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Theoretical Foundations of Anisotropic Diffusion in Image Processing

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Book cover Theoretical Foundations of Computer Vision

Part of the book series: Computing Supplement ((COMPUTING,volume 11))

Abstract

Theoretical Foundations of Anisotropic Diffusion in Image Processing. 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.

This work was supported by “Stiftung Volkswagenwerk” and “Stiftung Rheinland-Pfalz für Innovation”.

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Author information

Authors and Affiliations

  1. Laboratory of Technomathematics, University of Kaiserslautern, P.O. Box 3049, D-67653, Kaiserslautern, Federal Republic of Germany

    J. Weickert

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  1. J. Weickert
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Editors and Affiliations

  1. Institute for Pattern Recognition and Image Processing, Technical University Vienna, Austria

    W. Kropatsch

  2. Computer Science Department, Technical University at Berlin, Germany

    R. Klette

  3. Faculty of Electrical Engineering and Computer Science, University of Ljubljana, Slovenia

    F. Solina

  4. Institute for Informatics, University of Innsbruck, Austria

    R. Albrecht

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© 1996 Springer-Verlag Wien

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Weickert, J. (1996). Theoretical Foundations of Anisotropic Diffusion in Image Processing. In: Kropatsch, W., Klette, R., Solina, F., Albrecht, R. (eds) Theoretical Foundations of Computer Vision. Computing Supplement, vol 11. Springer, Vienna. https://doi.org/10.1007/978-3-7091-6586-7_13

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  • DOI: https://doi.org/10.1007/978-3-7091-6586-7_13

  • Publisher Name: Springer, Vienna

  • Print ISBN: 978-3-211-82730-7

  • Online ISBN: 978-3-7091-6586-7

  • eBook Packages: Springer Book Archive

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