Binary Image Denoising | Ising Model | Gibbs Sampling | MCMC | MRF | Bayesian | python
Binary Image Denoising with Gibbs Sampling (Bayesian inference with MCMC) in an MRF on Ising Model with evidence (observed noisy pixels) - an implementation with python
Pixels have values from the set {-1, +1}
Strength of the edge weights J=1
Markov property in the underlying (Discrete) MRF ensures that it's sufficient to sample according to P(X_i | X_N_i)
a Burn-in period of 100 iterations was used to let the posterior samples converge to true posterior distribution
#imageprocessing #imageprocessingpython #python #computervision #machinelearning #algorithm #mcmc #gibbs #markov