De-noising of SRµCT Fiber Images by Total Variation Minimization

Joakim Lindblad; Nataša Sladoje; Tibor Lukic

doi:10.1109/ICPR.2010.1116

De-noising of SRµCT Fiber Images by Total Variation Minimization

Joakim Lindblad
, Nataša Sladoje
, Tibor Lukic

Publikation: Kapitel i bok/rapport/konferenshandling › Konferensartikel i proceedings › Peer review

Sammanfattning

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

Originalspråk	Engelska
Titel på värdpublikation	2010 20th International Conference on Pattern Recognition
Förlag	The Institute of Electrical and Electronics Engineers, Inc.
Sidor	4621-4624
Antal sidor	4
ISBN (tryckt)	978-1-4244-7542-1
DOI	https://doi.org/10.1109/ICPR.2010.1116
Status	Publicerad - 2010

Publikationsserier

Serie	Proceedings - International Conference On Pattern Recognition
ISSN	1051-4651

Åtkomst av dokument

10.1109/ICPR.2010.1116

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abstract = "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",

author = "Joakim Lindblad and Nata{\v s}a Sladoje and Tibor Lukic",

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De-noising of SRµCT Fiber Images by Total Variation Minimization. / Lindblad, Joakim; Sladoje, Nataša; Lukic, Tibor.
2010 20th International Conference on Pattern Recognition. The Institute of Electrical and Electronics Engineers, Inc., 2010. s. 4621-4624 (Proceedings - International Conference On Pattern Recognition).

Publikation: Kapitel i bok/rapport/konferenshandling › Konferensartikel i proceedings › Peer review

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AU - Lindblad, Joakim

AU - Sladoje, Nataša

AU - Lukic, Tibor

PY - 2010

Y1 - 2010

N2 - 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

AB - 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

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DO - 10.1109/ICPR.2010.1116

M3 - Conference paper in proceedings

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T3 - Proceedings - International Conference On Pattern Recognition

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BT - 2010 20th International Conference on Pattern Recognition

PB - The Institute of Electrical and Electronics Engineers, Inc.

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