Estimating the granularity coefficient of a Potts-Markov random field
within an MCMC algorithm

Estimating the granularity coefficient of a Potts-Markov random field within an MCMC algorithm

23 July 2012

Marcelo Pereyra

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Papers citing "Estimating the granularity coefficient of a Potts-Markov random field within an MCMC algorithm"

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Title
Maximum likelihood estimation of regularisation parameters in high-dimensional inverse problems: an empirical Bayesian approach. Part I: Methodology and Experiments A. F. Vidal Valentin De Bortoli Marcelo Pereyra Alain Durmus 79 7 0 26 Nov 2019
A Variational Bayes Approach to Adaptive Radio Tomography Donghoon Lee G. Giannakis 48 6 0 05 Sep 2019
Variational Bayesian Approach and Gauss-Markov-Potts prior model Camille Chapdelaine 18 3 0 28 Aug 2018
Hierarchical Bayesian image analysis: from low-level modeling to robust supervised learning A. Lagrange M. Fauvel S. May N. Dobigeon 13 11 0 01 Dec 2017
Bayesian selection for the l2-Potts model regularization parameter: 1D piecewise constant signal denoising Jordan Frécon N. Pustelnik N. Dobigeon H. Wendt P. Abry 43 11 0 27 Aug 2016
Object Depth Profile and Reflectivity Restoration from Sparse Single-Photon Data Acquired in Underwater Environments Abderrahim Halimi Aurora Maccarone A. Mccarthy S. Mclaughlin G. Buller 44 87 0 22 Aug 2016
Fast unsupervised Bayesian image segmentation with adaptive spatial regularisation Marcelo Pereyra S. Mclaughlin 76 39 0 05 Feb 2015
Joint Segmentation and Deconvolution of Ultrasound Images Using a Hierarchical Bayesian Model based on Generalized Gaussian Priors Ningning Zhao Adrian Basarab Denis Kouamé J. Tourneret 106 47 0 08 Dec 2014
Collaborative sparse regression using spatially correlated supports - Application to hyperspectral unmixing Y. Altmann Marcelo Pereyra J. Bioucas-Dias 119 34 0 29 Sep 2014
Computing the Cramer-Rao bound of Markov random field parameters: Application to the Ising and the Potts models Marcelo Pereyra N. Dobigeon H. Batatia J. Tourneret 44 12 0 18 Jun 2012