Estimation and identification for 2-D block Kalman

Author

Azimi-Sadjadi, Mahmood R.

Author_Institution

Dept. of Electr. Eng., Colorado State Univ., Fort Collins, CO, USA

fYear

1988

fDate

7-9 Jun 1988

Firstpage

2077

Abstract

The author considers the development of recursive identification and estimation techniques for the 2-D block Kalman filtering method proposed by M.R. Azimi-Sadjadi and P.W. Wong (IEEE Trans. on Acoustics, Speech, and Signal Proc., vol.ASSP-35, p.1736-49, Dec. 1987). A recursive identification scheme is introduced which can be used online to update image model parameters based upon the local statistics within a processing window. The correlation matrix of the model noise is estimated by solving a set of vector Yule-Walker equations. A recursive procedure is given for computing the parameters of the higher-order models. A method for updating the Kalman gain matrix which does not require any matrix inversion operation is also suggested

Keywords

Kalman filters; identification; parameter estimation; picture processing; recursive functions; 2-D block Kalman filtering; Kalman gain matrix; correlation matrix; image model parameters; image processing; local statistics; parameter estimation; recursive identification; vector Yule-Walker equations; Adaptive filters; Filtering; Higher order statistics; Kalman filters; Parameter estimation; Recursive estimation; State estimation; Strips; System identification; Vectors;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 1988., IEEE International Symposium on

Conference_Location

Espoo

Type

conf

DOI

10.1109/ISCAS.1988.15350

Filename

15350