DeepAI AI Chat
Log In Sign Up

Bayesian Restoration of Digital Images Employing Markov Chain Monte Carlo a Review

04/11/2005
by   K. P. N. Murthy, et al.
0

A review of Bayesian restoration of digital images based on Monte Carlo techniques is presented. The topics covered include Likelihood, Prior and Posterior distributions, Poisson, Binay symmetric channel, and Gaussian channel models of Likelihood distribution,Ising and Potts spin models of Prior distribution, restoration of an image through Posterior maximization, statistical estimation of a true image from Posterior ensembles, Markov Chain Monte Carlo methods and cluster algorithms.

READ FULL TEXT

page 5

page 21

page 24

page 25

page 26

page 28

page 34

04/02/2019

Fast Bayesian Restoration of Poisson Corrupted Images with INLA

Photon-limited images are often seen in fields such as medical imaging. ...
08/07/2020

A Note on Using Discretized Simulated Data to Estimate Implicit Likelihoods in Bayesian Analyses

This article presents a Bayesian inferential method where the likelihood...
06/25/2021

Posterior Covariance Information Criterion

We introduce an information criterion, PCIC, for predictive evaluation b...
10/18/2017

Bayesian inversion of convolved hidden Markov models with applications in reservoir prediction

Efficient assessment of convolved hidden Markov models is discussed. The...
05/11/2020

Prior choice affects ability of Bayesian neural networks to identify unknowns

Deep Bayesian neural networks (BNNs) are a powerful tool, though computa...
05/28/2020

Bayesian Restoration of Audio Degraded by Low-Frequency Pulses Modeled via Gaussian Process

A common defect found when reproducing old vinyl and gramophone recordin...