Abstract
The acquisition of point cloud data by mobile laser scanning (MLS) includes not only the information about the 3D geometry of the object but also the intensity from the scanned object. However, due to the influence of various factors, there is a large deviation between the intensity and the spectral reflection characteristics of the scanned object. Intensity correction should be carried out before this method is applied to object recognition. A new point cloud intensity correction method for 2D MLS that was developed by combining theoretical derivation with empirical correction is proposed in this paper. First, based on the LiDAR formula, the main factors influencing MLS intensity are investigated, and a distance piecewise polynomial and an incident angle cosine polynomial are adopted to obtain the intensity correction model of UTM-30LX 2D LiDAR on a diffuse reflector plate. Second, according to the scan pattern, a 2D scan grid is constructed to organize the MLS intensity, and a new method of spherical neighborhood search fitting plane is proposed to accurately calculate the cosine of the incident angle. Finally, the obtained intensity correction model is utilized to correct the MLS intensity of a wall. Two groups of verification experiments are carried out on single sites and multiple sites to test the effect of the intensity correction model. Overall, the improvements in intensity consistency range from 70% to 92.7% after correction within the tested ranges of distance and incident angles [0.52 m-5.34 m, 0°-74°]. The results indicate that the proposed intensity correction model yields highly accurate fitting and can effectively remove the deviation in MLS intensity caused by the distance and incident angle.
Highlights
Light detection and ranging (LiDAR), a type of noncontact active remote sensing sensor, can quickly scan highresolution and high-precision 3D point cloud data on the target surface
A new point cloud intensity correction method for 2D mobile laser scanning (MLS) based on theoretical derivation and empirical correction is proposed to solve the problem that intensity information cannot be directly used for target recognition
Based on the diffuse reflection Lambert body of the same target reflectance, the intensity correction model of the piecewise distance polynomial and incident angle cosine polynomial is adopted, and the model parameters are calculated by experiments
Summary
Light detection and ranging (LiDAR), a type of noncontact active remote sensing sensor, can quickly scan highresolution and high-precision 3D point cloud data on the target surface. The intensity corresponds to the coordinate information one-to-one without registration and has the feature of pixel-level fusion. It represents the reflection spectral characteristics of the object target to the laser and can be used as an important feature of target classification [3,4,5]. Due to the influence of various factors, such as scanner characteristics, atmospheric transmission characteristics, target surface parameters, and data acquisition parameters, there is a large deviation between the intensity and the spectral reflection characteristics of the object target. It is necessary to eliminate the influence of various factors through correction [6,7,8]
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