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Density Driven Diffusion
Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.
Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.ORCID iD: 0000-0002-6096-3648
2013 (English)In: 18th Scandinavian Conferences on Image Analysis, 2013, 2013, 718-730 p.Conference paper, Published paper (Refereed)
Abstract [en]

In this work we derive a novel density driven diffusion scheme for image enhancement. Our approach, called D3, is a semi-local method that uses an initial structure-preserving oversegmentation step of the input image.  Because of this, each segment will approximately conform to a homogeneous region in the image, allowing us to easily estimate parameters of the underlying stochastic process thus achieving adaptive non-linear filtering. Our method is capable of producing competitive results when compared to state-of-the-art methods such as non-local means, BM3D and tensor driven diffusion on both color and grayscale images.

Place, publisher, year, edition, pages
2013. 718-730 p.
Series
Lecture Notes in Computer Science, ISSN 0302-9743 (print), 1611-3349 (online) ; 7944
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:liu:diva-90016DOI: 10.1007/978-3-642-38886-6_67ISI: 000342988500067ISBN: 978-3-642-38885-9 (print)ISBN: 978-3-642-38886-6 (print)OAI: oai:DiVA.org:liu-90016DiVA: diva2:611186
Conference
18th Scandinavian Conferences on Image Analysis (SCIA 2013), 17-20 June 2013, Espoo, Finland
Projects
VIDIGARNICSBILDLAB
Available from: 2013-04-08 Created: 2013-03-14 Last updated: 2016-05-04Bibliographically approved

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Åström, FreddieZografos, VasileiosFelsberg, Michael
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