Title :
Noise elimination algorithms for terrestrial 3D laser scanning data based on LS fitting
Author :
Zhao, Xin ; Wu, Kan ; Feng, Jinpeng ; Yu, Qisheng
Author_Institution :
Sch. of Environ. Sci. & Spatial Inf., Chian Univ. of Min. & Technol., Xuzhou, China
Abstract :
In order to avoid the influence on the founding of DEM, noise elimination is an important step for data processing after acquisition. Based on Least Squares theory, reference plane and partial planes are fitted separately. By comparing the relative position of each other, obvious noises are eliminated. Then, second filtering is carried out based on the distance from scattered data points to fitting plane. To prove the feasibility of noise elimination algorithms, experiments are taken, and the outcome indicates that the method is appropriate for gently area, and effect is remarkable.
Keywords :
data acquisition; geophysical image processing; image denoising; least squares approximations; LS fitting; data processing; least squares theory; noise elimination algorithm; partial plane; reference plane; terrestrial 3D laser scanning; Accuracy; Fitting; Laser modes; Noise; Noise reduction; Surface fitting; Three dimensional displays; noise elimination; partial plane; reference plane; terrestrial 3D Laser Scanning;
Conference_Titel :
Multimedia Technology (ICMT), 2011 International Conference on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-61284-771-9
DOI :
10.1109/ICMT.2011.6002723