Imaging and image processing in porous media research

By Anders Kaestner, E. Lehmann, Marco Stampanoni. 2008

235 citations recorded by the source corpus.

Subfields: Geophysics, Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/4dc4c0e50312ac79dc34e71ecd2af210e026566c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Geophysics

1. T. Gebrenegus
2. M. Porter
3. D. Wildenschild
4. Markus Tuller
5. P. Iassonov
6. Andre Peters
7. J. Nimmo

In Mechanical Engineering

1. M. Porter
2. T. Gebrenegus
3. D. Wildenschild
4. Markus Tuller
5. P. Iassonov
6. Martin J. Blunt

Citations in the corpus

• Neutron imaging of hydrogen-rich fluids in geomaterials and engineered porous media: A review (2014, background): “1 to 1 mm length scales in terms of sample size and image resolution (Kaestner et al., 2008).”
• Image processing of multiphase images obtained via X‐ray microtomography: A review (2014, methodology): “Progress in image progressing has kept a comparable pace in terms of new developments in image enhancement, image analysis, and hardware architectures [e.g., Ketcham and Carlson, 2001; Sheppard et al., 2004; Kaestner et al., 2008; Porter and Wildenschild, 2010; Tuller et al., 2013].”
• New Local Thresholding Method for Soil Images by Minimizing Grayscale Intra‐Class Variance (2013, methodology): “Nevertheless, the method requires the selection and application of a filtering step before thresholding, which, according to Kaestner et al. (2008), may have significant effects on segmentation results.”
• Image analysis algorithms for estimating porous media multiphase flow variables from computed microtomography data: a validation study (2010, methodology): “[23] proposed using a gradient image smoothed by a Gaussian filter for c (x, t) in Eq.”
• Segmentation of X‐ray computed tomography images of porous materials: A crucial step for characterization and quantitative analysis of pore structures (2009, methodology): “Although image enhancement can have significant effects on segmentation results, and a detailed investigation of the effect of different filtering methods is of interest [see, e.g., Kaestner et al., 2008], it was not the objective of this study.”