Denoising 3D models with attributes using soft thresholding

Michaël Roy, Sebti Foufou, Frédéric Truchetet

Research output: Contribution to journalConference article

Abstract

Recent advances in scanning and acquisition technologies allow the construction of complex models from real world scenes. However, the data of those models are generally corrupted by measurement errors. This paper describes an efficient single pass algorithm for denoising irregular meshes of scanned 3D model surfaces. In this algorithm, the frequency content of the model is assessed by a multiresolution analysis that requires only l-ring neighbourhood without any particular parameterization of the model faces. Denoising is achieved by applying the soft thresholding method to the detail coefficients given by the multiresolution analysis. Our method is suitable for irregular meshes with appearance attributes such as normal vectors and colors. Some results of real world scene models denoised with the proposed algorithm are given to demonstrate its efficiency.

Original languageEnglish (US)
Article number19
Pages (from-to)139-147
Number of pages9
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume5607
DOIs
StatePublished - Dec 1 2004
EventWavelet Applications in Industrial Processing II - Philadelphia, PA, United States
Duration: Oct 27 2004Oct 28 2004

Keywords

  • Denoising
  • Irregular mesh
  • Multiresolution analysis
  • Soft thresholding
  • Surface attributes

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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