanada

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