Multibeam Point Cloud Denoising Method Based on Modified Radius Filter

When using radius filters for point cloud filtering of multibeam point clouds, problems such as poor adaptability, difficulty in determining the threshold value, and easy filtering of edge terrain points occur. To address these problems, this paper proposes a multibeam point cloud denoising method that takes into account the edge effect of multibeam bathymetry data . The radius filter is combined with density clustering, and the radius filter is used to filter out the edge noise, while the density clustering is used to recall the mistakenly deleted terrain points. The experimental results show that the proposed method is able to filter edge noise while preserving the edge terrain well. The work in this paper provides a new solution for the automated processing of multibeam point cloud data, which is relevant to the development of multibeam data processing.