J. Weickert,
Theoretical foundations of anisotropic diffusion in image
processing,
Computing, Suppl. 11, 221-236, 1996.
A frequent problem in low-level vision consists of eliminating noise and
small-scale details from an image while still preserving or even enhancing
the edge structure. Nonlinear anisotropic diffusion filtering
may be one possibility to achieve these goals.
The objective of the present paper is to review the author's results on a
scale-space interpretation of a class of diffusion filters
which comprises also several nonlinear anisotropic models.
It is demonstrated that these models - which use an adapted diffusion tensor
instead of a scalar diffusivity - offer advantages over isotropic filters.
Most of the restoration and scale-space properties carry over
from the continuous to the discrete case. Applications are presented ranging
from preprocessing of medical images and postprocessing of fluctuating
numerical data to visualizing quality relevant features for the
grading of wood surfaces and fabrics.
If you would like a hard copy of this article, please e-mail the
name of the publication and your physical mail address to:
Joachim.Weickert@ti.uni-mannheim.de.
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