A Research on MBES data classification denoising algorithm based on Octree index

4th International Conference on Advances in Energy Resources and Environment Engineering

能源学;生态环境科学

Li, Xiaokai^1 ; Zhang, Fan^1 ; Wang, Yue^1 ; Chen, Huanjian^1

College of Geomatics, Shandong University of Science and Technology, Qingdao, Shandong

266590, China^1

关键词: Bayesian estimation theory;    Data classification;    Data de-noising;    De-noising algorithm;    Distribution characteristics;    Ground noise;    Multi-beam echo sounders;    Point cloud;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/237/2/022011/pdf
DOI  :  10.1088/1755-1315/237/2/022011

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

For the Multi-Beam Echo Sounder (MBES) data denoising problem, the noise is divided into near-ground noise and outlier noise away from the seabed. The algorithm in this paper considers the spatial distribution characteristics of noise and removes two kinds of noise by initial denoising and precise denoising. The algorithm first uses the octree index to organize the point cloud and removes the outlier noise. Then combined with Bayesian estimation theory and statistical methods to remove near-ground noise. This paper designs experiments to process MBES data and compare it with the statistical filter of PCL point cloud library. The experimental results show that compared with the PCL statistical filter, the algorithm used in this paper has good denoising effect and can better preserve the information such as regional boundaries.