FURTHER IMPROVED 2-D LATTICE FILTER STRUCTURE EMPLOYING MISSING REFLECTION COEFFICIENTS

A new lattice filter structure to model two-dimensional (2-D) autoregr essive (AR) fields is proposed. The proposed structure utilizes and ex tracts the information contained in the backward prediction error fiel ds and their delayed versions. The main idea is to use two sets of ref lection coefficients corresponding to two quadrant filters and to incr ease the number of reflection coefficients with the order of the latti ce filter. Increasing the number of reflection coefficients at each st age produces a sufficient number of independent parameters to model AR fields up to order three, which is an improvement over the existing 2 -D lattice filter structures. The improvement is confirmed by computer simulations. In addition, a relationship between the reflection coeff icients and the AR coefficients is derived. It is also shown that the entropy contained in the backward prediction error field vector of the proposed structure is closer to the input entropy when compared to th ose contained in existing 2-D lattice filters.