基于图像压缩的震损结构三维模型快速重建方法

针对基于数字图像的大尺度三维结构模型建模时间过长的问题，提出了利用图像压缩算法对震损结构三维模型快速重建的方法。首先，拍摄得到结构的原始图像；其次，利用主成分分析算法压缩图像；最后，基于处理后的图像对结构三维模型进行重建。为验证提出方法的有效性，对一个混凝土试块，受损的剪力墙试验模型和实际单体建筑进行图像采集，利用论文提出的方法进行图像压缩和三维建模。结果表明:将主成分分析算法引入到三维重建技术中，可以在不影响结构模型精确性的基础上极大地减少模型重建时间，与传统的三维模型建模时间相比，本文提出的方法结构三维建模所需的时间至少可降低30%。

Fast reconstruction of three-dimensional models of seismic-damaged structures based on image compression

The method of reconstructing the three-dimensional models of seismic-damaged structures rapidly based on image compression is proposed to solve the problem which is that the process of 3D reconstruction of large-scale structures based on digital images is time-consuming.First，the original structure image is taken，then the image is compressed by Principal Component Analysis（PCA）algorithm，and finally the 3D model of the structure is reconstructed based on the processed image. To verify the effectiveness of the proposed method，the images of a concrete block，a damaged shear wall and an actual single building are collected and their 3D models are reconstructed from compressed images by the proposed method. The experimental results show that the method of introduction of the algorithm of principal component analysis into the 3D reconstruction technique can greatly reduce the time of 3D reconstruction without affecting the accuracy of the models. Compared with the time of traditional methods of 3D reconstruction，the time of 3D reconstruction of structures based on the proposed method can be reduced by 30% at least.