Please use this identifier to cite or link to this item: doi:10.22028/D291-26290
Title: Adaptive structure tensors and their applications
Author(s): Brox, Thomas
van den Boomgaard, Rein
Lauze, Francois
van de Weijer, Jost
Weickert, Joachim
Mrazek, Pavel
Kornprobst, Pierre
Language: English
Year of Publication: 2005
DDC notations: 510 Mathematics
Publikation type: Other
Abstract: The structure tensor, also known as second moment matrix or Förstner interest operator, is a very popular tool in image processing. Its purpose is the estimation of orientation and the local analysis of structure in general. It is based on the integration of data from a local neighborhood. Normally, this neighborhood is defined by a Gaussian window function and the structure tensor is computed by the weighted sum within this window. Some recently proposed methods, however, adapt the computation of the structure tensor to the image data. There are several ways how to do that. This article wants to give an overview of the different approaches, whereas the focus lies on the methods based on robust statistics and nonlinear diffusion. Furthermore, the dataadaptive structure tensors are evaluated in some applications. Here the main focus lies on optic flow estimation, but also texture analysis and corner detection are considered.
Link to this record: urn:nbn:de:bsz:291-scidok-45091
Series name: Preprint / Fachrichtung Mathematik, Universität des Saarlandes
Series volume: 141
Date of registration: 24-Jan-2012
Faculty: MI - Fakultät für Mathematik und Informatik
Department: MI - Mathematik
Collections:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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