DocumentCode
2601791
Title
An edge-preserving blind image restoration using hierarchical Bayesian model
Author
He, Zhenya ; Zhang, Yunnong
Author_Institution
Dept. of Radio Eng., Southeast Univ., Nanjing, China
Volume
2
fYear
2002
fDate
2002
Firstpage
89
Abstract
Edge-preserving blind image restoration using a hierarchical Bayesian model is proposed in this paper. The restoration problem, when the point-spread function (PSF) of the degradation system is partially known, is examined. The simultaneously autoregressive image model and the fixed-f covariance model are used under a Bayesian framework. The evidence analysis approach is then used to simultaneously estimate the parameters and the image iteratively. An edge-preserving regularization operator is utilized to carry out regularization according to the local image characteristics. Numerical experiments and conclusions are given to show the effectiveness of our method.
Keywords
Bayes methods; autoregressive processes; covariance analysis; edge detection; image restoration; iterative methods; optical transfer function; parameter estimation; PSF; autoregressive image models; blur restoration problems; edge-preserving blind image restoration; edge-preserving regularization operators; evidence analysis; fixed-f covariance models; hierarchical Bayesian models; iterative parameter estimation; local image characteristics; partially known degradation system point-spread functions; Bayesian methods; Covariance matrix; Degradation; Electronic mail; Helium; Image analysis; Image restoration; Parameter estimation; Stochastic processes; White noise;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits and Systems, 2002. APCCAS '02. 2002 Asia-Pacific Conference on
Print_ISBN
0-7803-7690-0
Type
conf
DOI
10.1109/APCCAS.2002.1115130
Filename
1115130
Link To Document