Method for denoising lidar point cloud data of an isolation switch

Hongdong Lin; Fupeng Li; Yuhuan Jiang; Xingsheng Xie

doi:10.1117/12.3029126

6 May 2024 Method for denoising lidar point cloud data of an isolation switch

Hongdong Lin, Fupeng Li, Yuhuan Jiang, Xingsheng Xie

Proceedings Volume 13107, Fourth International Conference on Sensors and Information Technology (ICSI 2024); 1310737 (2024) https://doi.org/10.1117/12.3029126
Event: Fourth International Conference on Sensors and Information Technology (ICSI 2024), 2024, Xiamen, China

Abstract

This article presents an improved method for denoising point clouds that combines the DBSCAN clustering algorithm and filtering. Firstly, a LiDAR is deployed in the target acquisition area to collect initial point cloud data. Then, the improved DBSCAN clustering algorithm is used to classify the point cloud data while removing scattered data points, resulting in a preliminary denoised point cloud dataset. Finally, the improved bilateral filtering algorithm is applied to process the preliminary denoised point cloud dataset, resulting in accurate point cloud data.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Hongdong Lin, Fupeng Li, Yuhuan Jiang, and Xingsheng Xie "Method for denoising lidar point cloud data of an isolation switch", Proc. SPIE 13107, Fourth International Conference on Sensors and Information Technology (ICSI 2024), 1310737 (6 May 2024); https://doi.org/10.1117/12.3029126

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