Estimation and identification for 2-D block Kalman filtering

Author

Azimi-Sadjadi, Mahmood R.

Author_Institution

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

Volume

39

Issue

8

fYear

1991

fDate

8/1/1991 12:00:00 AM

Firstpage

1885

Lastpage

1889

Abstract

The development of a recursive identification and estimation procedure for two-dimensional block Kalman filtering is discussed. The recursive identification scheme can be used online to update the image model parameters at each iteration based on the local statistics within a block of the observed noisy image. The covariance matrix of the driving noise can also be estimated at each iteration of this algorithm. A recursive procedure for computing the parameters of the higher order models is given. Simulation results are also provided

Keywords

Kalman filters; adaptive filters; filtering and prediction theory; identification; parameter estimation; picture processing; 2-D block Kalman filtering; adaptive filtering; covariance matrix; driving noise; estimation procedure; higher order models; image model parameters; image restoration; iteration; noisy image; recursive identification; Autoregressive processes; Computational modeling; Covariance matrix; Filtering; Higher order statistics; Image restoration; Kalman filters; Pixel; Recursive estimation; Strips;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.91158

Filename

91158