Nonlinear Mean Filters and
Their Applications in
Image Filtering and Edge
Detection
CONSTANTINE KOTROPOULOS, MICHAEL PAPPAS, AND IOANNIS PITAS
Department of Informatics
Aristotle University of Thessaloniki
Thessaloniki, Greece
5.1 Introduction
Noise filtering and edge detection are two of the most important tasks in image
processing. Noise removal in images is a particularly difficult task due to the
nonstationary nature of images and the different types of noises (e.g., additive
and signal-dependent noise) that corrupt images.
In this chapter, we study the class of nonlinear mean filters for noise removal
and edge detection. Nonlinear mean filters can be considered as an alternative
to the median filter and its extensions and/or generalizations (e.g., max/median,
multistage median, median hybrid, trimmed mean, L-filters, etc.) [Ast97, Pit90].
All of these filters offer improvements in certain statistical properties at the ex-
pense of a lower ability to remove impulse noise.
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