Image Smoothing and Segmentation by Graph Regularization

  • Sébastien Bougleux
  • Abderrahim Elmoataz
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3804)


We propose a discrete regularization framework on weighted graphs of arbitrary topology, which leads to a family of nonlinear filters, such as the bilateral filter or the TV digital filter. This framework, which minimizes a loss function plus a regularization term, is parameterized by a weight function defined as a similarity measure. It is applicable to several problems in image processing, data analysis and classification. We apply this framework to the image smoothing and segmentation problems.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Sébastien Bougleux
    • 1
  • Abderrahim Elmoataz
    • 2
  1. 1.GREYC CNRS UMR 6072, ENSICAENCaenFrance
  2. 2.LUSAC, Site UniversitaireCherbourg-OctevilleFrance

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