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Representing local structure using tensors II
Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology. Linköping University, Center for Medical Image Science and Visualization (CMIV).ORCID iD: 0000-0002-9091-4724
Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology. Linköping University, Center for Medical Image Science and Visualization (CMIV).
2011 (English)In: Proceedings of the 17th Scandinavian conference on Image analysis / [ed] Anders Heyden, Fredrik Kahl, Springer, 2011, p. 545-556Conference paper, Published paper (Refereed)
Abstract [en]

Estimation of local spatial structure has a long history and numerous analysis tools have been developed. A concept that is widely recognized as fundamental in the analysis is the structure tensor. However, precisely what it is taken to mean varies within the research community. We present a new method for structure tensor estimation which is a generalization of many of it's predecessors. The method uses filter sets having Fourier directional responses being monomials of the normalized frequency vector, one odd order sub-set and one even order sub-set. It is shown that such filter sets allow for a particularly simple way of attaining phase invariant, positive semi-definite, local structure tensor estimates. We continue to compare a number of known structure tensor algorithms by formulating them in monomial filter set terms. In conclusion we show how higher order tensors can be estimated using a generalization of the same simple formulation.

Place, publisher, year, edition, pages
Springer, 2011. p. 545-556
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 6688
Keywords [en]
higher order, monomial filter, quadrature, structure tensor
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:liu:diva-78924DOI: 10.1007/978-3-642-21227-7_51ISI: 000308543900051ISBN: 978-3-642-21226-0 (print)ISBN: 978-3-642-21227-7 (print)OAI: oai:DiVA.org:liu-78924DiVA, id: diva2:536938
Conference
17th Scandinavian Conference on Image Analysis, SCIA 2011; Ystad; Sweden
Available from: 2012-06-25 Created: 2012-06-25 Last updated: 2018-02-07

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Knutsson, HansWestin, Carl-FredrikAndersson, Mats

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