# Discrete Markov image modeling and inference on the quadtree

@article{Lafert2000DiscreteMI, 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}, year={2000}, volume={9 3}, pages={ 390-404 } }

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…

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