Research demonstrates enhanced precision and accuracy in point clouds from terrestrial laser scanning, suggesting improvements in intensity measurements.
Key Points
This research aims to improve the accuracy and precision of signal intensities in point clouds produced by terrestrial laser scanners.
Developed a texture-dependent LiDAR range equation
Utilized a neural network method for signal reflectivity estimation
Evaluated four diverse terrestrial laser scanners
Achieved at least 40% improvement in accuracy of color intensities
Enhanced precision by 97% for individual point intensities
Established a framework for 4D TLS point cloud calibration