Please use this identifier to cite or link to this item: doi:10.22028/D291-26292
Title: PDEs for tensor image processing
Author(s): Weickert, Joachim
Feddern, Christian
Welk, Martin
Burgeth, Bernhard
Brox, Thomas
Language: English
Year of Publication: 2005
Free key words: matrix-valued images
denoising
regularisation
segmentation
DDC notations: 510 Mathematics
Publikation type: Other
Abstract: Methods based on partial differential equations (PDEs) belong to those image processing techniques that can be extended in a particularly elegant way to tensor fields. In this survey paper the most important PDEs for discontinuity-preserving denoising of tensor fields are reviewed such that the underlying design principles becomes evident. We consider isotropic and anisotropic diffusion filters and their corresponding variational methods, mean curvature motion, and selfsnakes. These filters preserve positive semidefiniteness of any positive semidefinite initial tensor field. Finally we discuss geodesic active contours for segmenting tensor fields. Experiments are presented that illustrate the behaviour of all these methods.
Link to this record: urn:nbn:de:bsz:291-scidok-45121
hdl:20.500.11880/26348
http://dx.doi.org/10.22028/D291-26292
Series name: Preprint / Fachrichtung Mathematik, Universität des Saarlandes
Series volume: 143
Date of registration: 25-Jan-2012
Faculty: MI - Fakultät für Mathematik und Informatik
Department: MI - Mathematik
Collections:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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