J. Weickert,
Nonlinear diffusion filtering,
B. Jähne, H. Haußecker, P. Geißler (Eds.),
Handbook on Computer Vision and Applications,
Vol. 2: Signal Processing and Pattern Recognition,
Academic Press, San Diego, 423-450, 1999.
The goal of this chapter is to give an introduction to some
selected key aspects of nonlinear diffusion filters.
After presenting different nonlinear diffusion models some
well-posedness and scale-space results are sketched and
a corresponding discrete framework is described.
Simple numerical schemes are derived that come down to
convolutions with a small space and time variant smoothing
mask. The practically important question of how to select
appropriate filter parameters is discussed in detail, and
extensions of nonlinear diffusion filters to multichannel
images are explained.
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Joachim.Weickert@ti.uni-mannheim.de.
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