Sensitivity of snow density and specific surface area measured by microtomography to different image processing algorithms
Microtomography can measure the X-ray attenuation coefficient in a 3-D volume of snow with a spatial resolution of a few microns. In order to extract quantitative characteristics of the microstructure, such as the specific surface area (SSA), from these data, the greyscale image first needs to be se...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2016-05-01
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| Series: | The Cryosphere |
| Online Access: | http://www.the-cryosphere.net/10/1039/2016/tc-10-1039-2016.pdf |
| _version_ | 1818944098878357504 |
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| author | P. Hagenmuller M. Matzl G. Chambon M. Schneebeli |
| author_facet | P. Hagenmuller M. Matzl G. Chambon M. Schneebeli |
| author_sort | P. Hagenmuller |
| collection | DOAJ |
| description | Microtomography can measure the X-ray attenuation coefficient in a 3-D volume
of snow with a spatial resolution of a few microns. In order to extract
quantitative characteristics of the microstructure, such as the specific
surface area (SSA), from these data, the greyscale image first needs to be
segmented into a binary image of ice and air. Different numerical algorithms
can then be used to compute the surface area of the binary image. In this
paper, we report on the effect of commonly used segmentation and surface area
computation techniques on the evaluation of density and specific surface
area. The evaluation is based on a set of 38 X-ray tomographies of different
snow samples without impregnation, scanned with an effective voxel size of
10 and 18 μm. We found that different surface area computation
methods can induce relative variations up to 5 % in the density and SSA
values. Regarding segmentation, similar results were obtained by sequential
and energy-based approaches, provided the associated parameters were correctly chosen.
The voxel size also appears to affect the values of density and SSA,
but because images with the higher resolution also show the higher noise
level, it was not possible to draw a definitive conclusion on this effect of
resolution. |
| first_indexed | 2024-12-20T07:37:50Z |
| format | Article |
| id | doaj.art-126533b3133548f09daf4fcf3be4c16b |
| institution | Directory Open Access Journal |
| issn | 1994-0416 1994-0424 |
| language | English |
| last_indexed | 2024-12-20T07:37:50Z |
| publishDate | 2016-05-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | The Cryosphere |
| spelling | doaj.art-126533b3133548f09daf4fcf3be4c16b2022-12-21T19:48:14ZengCopernicus PublicationsThe Cryosphere1994-04161994-04242016-05-011031039105410.5194/tc-10-1039-2016Sensitivity of snow density and specific surface area measured by microtomography to different image processing algorithmsP. Hagenmuller0M. Matzl1G. Chambon2M. Schneebeli3Météo-France – CNRS, CNRM-GAME, UMR3589, CEN, 1441 rue de la piscine, 38400 Saint Martin d'Hères, FranceWSL Institute for Snow and Avalanche Research SLF, Fluelastrasse 11, 7260 Davos Dorf, SwitzerlandUniversité Grenoble Alpes, Irstea, UR ETGR, 2 rue de la Papeterie – BP 76, 38402 Saint Martin d'Hères, FranceWSL Institute for Snow and Avalanche Research SLF, Fluelastrasse 11, 7260 Davos Dorf, SwitzerlandMicrotomography can measure the X-ray attenuation coefficient in a 3-D volume of snow with a spatial resolution of a few microns. In order to extract quantitative characteristics of the microstructure, such as the specific surface area (SSA), from these data, the greyscale image first needs to be segmented into a binary image of ice and air. Different numerical algorithms can then be used to compute the surface area of the binary image. In this paper, we report on the effect of commonly used segmentation and surface area computation techniques on the evaluation of density and specific surface area. The evaluation is based on a set of 38 X-ray tomographies of different snow samples without impregnation, scanned with an effective voxel size of 10 and 18 μm. We found that different surface area computation methods can induce relative variations up to 5 % in the density and SSA values. Regarding segmentation, similar results were obtained by sequential and energy-based approaches, provided the associated parameters were correctly chosen. The voxel size also appears to affect the values of density and SSA, but because images with the higher resolution also show the higher noise level, it was not possible to draw a definitive conclusion on this effect of resolution.http://www.the-cryosphere.net/10/1039/2016/tc-10-1039-2016.pdf |
| spellingShingle | P. Hagenmuller M. Matzl G. Chambon M. Schneebeli Sensitivity of snow density and specific surface area measured by microtomography to different image processing algorithms The Cryosphere |
| title | Sensitivity of snow density and specific surface area measured by microtomography to different image processing algorithms |
| title_full | Sensitivity of snow density and specific surface area measured by microtomography to different image processing algorithms |
| title_fullStr | Sensitivity of snow density and specific surface area measured by microtomography to different image processing algorithms |
| title_full_unstemmed | Sensitivity of snow density and specific surface area measured by microtomography to different image processing algorithms |
| title_short | Sensitivity of snow density and specific surface area measured by microtomography to different image processing algorithms |
| title_sort | sensitivity of snow density and specific surface area measured by microtomography to different image processing algorithms |
| url | http://www.the-cryosphere.net/10/1039/2016/tc-10-1039-2016.pdf |
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