Parameter estimation in 2D fields

The problem of estimating the parameters of noncausal finite lattice Gauss Markov random fields is addressed. It is shown how the structure of the potential matrix (the inverse of the field covariance matrix) can be used to specify the valid parameter space and formulate a computationally practical maximum likelihood estimation procedure. A modification that enables this to generate accurate parameter estimates from noisy data is provided.<<ETX>>