Affiliations: [a] School of Engineering, Sun Yat-Sen University, Guangzhou, Guangdong, China
| [b] Guangdong Construction Polytechnic, Guangzhou, Guangdong, China
Correspondence:
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Corresponding author. Yu Liang, School of Engineering, Sun Yat-Sen University, Guangzhou 510006, Guangdong, China. E-mail: liangyu25@mail.sysu.edu.cn.
Abstract: The mechanical properties of the geo-materials are greatly affected by the internal micro structure system. Multi-scale modelling and analysis are considered as an effective tool for revealing the mechanical process. Aiming at the problems of the light intensity decrease and the uneven illumination, a Retinex scale optimized image enhancement algorithm is proposed, based on the light reflection model and Retinex theory. Based on the Retinex theory, a Monte-Carlo random geometric numerical model of the microstructure is established, with some soil specimens in South China as the study object. After that, three-axis consolidation process of soft soil materials are simulated, which are compared with the experimental data. The results show that: the Retinex scale optimized image enhancement algorithm can accurately estimate the illumination component, eliminate the influence of the uneven illumination, improve the contrast of image and retain the details of the microstructure simultaneously. The random field model with this algorithm is simple and effective, the image becomes clearer, and the contrast ratio is improved, after using Retinex algorithm to enhance the CT image of rock and soil. The threshold segmentation of the enhanced image, and the fidelity between the enhanced image and the original image, are higher than that of the homomorphic filtering method and histogram equalization method, which explained that the algorithm could preserve the microstructure information of the micro image well. The result of numerical simulation is similar with the one obtained from conventional three axis consolidation test, which proves that the simulation result is reliable.
Keywords: Rock and soil materials, microstructure, random field, scale optimization, Retinex algorithm
