A stabilization algorithm for multichannel multidimensional linear prediction of imagery

The authors have investigated the stability problems observed in multichannel multidimensional linear predictive modeling of images. It is known that based on a positive definite autocorrelation matrix, singular values of the matrix H=δ_i+1×Herm (δ_i+1) must lie inside the unit circle for a stable solution, where δ_i+1 is the normalized partial correlation matrix and Herm denotes the Hermitian operator. The authors have developed a two-step stabilization method to obtain stabilized linear prediction coefficients for short term analysis windows formed digitized images. The authors have modified the multichannel Levinson recursion algorithm to include this stability procedure. They have tested the algorithm on numerous images commonly used in image coding and the results are very impressive