Bi-normal filtering for mesh denoising

Mingqiang Wei, Jinze Yu, Wai Man Pang, Jun Wang, Jing Qin, Ligang Liu, Pheng Ann Heng

Research output: Journal article publicationJournal articleAcademic researchpeer-review

82 Citations (Scopus)


Most mesh denoising techniques utilize only either the facet normal field or the vertex normal field of a mesh surface. The two normal fields, though contain some redundant geometry information of the same model, can provide additional information that the other field lacks. Thus, considering only one normal field is likely to overlook some geometric features. In this paper, we take advantage of the piecewise consistent property of the two normal fields and propose an effective framework in which they are filtered and integrated using a novel method to guide the denoising process. Our key observation is that, decomposing the inconsistent field at challenging regions into multiple piecewise consistent fields makes the two fields complementary to each other and produces better results. Our approach consists of three steps: vertex classification, bi-normal filtering, and vertex position update. The classification step allows us to filter the two fields on a piecewise smooth surface rather than a surface that is smooth everywhere. Based on the piecewise consistence of the two normal fields, we filtered them using a piecewise smooth region clustering strategy. To benefit from the bi-normal filtering, we design a quadratic optimization algorithm for vertex position update. Experimental results on synthetic and real data show that our algorithm achieves higher quality results than current approaches on surfaces with multifarious geometric features and irregular surface sampling.
Original languageEnglish
Article number6822598
Pages (from-to)43-55
Number of pages13
JournalIEEE Transactions on Visualization and Computer Graphics
Issue number1
Publication statusPublished - 1 Jan 2015
Externally publishedYes


  • bi-normal filtering
  • feature preserving
  • Mesh denoising
  • piecewise consistence
  • piecewise smooth surface

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Computer Graphics and Computer-Aided Design


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