Two dimensional AR modeling by autocorrelation fitting

Author

Jackson, L. ; Chen, Haiguang

Author_Institution

Dept. of Electr. Eng., Rhode Island Univ., Kingston, RI, USA

fYear

1990

fDate

3-6 Apr 1990

Firstpage

2527

Abstract

The problem of two-dimensional AR (autoregressive) modeling of two-dimensional stationary random fields by fitting the estimated autocorrelation function with the model autocorrelation function is addressed. Both nonsymmetric half-plane and quarter-plane supports are used for modeling. Ekstrom-Woods (1976) two-dimensional spectral factorization is used to generate a stable and accurate initial estimate of the model coefficients and permits the determination of the model coefficients with the same support as the original autocorrelation data. Several experimental results are given to illustrate the effectiveness of the method in two-dimensional artificial random field synthesis and spectral estimation

Keywords

filtering and prediction theory; parameter estimation; spectral analysis; artificial random field synthesis; autocorrelation fitting; autoregressive modelling; nonsymmetric half-plane supports; quarter-plane supports; spectral estimation; spectral factorization; two-dimensional stationary random fields; Autocorrelation; Convolution; Filters; Iterative algorithms; Nonlinear equations; Quadratic programming; Two dimensional displays; Writing;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1990. ICASSP-90., 1990 International Conference on

Conference_Location

Albuquerque, NM

ISSN

1520-6149

Type

conf

DOI

10.1109/ICASSP.1990.116115

Filename

116115