Iterative Image Resolution Enhancement Using MAP Estimator

Author

Peimin, Yan ; Shuozhong, Wang

Author_Institution

Sch. of Commun. & Inf. Eng., Shanghai Univ.

fYear

2006

fDate

5-8 Dec. 2006

Firstpage

1

Lastpage

3

Abstract

An iterative image resolution enhancement algorithm is presented based on a Bayesian MAP estimator. In order to speed up convergence and improve stability, additive regularization terms based on a set of exponentially varying weights and a least square criterion are added to the cost functional. Experimental results show that sufficient numbers of low-resolution frames and iterations are needed to produce a high-resolution image. However, excessive frames and iterations do not provide further improvement of the reconstructed image quality

Keywords

Bayes methods; image enhancement; image resolution; iterative methods; least squares approximations; maximum likelihood estimation; Bayesian MAP estimator; convergence; image quality; iterative image resolution enhancement; least square criterion; Bayesian methods; Convergence; Cost function; Image quality; Image reconstruction; Image resolution; Iterative algorithms; Iterative methods; Least squares methods; Spatial resolution; MAP estimator; convergence; iteration; resolution enhancement;

fLanguage

English

Publisher

ieee

Conference_Titel

Control, Automation, Robotics and Vision, 2006. ICARCV '06. 9th International Conference on

Conference_Location

Singapore

Print_ISBN

1-4244-0341-3

Electronic_ISBN

1-4214-042-1

Type

conf

DOI

10.1109/ICARCV.2006.345395

Filename

4150361