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De-noising of SRµCT...
De-noising of SRµCT Fiber Images by Total Variation Minimization
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- Lindblad, Joakim (författare)
- 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
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- Sladoje, Natasa (författare)
- Uppsala universitet,Centrum för bildanalys,Datoriserad bildanalys,Faculty of Technical Sciences, University of Novi Sad,University of Novi Sad
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- Lukic, Tibor (författare)
- University of Novi Sad, Faculty of Technical Sciences
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(creator_code:org_t)
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- ISBN 9781424475421
- Istanbul, Turkey, 2010
- 2010
- Engelska.
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Ingår i: Proceedings of the 20th International Conference on Pattern Recognition (ICPR10). - Istanbul, Turkey. - 1051-4651. - 9781424475421 ; , s. 4621-4624
- Relaterad länk:
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- 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.
Ämnesord
- 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)
Nyckelord
- Image analysis
- Bildanalys
- Computerized Image Analysis
- Datoriserad bildanalys
- Computerized Image Processing
- Datoriserad bildbehandling
Publikations- och innehållstyp
- ref (ämneskategori)
- kon (ämneskategori)
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