Parameter estimation in Bayesian high-resolution image reconstruction with multisensors

Author

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

Author_Institution

Dept. de Ciencias de la Computacion e I.A., Univ. de Granada, Spain

Volume

12

Issue

12

fYear

2003

Firstpage

1655

Lastpage

1667

Abstract

We consider the estimation of the unknown parameters for the problem of reconstructing a high-resolution image from multiple undersampled, shifted, degraded frames with subpixel displacement errors. We derive mathematical expressions for the iterative calculation of the maximum likelihood estimate of the unknown parameters given the low resolution observed images. These iterative procedures require the manipulation of block-semi circulant (BSC) matrices, that is, block matrices with circulant blocks. We show how these BSC matrices can be easily manipulated in order to calculate the unknown parameters. Finally the proposed method is tested on real and synthetic images.

Keywords

Bayes methods; image reconstruction; image resolution; iterative methods; matrix algebra; maximum likelihood estimation; sensor fusion; Bayesian high-resolution image reconstruction; Bayesian methods; block matrices; block-semi circulant matrices; circulant blocks; iterative calculation; maximum likelihood estimation; multiple frames; multisensors; parameter estimation; subpixel displacement errors; Bayesian methods; Charge-coupled image sensors; Degradation; Image reconstruction; Image resolution; Optical imaging; Parameter estimation; Pixel; Signal resolution; Signal to noise ratio;

fLanguage

English

Journal_Title

Image Processing, IEEE Transactions on

Publisher

ieee

ISSN

1057-7149

Type

jour

DOI

10.1109/TIP.2003.818117

Filename

1257401