Robust filtering in a laser scanner point cloud

Authors:
Sebastian Budzan
Affiliations:
Silesian University of Technology, Department of Automatic control, Gliwice, Poland
Venue:
Machine Graphics & Vision International Journal
Year:
2006

Citing 5
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Abstract

This paper presents a new effective and robust approach to noise reduction in a three-dimensional data measurement algorithm. In the literature, there are numerous algorithms for noise reduction. The proposed filter class is based on the nonparametric estimation of the density probability function in a sliding filter sphere. The main idea of the applied algorithm depends is to maximize the distance between points in the three-dimensional space - the nearest neighbors in sliding 3D sphere.