Two-dimensional recursive parameter identification for adaptive Kalman filtering

Author

Azimi-Sadjadi, Mahmood R. ; Bannour, Sami

Author_Institution

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

Volume

38

Issue

9

fYear

1991

fDate

9/1/1991 12:00:00 AM

Firstpage

1077

Lastpage

1081

Abstract

The authors study the development of a two-dimensional (2-D) adaptive Kalman filtering by recursive adjustment of the parameters of an autoregressive (AR) image model with a nonsymmetric half-plane (NSHP) region of support. The image and degradation models are formulated in a 2-D state-space model, for which the relevant 2-D Kalman filtering equations are given. The recursive parameter identification is achieved using the extension of the stochastic Newton approach to the 2-D case. This process can be implemented online to estimate the image model parameters based upon the local statistics in every processing window. Simulation results for removing an additive noise from a degraded image are presented

Keywords

Kalman filters; adaptive filters; filtering and prediction theory; parameter estimation; picture processing; state-space methods; two-dimensional digital filters; 2D filtering; AR image model; adaptive Kalman filtering; additive noise removal; autoregressive model; degradation models; image model parameters; local statistics; nonsymmetric half-plane; recursive parameter identification; state-space model; stochastic Newton approach; Adaptive filters; Additive noise; Degradation; Equations; Filtering; Kalman filters; Parameter estimation; Statistics; Stochastic resonance; Two dimensional displays;

fLanguage

English

Journal_Title

Circuits and Systems, IEEE Transactions on

Publisher

ieee

ISSN

0098-4094

Type

jour

DOI

10.1109/31.83878

Filename

83878