A signal processing approach to fair surface design
SIGGRAPH '95 Proceedings of the 22nd annual conference on Computer graphics and interactive techniques
Implicit fairing of irregular meshes using diffusion and curvature flow
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
Anisotropic geometric diffusion in surface processing
Proceedings of the conference on Visualization '00
Anisotropic diffusion of surfaces and functions on surfaces
ACM Transactions on Graphics (TOG)
Polyhedral Surface Smoothing with Simultaneous Mesh Regularization
GMP '00 Proceedings of the Geometric Modeling and Processing 2000
Non-iterative, feature-preserving mesh smoothing
ACM SIGGRAPH 2003 Papers
ACM SIGGRAPH 2003 Papers
Bilateral Filtering for Gray and Color Images
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Fuzzy Vector Median-Based Surface Smoothing
IEEE Transactions on Visualization and Computer Graphics
Mesh editing with poisson-based gradient field manipulation
ACM SIGGRAPH 2004 Papers
Feature-Preserving Mesh Denoising via Bilateral Normal Filtering
CAD-CG '05 Proceedings of the Ninth International Conference on Computer Aided Design and Computer Graphics
Robust Feature-Preserving Mesh Denoising Based on Consistent Subneighborhoods
IEEE Transactions on Visualization and Computer Graphics
Fast and Effective Feature-Preserving Mesh Denoising
IEEE Transactions on Visualization and Computer Graphics
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In this paper, we present a robust and efficient mesh denoising algorithm which preserves high-resolution details very well. Our method is a three-stage algorithm. Firstly, we modify a robust density-based clustering method and apply it to the face neighborhood of each triangular face to extract a subset of neighbors which belong to the same cluster as the central face. Because the faces within the extracted subset are not distributed across high-resolution details, we filter the central face normal iteratively within this subset to remove noise and preserve such details as much as possible. Finally, vertex positions are updated to be consistent with the filtered face normals using a least-squares formulation. Experiments on various types of meshes indicate that our method has advantages over previous surface denoising methods.