Two-Dimensional Least Squares Lattice Algorithm for Linear Prediction

Takayuki NAKACHI  Katsumi YAMASHITA  Nozomu HAMADA  

IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E80-A       pp.2325-2329
Publication Date: 1997/11/25
Online ISSN: 
Print ISSN: 0916-8508
Type of Manuscript: Category: Digital Signal Processing
lattice filter,  2-D signal processing,  adaptive filter,  texture analysis,  

Full Text: PDF>>
Buy this Article

In this paper, we propose a two-dimensional (2-D) least-squares lattice (LSL) algorithm for the general case of the autoregressive (AR) model with an asymmetric half-plane (AHP) coefficient support. The resulting LSL algorithm gives both order and space recursions for the 2-D deterministic normal equations. The size and shape of the coefficient support region of the proposed lattice filter can be chosen arbitrarily. Furthermore, the ordering of the support signal can be assigned arbitrarily. Finally, computer simulation for modeling a texture image is demonstrated to confirm the proposed model gives rapid convergence.