This paper proposes a denoising algorithm for 3D cloud model.The algorithm removes outlier noise point based on density filtering and vector information of points.Then, the boundary feature of the model is detected by the tensor voting algorithm and the uniformity of the projection of the nearest neighbors of the data points on the least squares plane, and the features can be enhanced.Finally, the model surface is smoothed by bilateral filtering.The experimental results show that the algorithm can effectively smooth the model and preserve and strengthen the boundary feature of the model to avoid the problem that the smooth operation of the model damages the model features.%提出一种三维点云模型的去噪光滑算法.该算法根据密度滤波和点法矢量信息对离群噪声点进行去除;再利用张量投票算法和数据点的近邻点在其最小二乘平面上投影的分布均匀性检测出模型的边界特征,并对特征实现加强操作;最后,采用双边滤波对模型表面进行光滑.实验表明,该算法能有效地对模型进行去噪光滑处理,且由于对模型边界特征进行了保留与加强,从而避免了模型光滑操作对模型特征造成损害的问题.
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