Sensitivity of snow density and specific surface area measured by microtomography to different image processing algorithms

• Published in: The Cryosphere
• Main Authors: Hagenmuller, P., Matzl, M., Chambon, Guillaume, Schneebeli, M.
• Other Authors: Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales Toulouse (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales Toulouse (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Erosion torrentielle neige et avalanches (UR ETGR (ETNA)), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Institut Fédéral de Recherches sur la Forêt, la Neige et le Paysage (WSL), Institut Fédéral de Recherches Suisse
• Format: Article in Journal/Newspaper
• Language: English
• Published: HAL CCSD 2016
• Subjects: density; microstructure; imagery; snow; IMAGERIE; NEIGE; DENSITE; RAYONNEMENT X; [SDE.IE]Environmental Sciences/Environmental Engineering; [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]; [SDU.STU.ME]Sciences of the Universe [physics]/Earth Sciences/Meteorology; The Cryosphere
• Online Access: https://hal.science/hal-01541664; https://hal.science/hal-01541664/document; https://hal.science/hal-01541664/file/gr2016-pub00054181.pdf; https://doi.org/10.5194/tc-10-1039-2016

[Departement_IRSTEA]Eaux [TR1_IRSTEA]RIVAGE International audience 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 18aEuro-mu m. We found that different surface area computation methods can induce relative variations up to 5aEuro-% 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.