Proceedings: GI 2000

Anisotropic Feature-Preserving Denoising of Height Fields and Bivariate Data

Mathieu Desbrun, Mark Meyer, Peter Schr, Alan Barr

Proceedings of Graphics Interface 2000: Montréal, Québec, Canada, 15 - 17 May 2000, 145-152

DOI 10.20380/GI2000.20

  • BibTeX

     title = {Anisotropic Feature-Preserving Denoising of Height Fields and Bivariate Data},
     author = {Mathieu Desbrun and Mark Meyer and Peter Schr{ and Alan H. Barr},
     booktitle = {Proceedings of the Graphics Interface 2000 Conference, May 15-17, 2000, Montr{'{e}}al, Qu{'{e}}bec, Canada},
     year = {2000},
     month = {May},
     pages = {145--152},
     url = {}


In this paper, we present an efficient way to denoise bivariate data like height fields, color pictures or vector fields, while preserving edges and other features. Mixing surface area minimization, graph flow, and nonlinear edge-preservation metrics, our method generalizes previous anisotropic diffusion approaches in image processing, and is applicable to data of arbitrary dimension. Another notable difference is the use of a more robust discrete differential operator, which captures the fundamental surface properties. We demonstrate the method on range images and height fields, as well as greyscale or color images.