Bayesian parameter estimation in image reconstruction from subsampled blurred observations

Author

Vega, Miguel ; Mateos, Javier ; Molina, Rafael ; Katsaggelos, Aggelos K.

Author_Institution

Dpto. de Lenguajes y Sistemas Informaticos, Granada Univ., Spain

Volume

2

fYear

2003

fDate

14-17 Sept. 2003

Abstract

In this paper we consider the estimation of the unknown hyperparameters for the problem of reconstructing a high-resolution image from multiple undersampled, shifted, blurred and degraded frames with subpixel displacement errors. We derive mathematical expressions for the iterative calculation of the maximum likelihood estimate (mle) of the unknown hyperparameters given the low resolution observed images. Finally, the proposed method is tested on a synthetic image.

Keywords

Bayes methods; image reconstruction; maximum likelihood estimation; parameter estimation; Bayesian parameter estimation; high-resolution image reconstruction; iterative calculation; maximum likelihood estimate; subpixel displacement error; subsampled blurred observation; synthetic image; unknown hyperparameter estimation; Bayesian methods; Computer errors; Degradation; Image reconstruction; Image resolution; Image sensors; Parameter estimation; Signal processing; Signal resolution; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 2003. ICIP 2003. Proceedings. 2003 International Conference on

ISSN

1522-4880

Print_ISBN

0-7803-7750-8

Type

conf

DOI

10.1109/ICIP.2003.1246845

Filename

1246845