The geometric and spatial characteristics of pore structures determine the permeability and water retention of soils, which have important effects on soil functional diversity and ecological restoration. Until recently, there have not been tools and methods to visually and quantitatively describe the characteristics of soil pores. To solve this problem, this research reconstructs the geometry and spatial distribution of soil pores by the marching cubes method, texture mapping method and the ray casting method widely used in literature. The objectives were to explore an optimal method for three-dimensional visualization of soil pore structure by comparing the robustness of the three methods on soil CT images with single pore structure and porosity ranging from low (2–5%) to high (12–18%), and to evaluate the reconstruction performance of the three methods with different geometric features. The results demonstrate that there are aliases (jagged edges) and deficiency at the boundaries of the model reconstructed by the marching cubes method and pore volumes are smaller than the ground truth, whereas the results of the texture mapping method lack the details of pore structures. For all the soil images, the ray casting method is preferable since it better preserves the pore characteristics of the ground truth. Furthermore, the ray casting method produced the best soil pore model with higher rendering speed and lower memory consumption. Therefore, the ray casting method provides a more advanced method for visualization of pore structures and provides an optional technique for the study of the transport of moisture and the exchange of air in soil.
This is a preview of subscription content, log in to check access.
Bozorgi M, Lindseth F (2015) GPU-based multi-volume ray casting within VTK for medical applications. Int J Comput Assist Radiol Surg 10(3):293–300CrossRefGoogle Scholar
Elliot TR, Heck RJ (2007) A comparison of optical and X-ray CT technique for void analysis in soil thin section. Geoderma 141(1–2):60–70CrossRefGoogle Scholar
Falconer RE, Houston AN, Otten W, Baveye PC (2012) Emergent behavior of soil fungal dynamics: influence of soil architecture and water distribution. Soil Sci 177(2):111–119CrossRefGoogle Scholar
Hill RL, Horton R, Cruse RM (1985) Tillage effects on soil water retention and pore size distribution of two mollisols 1. Soil Sci Soc Am J 49(5):1264–1270CrossRefGoogle Scholar
Hwang H, Haddad RA (1995) Adaptive median filters: new methods and results. IEEE Trans Image Process 4(4):499–502CrossRefGoogle Scholar
Kopf JP, Hedman LPJ, Szeliski R (2018) Three-dimensional scene reconstruction from set of two dimensional images for consumption in virtual reality. United States Patent Application No. 10/038,894Google Scholar
Krinidis S, Chatzis V (2010) A robust fuzzy local information C-means clustering method. IEEE Trans Image Process 19(5):1328–1337CrossRefGoogle Scholar
Ray H, Pfister H, Silver D, Cook TA (1999) Ray casting architectures for volume visualization. IEEE Trans Vis Comput Graph 5(3):210–223CrossRefGoogle Scholar
Shi Z, Jinyi C (2015) Improved method of volume rendering combined texture mapping with ray casting based on CUDA. Appl Res Comput 32(06):1884–1887Google Scholar
Taina IA, Heck RJ, Elliot TR (2008) Application of X-ray computed tomography to soil science: a literature review. Can J Soil Sci 88(1):1–20CrossRefGoogle Scholar
Thanh CQ, Hai NT (2017) Trilinear interpolation method for reconstruction of 3D MRI brain image. Am J Signal Process 7(1):1–11Google Scholar
Yu X, Fu Y, Lu S (2017) Characterization of the pore structure and cementing substances of soil aggregates by a combination of synchrotron radiation X-ray micro-computed tomography and scanning electron microscopy. Eur J Soil Sci 68(1):66–79CrossRefGoogle Scholar
Zelelew HM, Almuntashri A, Agaian S, Papagiannakis AT (2013) An improved image processing technique for asphalt concrete X-ray CT images. Road Mater Pavement Des 14(2):341–359CrossRefGoogle Scholar
Zhang W, Xu C, Liu J (2018) Image processing method and apparatus for three-dimensional reconstruction. U.S. Patent Application No. 10/043,308Google Scholar