DocumentCode :
1550919
Title :
Optimum quarter-plane autoregressive modeling of 2-D fields using four-field lattice approach
Author :
Kayran, Ahmet H. ; Parker, Sydney R.
Author_Institution :
Dept. of Electr. Eng., Istanbul Tech. Univ., Turkey
Volume :
45
Issue :
9
fYear :
1997
fDate :
9/1/1997 12:00:00 AM
Firstpage :
2363
Lastpage :
2373
Abstract :
A new orthogonal four-field two-dimensional (2-D) quarter-plane lattice structure with a complete set of reflection coefficients is developed by employing appropriately defined auxiliary prediction errors. This work is the generalization of the three-parameter lattice filter proposed by Parker and Kayran (1984). After the first stage, four auxiliary forward and four auxiliary backward prediction errors are generated in order to obtain a growing number of 2-D reflection coefficients at successive stages. The theory has been proven by using a geometrical formulation based on the mathematical concepts of vector space, orthogonal projection, and subspace decomposition. It is shown that all four quarter-plane filters are orthogonal and thus optimum for all stages. In addition to developing the basic theory, a set of orthogonal backward prediction error fields for successive lattice parameter model stages is presented
Keywords :
autoregressive processes; error analysis; filtering theory; lattice filters; network parameters; prediction theory; random processes; two-dimensional digital filters; 2D digital filter; 2D fields; 2D reflection coefficients; auxiliary backward prediction errors; auxiliary forward prediction errors; four-field lattice approach; geometrical formulation; lattice parameter model stages; optimum quarter-plane autoregressive modeling; orthogonal backward prediction error fields; orthogonal projection; orthogonal quarter-plane filters; subspace decomposition; three-parameter lattice filter; vector space; Data compression; Filters; Helium; Image recognition; Lattices; Predictive models; Recursive estimation; Reflection; Two dimensional displays; Very large scale integration;
fLanguage :
English
Journal_Title :
Signal Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1053-587X
Type :
jour
DOI :
10.1109/78.622958
Filename :
622958
Link To Document :
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