基于点云增强的网格化优化算法

针对三维点云在采用传统泊松算法进行网格化重建时,重建时间较长并且最终重建出的模型存在孔洞和局部细节缺失等问题,提出一种基于点云增强的网格化优化算法.该算法首先通过统计滤波对初始点云进行降噪处理,为了在保证细节特征的基础上提高重建效率,在通过体素滤波进行适当点云降采样的同时利用双三次样条插值进行点云孔洞修复,然后将移动最...

Grid Optimization Algorithm Based on Point Cloud Enhancement

Aiming at the problems of 3D point cloud using traditional Poisson algorithm for grid reconstruction, the reconstruction time is long and the final model has holes and local details missing, a grid optimization algorithm based on point cloud enhancement is proposed. Firstly, the initial point cloud is denoised by statistical filtering. In order to improve the reconstruction efficiency on the basis of guaranteeing the detailed features, the point cloud hole repair is performed using bicubic spline interpolation while performing appropriate point cloud down sampling through voxel filtering. Then, the moving least squares error function is introduced into the point cloud normal calculation to optimize the quality of the point cloud normal vector. The experimental results show that the optimized gridding algorithm takes less time than the traditional Poisson reconstruction algorithm and improves the accuracy of the reconstructed model to a certain extent.