Robust Feature-Preserving Mesh Denoising Based on Consistent Subneighborhoods

—In this paper, we introduce a feature-preserving denoising algorithm. It is built on the premise that the underlying surface of a noisy mesh is piecewise smooth, and a sharp feature lies on the intersection of multiple smooth surface regions. A vertex close to a sharp feature is likely to have a neighborhood that includes distinct smooth segments. By defining the consistent subneighborhood as the segment whose geometry and normal orientation most consistent with those of the vertex, we can completely remove the influence from neighbors lying on other segments during denoising. Our method identifies piecewise smooth subneighborhoods using a robust density-based clustering algorithm based on shared nearest neighbors. In our method, we obtain an initial estimate of vertex normals and curvature tensors by robustly fitting a local quadric model. An anisotropic filter based on optimal estimation theory is further applied to smooth the normal field and the curvature tensor field. This is f...

• Type: Journal
• Year: 2010
• Where: TVCG
• Authors: Hanqi Fan, Yizhou Yu, Qunsheng Peng
• Keywords: Consistent Subneighborhood, Piecewise Smooth, Sharp Features, TVCG 2010