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《Nanotechnology and Precision Engineering》 2012-01
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Denoising Approach of High Density Point Clouds Based on Mixed Classification of Curvature Features

GE Bao-zhen1,2,XIANG Chen1,2,TIAN Qing-guo1,2,PENG Bo1,2(1.School of Precision Instruments and Opto-Electronics Engineering,Tianjin University,Tianjin 300072,China; 2.Key Laboratory of Opto-Electronics Information Technology of Ministry of Education,Tianjin University,Tianjin 300072,China)  
In order to resolve the existing problems in algorithms for smoothing and denoising complex point clouds,an effective and feature-preserving 3D point-cloud smoothing method based on the mixed curvature feature classification was presented.It combined local plane projection and bilateral denoising method.The local curvature feature of each point was evaluated by principal component analysis.According to the features,the point clouds were divided into plane,sub-featured and rich-featured classes and linearly mixed type.With the different neighborhood types,the combination of the plane projection smoothing method for plane class and the variable parameter bilateral filtering method for sub-featured and rich-featured classes were applied.The algorithm presented has been applied to process point-cloud data sets obtained by a high resolution 3D human body laser scanner.The experimental results show that the proposed method can effectively remove noise and preserve geometric features while can significantly simplify the normal direction adjustment process.
【Fund】: 国家自然科学基金资助项目(61027012 61177002)
【CateGory Index】: TP391.41
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3 CHEN Zhong;DUAN Li-ming;WU Zhi-fang;ICT Research Center,Key Laboratory of Optoelectronic Technology and Systems,Ministry of Education,Chongqing University;College of Mechanical Engineering,Chongqing University;China Three Design Industry Engineering Corporation;;Removal method for stair-stepped artifacts based on improved spherical cover algorithm[J];计算机集成制造系统;2014-02
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7 Hua Gang1,2),Liu Fang3),Lin Hai1),and Sun Jinguang2)1)(State Key Laboratory of CAD & CG,Zhejiang University,Hangzhou 310058)2)(School of Electronic and Information Engineering,Liaoning Technique University,Huludao 125105)3)(Software Technology Institute,Dalian Jiaotong University,Dalian 116052);Multi-attribute Trilateral Filtering for Seismic Data[J];计算机辅助设计与图形学学报;2011-06
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【Co-references】
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