摘要
在气象领域中,多普勒天气雷达探测到的气象数据采用以雷达站点为原点的三维极坐标系进行存储,具有形状不规则、数据量大等特征。Marching Cubes(MC)算法是三维重建中的经典算法,但应用于气象领域时存在重建效率低下和不能直接处理气象数据的缺点。为了实现气象数据的三维重建,基于MC算法提出雷达数据归一化处理与状态标记判别算法NBV-MC。该算法根据雷达基数据文件的特点对其进行归一化预处理,使用雷达基数据构建拟梯形六面体体素,对每一个六面体体素进行状态标记,在遍历六面体体素时动态判别其是否需要处理。实验结果表明,NBV-MC算法不仅解决了由于气象数据具有不规则性而不能直接用于MC算法的问题,而且可以在保证数据真实性和重建效果的情况下有效减少绘制等值面所需要的三角面片数量,提高重建速度。与MC算法相比,NBV-MC算法的重建效率提升了77.70%以上,有利于实时场景交互,便于气象研究人员直接分析雷达数据。
In the field of meteorology,the meteorological data detected by Doppler weather radar is stored in a three-dimensional polar coordinate system with the radar station as the origin,which has characteristics such as irregular shape and large data volume.The Marching Cubes(MC)algorithm is a classic algorithm in 3D reconstruction,but it has the disadvantages of low reconstruction efficiency and inability to directly process meteorological data when applied in the meteorological field.In order to achieve three-dimensional reconstruction of meteorological data,a radar data normalization and state labeling discrimination algorithm NBV-MC is proposed based on the MC algorithm.This algorithm normalizes and preprocesses radar based data files based on their characteristics,constructs trapezoidal hexahedral voxels using radar based data,marks the state of each hexahedral voxel,and dynamically determines whether it needs to be processed when traversing hexahedral voxels.The experimental results show that the NBV-MC algorithm not only solves the problem of being unable to be directly used in the MC algorithm due to the irregularity of meteorological data,but also effectively reduces the number of triangles required to draw contour surfaces while ensuring data authenticity and reconstruction efficiency,and improves reconstruction speed.Compared with the MC algorithm,the reconstruction efficiency of NBV-MC algorithm has increased by more than 77.70%,which is conducive to real-time scene interaction and facilitates meteorological researchers to directly analyze radar data.
作者
魏敏
李足镇
李旭
WEI Min;LI Zuzhen;LI Xu(School of Computer Science,Chengdu University of Information Technology;College of Optoelectronic Technology,Chengdu University of Information Technology,Chengdu 610225,China)
出处
《软件导刊》
2024年第9期181-186,共6页
Software Guide
基金
四川省科技厅项目(2022YFS0568)
四川省科技计划项目(2023YFQ0072)。
