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De-noising of SRµCT Fiber Images by Total Variation Minimization

Lindblad, Joakim (author)
Swedish University of Agricultural Sciences,Sveriges lantbruksuniversitet,Uppsala universitet,Centrum för bildanalys,Datoriserad bildanalys,Mathematical Institute, Serbian Academy of Sciences and Arts, Belgrade, Serbia,,Centre for Image Analysis
Sladoje, Natasa (author)
Uppsala universitet,Centrum för bildanalys,Datoriserad bildanalys,Faculty of Technical Sciences, University of Novi Sad,University of Novi Sad
Lukic, Tibor (author)
University of Novi Sad, Faculty of Technical Sciences
 (creator_code:org_t)
 
ISBN 9781424475421
Istanbul, Turkey, 2010
2010
English.
In: Proceedings of the 20th International Conference on Pattern Recognition (ICPR10). - Istanbul, Turkey. - 1051-4651. - 9781424475421 ; , s. 4621-4624
  • Conference paper (peer-reviewed)
Abstract Subject headings
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  • SRμCT images of paper and pulp fiber materials are characterized by a low signal to noise ratio. De-noising is therefore a common preprocessing step before segmentation into fiber and background components. We suggest a de-noising method based on total variation minimization using a modified Spectral Conjugate Gradient algorithm. Quantitative evaluation performed on synthetic 3D data and qualitative evaluation on real 3D paper fiber data confirm appropriateness of the suggested method for the particular application.

Subject headings

NATURVETENSKAP  -- Data- och informationsvetenskap -- Datorseende och robotik (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Vision and Robotics (hsv//eng)
LANTBRUKSVETENSKAPER  -- Lantbruksvetenskap, skogsbruk och fiske -- Skogsvetenskap (hsv//swe)
AGRICULTURAL SCIENCES  -- Agriculture, Forestry and Fisheries -- Forest Science (hsv//eng)

Keyword

Image analysis
Bildanalys
Computerized Image Analysis
Datoriserad bildanalys
Computerized Image Processing
Datoriserad bildbehandling

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ref (subject category)
kon (subject category)

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