Two-Dimensional Linear Prediction Covariance Method and Its Recursive Solution

The two-dimensional (2-D) linear prediction "covariance" method is considered for the general case of a predictor with an asymmetric half-plane support lattice. The extension of a previous one-dimensional algorithm, based on conjugate directions, for solving recursively the symmetric set of normal equations for the 2-D covariance method is discussed. The effects of modeling caused by the choice of support lattices and of the ordering for the predictor coefficients are also studied. Examples are provided illustrating the various issues involved in modeling and the application of the "covariance" method in image coding.