Two-dimensional Markov spectral estimation
J. Woods · IEEE Transactions on Information Theory · 1976
A constructive proof is given for the existence and uniqueness of a two-dimensional discrete Markov random field which agrees with correlation values in a nearest neighbor array. The corresponding spectrum is the two-dimensional maximum entropy (ME) spectrum whose form was discovered by Burg. An iterative algorithm is developed for computing an approximation to this Markov spectrum for a regularly spaced array. The algorithm approximates the desired Markov correlation function by a truncated convolution power series (CPS) in an operatorh. The algorithm's performance is demonstrated on both simulated data and real noise data. The Markov spectral estimate can offer higher resolution than previously proposed spectral estimates.