Discrete Markov image modeling and inference on the quadtree

  title={Discrete Markov image modeling and inference on the quadtree},
  author={Jean-Marc Lafert{\'e} and Patrick P{\'e}rez and Fabrice Heitz},
  journal={IEEE transactions on image processing : a publication of the IEEE Signal Processing Society},
  volume={9 3},
Noncasual Markov (or energy-based) models are widely used in early vision applications for the representation of images in high-dimensional inverse problems. Due to their noncausal nature, these models generally lead to iterative inference algorithms that are computationally demanding. In this paper, we consider a special class of nonlinear Markov models which allow one to circumvent this drawback. These models are defined as discrete Markov random fields (MRF) attached to the nodes of a… 

Unsupervised image classification with a hierarchical EM algorithm

  • A. ChardinP. Pérez
  • Computer Science
    Proceedings of the Seventh IEEE International Conference on Computer Vision
  • 1999
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