Open Access

ARTICLE

Fine-Grained Point Cloud Intensity Correction Modeling Method Based on Mobile Laser Scanning

Xu Liu¹, Qiujie Li^1,*, Youlin Xu¹, Musaed Alhussein², Khursheed Aurangzeb^2,*, Fa Zhu¹

1 College of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing, 210037, China
2 Department of Computer Engineering, College of Computer and Information Sciences, King Saud University, P.O. Box 51178, Riyadh, 11543, Saudi Arabia

* Corresponding Authors: Qiujie Li. Email: ; Khursheed Aurangzeb. Email:

Computers, Materials & Continua 2025, 83(1), 575-593. https://doi.org/10.32604/cmc.2025.062445

Received 18 December 2024; Accepted 01 February 2025; Issue published 26 March 2025

Abstract

The correction of Light Detection and Ranging (LiDAR) intensity data is of great significance for enhancing its application value. However, traditional intensity correction methods based on Terrestrial Laser Scanning (TLS) technology rely on manual site setup to collect intensity training data at different distances and incidence angles, which is noisy and limited in sample quantity, restricting the improvement of model accuracy. To overcome this limitation, this study proposes a fine-grained intensity correction modeling method based on Mobile Laser Scanning (MLS) technology. The method utilizes the continuous scanning characteristics of MLS technology to obtain dense point cloud intensity data at various distances and incidence angles. Then, a fine-grained screening strategy is employed to accurately select distance-intensity and incidence angle-intensity modeling samples. Finally, based on these samples, a high-precision intensity correction model is established through polynomial fitting functions. To verify the effectiveness of the proposed method, comparative experiments were designed, and the MLS modeling method was validated against the traditional TLS modeling method on the same test set. The results show that on Test Set 1, where the distance values vary widely (i.e., 0.1–3 m), the intensity consistency after correction using the MLS modeling method reached 7.692 times the original intensity, while the traditional TLS modeling method only increased to 4.630 times the original intensity. On Test Set 2, where the incidence angle values vary widely (i.e., 0°–80°), the MLS modeling method, although with a relatively smaller advantage, still improved the intensity consistency to 3.937 times the original intensity, slightly better than the TLS modeling method’s 3.413 times. These results demonstrate the significant advantage of the modeling method proposed in this study in enhancing the accuracy of intensity correction models.

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Keywords

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