A Robust Algorithm for Denoising Meshes with High-Resolution Details

  • Hanqi Fan
  • Qunsheng Peng
  • Yizhou Yu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7633)


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.


Mesh Denoising High-Resolution Details Face Neighborhood Normal Clustering Normal Filtering 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Hanqi Fan
    • 1
  • Qunsheng Peng
    • 2
  • Yizhou Yu
    • 3
  1. 1.College of Information EngineeringNorth China University of TechnologyBeijingChina
  2. 2.State Key Lab. of CAD&CGZhejiang UniversityHangzhouChina
  3. 3.Dept. of Computer ScienceThe University of HongKongHongKong

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