Identification and restoration of images with symmetric noncausal blurs

Author

Biemond, Jan ; Van Der Putten, Frits G. ; Woods, John W.

Author_Institution

Dept. of Electr. Eng., Delft Univ. of Technol., Netherlands

Volume

35

Issue

4

fYear

1988

fDate

4/1/1988 12:00:00 AM

Firstpage

385

Lastpage

393

Abstract

A parallel identification and restoration procedure is described for images with symmetric, noncausal blurs. It is shown that the identification problem can be specified as a parallel set of one-dimensional complex autoregressive moving-average (ARMA) identification problems. By expressing the ARMA models as equivalent infinite-order autoregressive (AR) models, an entirely linear estimation procedure can be followed. It is shown that under the condition of blur symmetry, it is possible to reconstruct a useful noncausal set of MA (blur) parameters from the identified minimum-phase set. The identified image model and blur parameters are supplied to a parallel Kalman restoration filter. Several identification and restoration results on image data are given as examples

Keywords

Kalman filters; filtering and prediction theory; parameter estimation; picture processing; statistical analysis; time series; AR models; ARMA models; autoregressive moving-average; images; infinite-order autoregressive; linear estimation procedure; minimum-phase set; parallel Kalman restoration filter; parallel identification; picture processing; restoration procedure; symmetric noncausal blurs; Cameras; Circuits and systems; Degradation; Image reconstruction; Image restoration; Information analysis; Kalman filters; Layout; Lenses; Transfer functions;

fLanguage

English

Journal_Title

Circuits and Systems, IEEE Transactions on

Publisher

ieee

ISSN

0098-4094

Type

jour

DOI

10.1109/31.1753

Filename

1753