MRF parameter estimation by an accelerated method
Markov random field (MRF) modelling is a popular method for pattern recognition and computer vision and MRF parameter estimation is of particular importance to MRF modelling. In this paper, a new approach based on MetropolisHastings algorithm and gradient method is presented to estimate MRF parameters. With properly chosen proposal distribution for MetropolisHastings algorithm, the Markov chain constructed by the method converges to stationary distribution quickly and it gives a good estimation result.
parameter estimation markov random field metropolishastings method