Abstract
A point cloud data filtering method of laser radar imaging based on classification of curvature is investigated to resolve the deficiencies of the massive 3D point cloud data model filtering using single method. This method divides the region of point cloud data model by the average Gaussian curvature value in neighbor of the sampling point, and then the adaptive median filtering and adaptive bilateral filtering method are used for different region types. Static and dynamic targets are adopted respectively in simulation experiments, experiments show the method can effectively remove the noise of targets under the different motion states, it can also keep details of point cloud data models, and this method has better filtering performance compared with the single filtering method.
Supported by The National Nature Science Foundation of China (Grant No. 61261160497).
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© 2016 Springer Science+Business Media Singapore
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Yuan, X., Li, Q. (2016). A Filtering Method of Laser Radar Imaging Based on Classification of Curvature. In: Zhang, L., Song, X., Wu, Y. (eds) Theory, Methodology, Tools and Applications for Modeling and Simulation of Complex Systems. AsiaSim SCS AutumnSim 2016 2016. Communications in Computer and Information Science, vol 644. Springer, Singapore. https://doi.org/10.1007/978-981-10-2666-9_25
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DOI: https://doi.org/10.1007/978-981-10-2666-9_25
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