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On Geometric Transformations of Local Structure Tensors
Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
Centre for Image Analysis, SLU, Uppsala, Sweden.
Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
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
2009 (English)In: Tensors in Image Processing and Computer Vision: Part 2 / [ed] S. Aja-Fernandez, R. de Luis Garcia, D. Tao, X. Li, Springer London, 2009, 179-193 p.Chapter in book (Refereed)
Abstract [en]

The structure of images has been studied for decades and the use of local structure tensor fields appeared during the eighties [3, 14, 6, 9, 11]. Since then numerous varieties of tensors and estimation schemes have been developed. Tensors have for instance been used to represent orientation [7], velocity, curvature [2] and diffusion [19] with applications to adaptive filtering [8], motion analysis [10] and segmentation [17]. Even though sampling in non-Cartesian coordinate system are common, analysis and processing of local structure tensor fields in such systems is less developed. Previous work on local structure in non-Cartesian coordinate systems include [21, 16, 1, 18].

Place, publisher, year, edition, pages
Springer London, 2009. 179-193 p.
Series
Advances in Pattern Recognition, ISSN 1617-7916
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:liu:diva-60131DOI: 10.1007/978-1-84882-299-3_8ISBN: 978-1-84882-298-6 (print)ISBN: 978-1-84882-299-3 (print)OAI: oai:DiVA.org:liu-60131DiVA: diva2:355245
Conference
Tensors in Image Processing and Computer Vision
Funder
Swedish Research CouncilVINNOVA
Available from: 2010-10-06 Created: 2010-10-06 Last updated: 2015-08-19Bibliographically approved

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Svensson, BjörnBrun, AndersAndersson, MatsKnutsson, Hans

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CiteExportLink to record
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