Title :
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
fDate :
8/1/1995 12:00:00 AM
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;
Journal_Title :
Circuits and Systems II: Analog and Digital Signal Processing, IEEE Transactions on
