【摘要】 基于2维图像的砂岩3维结构重建中,确定3维结构的自相关函数分布是一个难题。基于傅里叶变换的重建方法利用经验公式确定重建3维结构的自相关函数,但重建结果的误差较大。该文提出以3维结构的自相关分布作为粒子的位置,以3维结构与2维图像统计特征的误差作为粒子的适应度,用粒子群优化确定重建问题的最优解。与基于傅里叶变换重建算法相比,该方法得到的重建结果统计特征与2维图像的相似度明显提高。与经典的模拟退火重建算法相比,达到相同的重建效果,基于粒子群优化的重建方法具有更高的效率,具有良好的实际应用价值。更多还原

【Abstract】 In the progress of 3-Dimensional(3D) reconstruction from 2-Dimensional(2D) rock slice images,it is difficult to determine the auto-correlation function of the 3D microstructure.The reconstruction method based on the fast Fourier transforms uses empirical formula to predict the auto-correlation function of the 3D microstructure,but the reconstruction result has relative large error.Another reconstruction method based on Particle Swarm Optimization(PSO) to optimize the reconstruction progress is proposed in this paper.This method sets autocorrelation function of 3D microstructure as the position of particles,calculates fitness value as the error between 3D microstructure and 2D image.Compared with FFT reconstruction method,the similarity between reconstruction results and 2D image is greatly improved.Compared with simulated annealing method,the proposed method reaches similar reconstruction result.The reconstruction method based on PSO is more efficient and can be well applied to the image reconstruction.更多还原