We propose in this paper a robust surface mesh denoising method that can effectively remove mesh noise while faithfully preserving sharp features. This method utilizes surface fitting and projection techniques. Sharp features are preserved in the surface fitting algorithm by considering an anisotropic neighborhood of each vertex detected by the normal-weighted distance. In addition, to handle the mesh with a high level of noise, we perform a pre-filtering of surface normals prior to the neighborhood searching. A number of experimental results and comparisons demonstrate the excellent performance of our method in preserving important surface geometries while filtering mesh noise.

中文翻译：

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通过各向异性表面拟合进行特征保留网格去噪

我们在本文中提出了一种鲁棒的表面网格去噪方法，可以有效去除网格噪声，同时忠实地保留锐利特征。该方法利用表面拟合和投影技术。通过考虑由法线加权距离检测到的每个顶点的各向异性邻域，在表面拟合算法中保留了尖锐特征。此外，为了处理具有高噪声水平的网格，我们在邻域搜索之前对表面法线进行预过滤。许多实验结果和比较证明了我们的方法在过滤网格噪声的同时保留重要表面几何形状的出色性能。