XRCT image processing for sand fabric reconstruction

We explore computationally efficient techniques to improve the XRCT image processing of low resolution and very noisy images for use in reconstruction of the fabric of densely packed, natural sand deposits. To this end we evaluate an image preprocessing workflow that incorporates image denoising, si...

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Veröffentlicht in:	Granular matter Jg. 26; H. 1; S. 15
Hauptverfasser:	Tan, Peng, Wijesuriya, Hasitha Sithadara, Sitar, Nicholas
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Berlin/Heidelberg Springer Berlin Heidelberg 01.02.2024 Springer Nature B.V
Schlagworte:	Algorithms Avatars Clay Complex Fluids and Microfluidics Engineering Fluid Dynamics Engineering Thermodynamics Evolution Fields (mathematics) Foundations Geoengineering Grains Granular materials Heat and Mass Transfer Hydraulics Image processing Image quality Image reconstruction Image resolution Image segmentation Industrial Chemistry/Chemical Engineering Materials Science Original Report Physics Physics and Astronomy Sand Sand & gravel Signal to noise ratio Soft and Granular Matter Spatial data Workflow X-rays Hidden Markov random field Non-local mean filter Level sets Image super-resolution Weighted expectation maximization algorithm
ISSN:	1434-5021, 1434-7636
Online-Zugang:	Volltext
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