On the parameter estimation of 2-D moving average random fields

The problem of estimating the parameters of 2-D homogeneous moving average (MA) random fields only from output measurements is addressed. A novel computationally efficient algorithm for the estimation of the parameters of a minimum-phase 2-D MA model with a nonsymmetric half-plane (NSHP) region of support (ROS) is proposed. Using the 2-D spectral factorization, relationship between the NSHP MA model parameters and the cepstral coefficients of a 2-D MA random field is considered. Based on this relation, recursive equations are derived so as to estimate the NSHP MA model parameters. It is noteworthy that the proposed algorithm is practical, i.e., it does not require computationally complex processes namely fitting to a high-order autoregressive model, any initial estimates, nor matrix inversion. Performance analysis of the derived algorithm together with an existing method is given for comparison purposes.