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 :
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