Fast Edge Preserving Picture Recovery by Finite Markov Random Fields

  • Michele Ceccarelli
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3617)


We investigate the properties of edge preserving smoothing in the context of Finite Markov Random Fields (FMRF). Our main result follows from the definition of discontinuity adaptive potential for FMRF which imposes to penalize linearly image gradients. This is in agreement with the Total Variation based regularization approach to image recovery and analysis. We also report a fast computational algorithm exploiting the finiteness of the field, it uses integer arithmetic and a gradient descent updating procedure. Numerical results on real images and comparisons with anisotropic diffusion and half-quadratic regularization are reported.


IEEE Transaction Conjugate Gradient Algorithm Recovery Algorithm Smoothing Process Total Variation Norm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Michele Ceccarelli
    • 1
  1. 1.Research Centre on Software Technologies-RCOSTUniversity of SannioBeneventoItaly

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