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Using Channel Representations in Regularization Terms: A Case Study on Image Diffusion
Forschungszentrum Jülich, Germany.
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 Science and Technology, Communications and Transport Systems. Linköping University, The Institute of Technology.
Forschungszentrum Jülich, Germany.
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2014 (English)In: Proceedings of the 9th International Conference on Computer Vision Theory and Applications, SciTePress, 2014, Vol. 1, 48-55 p.Conference paper, Published paper (Refereed)
Abstract [en]

In this work we propose a novel non-linear diffusion filtering approach for images based on their channel representation. To derive the diffusion update scheme we formulate a novel energy functional using a soft-histogram representation of image pixel neighborhoods obtained from the channel encoding. The resulting Euler-Lagrange equation yields a non-linear robust diffusion scheme with additional weighting terms stemming from the channel representation which steer the diffusion process. We apply this novel energy formulation to image reconstruction problems, showing good performance in the presence of mixtures of Gaussian and impulse-like noise, e.g. missing data. In denoising experiments of common scalar-valued images our approach performs competitive compared to other diffusion schemes as well as state-of-the-art denoising methods for the considered noise types.

Place, publisher, year, edition, pages
SciTePress, 2014. Vol. 1, 48-55 p.
Keyword [en]
Image Enhancement, Channel Representation, Channel Smoothing, Diffusion, Energy Minimization
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:liu:diva-103669DOI: 10.5220/0004667500480055ISBN: 978-989-758-003-1 (print)OAI: oai:DiVA.org:liu-103669DiVA: diva2:690190
Conference
9th International Conference on Computer Vision Theory and Applications (VISAPP 2014), 5-8 January 2014, Lisbon, Portugal
Projects
VIDIGARNICS
Available from: 2014-01-22 Created: 2014-01-22 Last updated: 2017-06-01Bibliographically approved

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Åström, FreddieBaravdish, GeorgeFelsberg, Michael

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Åström, FreddieBaravdish, GeorgeFelsberg, Michael
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Center for Medical Image Science and Visualization (CMIV)Computer VisionThe Institute of TechnologyCommunications and Transport Systems
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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
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Output format
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