Repository logo
 

Reduced order strip Kalman filtering using singular perturbation method

dc.contributor.authorKhorasani, K., author
dc.contributor.authorAzimi-Sadjadi, Mahmood R., author
dc.contributor.authorIEEE, publisher
dc.date.accessioned2007-01-03T04:18:36Z
dc.date.available2007-01-03T04:18:36Z
dc.date.issued1990
dc.description.abstractStrip Kalman filtering for restoration of images degraded by linear shift invariant (LSI) blur and additive white Gaussian (WG) noise is considered. The image process is modeled by a 1-D vector autoregressive (AR) model in each strip. It is 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 owing to the strong-weak correlation effects within a window. The time scale property of the singularly perturbed system is then utilized to decompose the original system into reduced order subsystems which closely capture the behavior of the full order system. For these subsystems the relevant Kalman filtering equations are given which provide the suboptimal filtered estimates of the image and the one-step prediction estimates of the blur needed for the next stage. Simulation results are also provided.
dc.format.mediumborn digital
dc.format.mediumarticles
dc.identifier.bibliographicCitationAzimi-Sadjadi, M. R. and K. Khorasani, Reduced Order Strip Kalman Filtering Using Singular Perturbation Method, IEEE Transactions on Circuits and Systems 37, no. 2 (February 1990): 284-290.
dc.identifier.urihttp://hdl.handle.net/10217/1017
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado State University. Libraries
dc.relation.ispartofFaculty Publications
dc.rights©1990 IEEE.
dc.rightsCopyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.
dc.subjectperturbation theory
dc.subjectfiltering and prediction theory
dc.subjectKalman filters
dc.subjectpicture processing
dc.subjectwhite noise
dc.titleReduced order strip Kalman filtering using singular perturbation method
dc.typeText

Files

Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
ECEmra00028.pdf
Size:
653.85 KB
Format:
Adobe Portable Document Format
Description: