Feature-preserving kernel diffusion for surface denoising

  • Authors:
  • Khaled Tarmissi;A. Ben Hamza

  • Affiliations:
  • Concordia Institute for Information Systems Engineering, Concordia University, Montréal, QC, Canada;Concordia Institute for Information Systems Engineering, Concordia University, Montréal, QC, Canada

  • Venue:
  • ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
  • Year:
  • 2009

Quantified Score

Hi-index 0.00

Visualization

Abstract

We present a 3D mesh denoising method based on kernel density estimation. The proposed approach is able to reduce the oversmoothing effect and effectively remove undesirable noise while preserving prominent geometric features of a 3D mesh such as curved surface regions, sharp edges, and fine details. The experimental results demonstrate the effectiveness of the proposed approach in comparison to existing mesh denoising techniques.