Title :
Iterative Image Resolution Enhancement Using MAP Estimator
Author :
Peimin, Yan ; Shuozhong, Wang
Author_Institution :
Sch. of Commun. & Inf. Eng., Shanghai Univ.
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;
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
DOI :
10.1109/ICARCV.2006.345395
