Bayesian high resolution image reconstruction with incomplete multisensor low resolution systems

Author

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

Author_Institution

Dept. de Ciencias de la Comput. e Inteligencia Artificial, Granada Univ., Spain

Volume

3

fYear

2003

fDate

6-10 April 2003

Abstract

We consider the problem of reconstructing a high-resolution image from an incomplete set of undersampled, shifted, degraded frames with subpixel displacement errors. We derive mathematical expressions for the calculation of the maximum a posteriori (MAP) estimate of the high resolution image given the low resolution observed images. We also examine the role played by the prior model when an incomplete set of low resolution images is used. Finally, the proposed method is tested on real and synthetic images.

Keywords

Bayes methods; image reconstruction; image resolution; maximum likelihood estimation; Bayesian image reconstruction; MAP estimation; high resolution image reconstruction; incomplete image set; low resolution multisensor; maximum a posteriori estimation; Bayesian methods; Computer errors; Degradation; Image reconstruction; Image resolution; Image sensors; Least squares methods; Maximum likelihood estimation; Signal resolution; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03). 2003 IEEE International Conference on

ISSN

1520-6149

Print_ISBN

0-7803-7663-3

Type

conf

DOI

10.1109/ICASSP.2003.1199572

Filename

1199572