NDLI: Reduced order strip Kalman filtering using singular perturbation method

Content Provider	IEEE Xplore Digital Library
Author	Azimi-Sadjadi, M.R. Navid-Azarbaijani, F. Khorasani, K. Bartels, V.J.
Copyright Year	1988
Description	Author affiliation: Dept. of Electr. Eng., Colorado State Univ., Fort Collins, CO, USA (Azimi-Sadjadi, M.R.)
Abstract	Strip Kalman filtering for restoration of images degraded by linear-shift-invariant blur and additive white Gaussian noise is considered. The image process is modeled by a large-order perturbed vector AR (autoregressive) model which takes into account the strong-weak correlation effects within a window. It has been shown that the composite dynamic model that is obtained by combining the image model and the blur model takes the form of a singularly perturbed system. The time-scale property of this singularly perturbed system is then utilized to decompose the large-order system into a reduced-order subsystem which closely captures the behavior of the original system. For this subsystem the relevant Kalman filtering equations are obtained which at each stage provide the suboptimal filtered estimates of the image and the one-step prediction estimates of the blur that are needed for the next stage.<>
Starting Page	2081
Ending Page	2084
File Size	255895
Page Count	4
File Format	PDF
DOI	10.1109/ISCAS.1988.15351
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1988-06-07
Publisher Place	Finland
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Strips Kalman filters Filtering Perturbation methods Reduced order systems Image generation Equations Image restoration Recursive estimation Degradation
Content Type	Text
Resource Type	Article

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