Multiscale cloth simulation filtering algorithm based on terrain roughness

Dan Zhang; Chuanli Kang; Lei Cai; Xuanhao Li; Shiwei Wang

doi:10.1117/12.3059016

2 January 2025 Multiscale cloth simulation filtering algorithm based on terrain roughness

Dan Zhang, Chuanli Kang, Lei Cai, Xuanhao Li, Shiwei Wang

Author Affiliations +

Proceedings Volume 13514, International Conference on Remote Sensing and Digital Earth (RSDE 2024); 135140H (2025) https://doi.org/10.1117/12.3059016
Event: 2024 International Conference on Remote Sensing and Digital Earth, 2024, Chengdu, China

Abstract

In order to improve the accuracy of airborne LiDAR point cloud filtering algorithm in terrain complex regions, an adaptive cloth simulation filtering algorithm based on terrain roughness is proposed. Firstly, the point cloud data is preprocessed to extract three terrain features: Gaussian curvature, average curvature, and slope. Principal component analysis is used to linearly combine them into a comprehensive terrain roughness. Different grid scales are divided according to the terrain, and different stages are set based on the roughness of each subregion. Different fabric hardness, fabric resolution, and ground point thresholds are set. Finally, fabric simulation filtering is performed. Three sets of data publicly released by the International Society for Photogrammetry and Remote Sensing (ISPRS) are used to validate the algorithm, and the experimental results show that, compared with the traditional cloth simulation filtering algorithm, the class I error, class II error and total error are reduced to achieve a better filtering effect.

(2025) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Dan Zhang, Chuanli Kang, Lei Cai, Xuanhao Li, and Shiwei Wang "Multiscale cloth simulation filtering algorithm based on terrain roughness", Proc. SPIE 13514, International Conference on Remote Sensing and Digital Earth (RSDE 2024), 135140H (2 January 2025); https://doi.org/10.1117/12.3059016

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