Unsupervised Bayesian wavelet domain segmentation using Potts-Markov random field modeling

@article{Brault2005UnsupervisedBW,
  title={Unsupervised Bayesian wavelet domain segmentation using Potts-Markov random field modeling},
  author={Patrice Brault and Ali Mohammad-Djafari},
  journal={J. Electronic Imaging},
  year={2005},
  volume={14},
  pages={043011}
}
We describe a new fully unsupervised image segmentation method based on a Bayesian approach and a Potts-Markov random field (PMRF) model that are performed in the wavelet domain. A Bayesian segmentation model, based on a PMRF in the direct domain, has already been successfully developed and tested. This model performs a fully unsupervised segmentation, on images composed of homogeneous regions, by introducing a hidden Markov model (HMM) for the regions to be classified, and Gaussian… 

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