摘要
基于多景深融合模型的激光三维图像重构方法难以应付大规模点云大数据处理问题,为解决此问题,研究基于大数据分析技术的激光三维图像重构方法。采用基于MapReduce算法的计算模型处理激光三维图像的点云大数据,使用K-means聚类算法分割处理完成的激光三维图像点云大数据,读取分割完成的点云大数据,通过OpenGL应用程序接口设置数据点的颜色、纹理、贴图等元素,变换视线、视点方向,重构激光三维图像。实验结果表明,所提方法根据原始点云大数据可有效重构激光三维图像,平均用时在11.3ms左右,重构精确度均值高达98.1%,是一种高效、准确的激光三维图像重构方法。
The 3D image reconstruction method based on multi-field depth fusion model is difficult to cope with large-scale point cloud data processing.To solve this problem,a 3D image reconstruction method based on big data analysis is proposed.The point cloud data of the laser three-dimensional image is processed by using the MapReduce algorithm calculation model.The K-means clustering algorithm is used to segment the finished point cloud data of the laser three-dimensional image and read the divided point cloud data.Through the OpenGL application interface,the color,texture,texture,and other elements of the data points are set,and the line of sight and point of view are changed to reconstruct the three-dimensional image of the laser.The experimental results show that the proposed method can effectively reconstruct the laser 3D image based on the original point cloud data,with an average time of 11.3 ms and an average accuracy of 98.1%.It is an efficient and accurate method of laser 3D image reconstruction.
作者
龚皓
干彬
GONG Hao;GAN Bin(Sichuan University of Media and Communications,Chengdu 611745,China)
出处
《激光杂志》
北大核心
2019年第6期83-87,共5页
Laser Journal
基金
四川省教育厅科研项目(No.16ZB0490)
