Noncausal image modeling using descriptor approach

Author

Hasan, Mohammed A. ; Azimi-Sadjadi, Mahmood R.

Author_Institution

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

Volume

42

Issue

8

fYear

1995

fDate

8/1/1995 12:00:00 AM

Firstpage

536

Lastpage

540

Abstract

The problems of noncausal image modeling and subsequent image estimation are considered in this brief. The noncausal vector autoregressive (AR) model for the image process is arranged into a descriptor system. This system is then decomposed into backward and forward stable subsystems. The resulting subsystems are utilized to derive a Kalman filter by solving some types of discrete time algebraic Lyapunov equations. A numerical example for noncausal image modeling is also presented

Keywords

Kalman filters; Lyapunov matrix equations; autoregressive processes; filtering theory; image processing; Kalman filter; autoregressive model; backward stable subsystems; descriptor system; discrete time algebraic Lyapunov equations; forward stable subsystems; image estimation; image processing; image restoration; noncausal image modeling; noncausal vector AR model; Autoregressive processes; Covariance matrix; Data mining; Degradation; Equations; Filtering; Image restoration; Spectral analysis; State estimation; Strips;

fLanguage

English

Journal_Title

Circuits and Systems II: Analog and Digital Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1057-7130

Type

jour

DOI

10.1109/82.404084

Filename

404084