一种顾及水下地形特点的多波束点云去噪算法

A Multi-Beam Point Cloud Denoising Algorithm Considering Underwater Topographic Features

针对包含大量噪声的多波束点云去噪问题,顾及水下地形特点设计算法去除近地表噪声和明显离群噪声。算法基于RANSAC算法思想拟合局部平面,结合统计分析方法去除给定阈值范围之外的噪声;结合共面法矢量特征预判去除离群面并探测保留陡坡等高程梯度变化明显的敏感地形。通过减少点云数据检索次数、使用哈希表等方式优化算法,提高执行效率。能够保证地形一致性的同时较好地保留区域边界等信息。最后,设计实验对多波束点云去噪结果达到预期,并对实验结果进行探讨提出后续研究方向。

Aiming at the problem of multi-beam point cloud denoising with large amount of noise, the designed algorithm of underwater terrain is used to remove near-surface noise and obvious outlier noise. The algorithm is based on the RANSAC algorithm to fit the local plane, and the statistical analysis method is used to remove the noise outside the given threshold. The coplanar vector feature is used to remove the outliers and detect the sensitive terrain with obvious gradient. By reducing the number of point cloud data retrieval, using a hash table to optimize the algorithm to improve the efficiency of the implementation, the terrain consistency can be guaranteed at the same time the regional boundaries and other information can be better retained. Finally, the designed experiment is used to denoise the multi-beam point cloud, and the result is expected. The experimental results are discussed and the research direction is put forward.