Open AccessResearch on denoising algorithm of 3D point cloud data based on curvature change
Author(s) -
Shigang Wang,
Jing He,
Shuping Peng,
Xueshan Gao
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/768/7/072041
Subject(s) - noise reduction , algorithm , point cloud , feature (linguistics) , video denoising , computer science , curvature , non local means , artificial intelligence , cloud computing , mathematics , image denoising , geometry , philosophy , linguistics , object (grammar) , video tracking , multiview video coding , operating system
This paper focuses on the algorithm of denoising for 3D point cloud data in 3D modelling technology. Through the problem that it is difficult to retain the feature points of traditional 3D point cloud data denoising and the denoising amplitude is too large, taking the change of Gaussian curvature value of sampling points as the basis of region division, an improved denoising algorithm based on the combination of median denoising algorithm and bilateral denoising algorithm is proposed The algorithm is implemented and simulated by pseudo code. The simulation results show that the 3D point cloud data denoising algorithm based on curvature change not only has a higher ability in denoising effect and feature retention effect, but also has a greater advantage in the execution time of the denoising algorithm.