DocumentCode
510213
Title
Fast Parameter Estimation in Image Restoration Based on Hierarchical Bayesian Framework
Author
Xiao, Su ; Han, Guoqiang ; Wo, Yan ; Li, Zhan ; Chen, Xiangji
Author_Institution
Sch. of Comput. Sci. & Eng., South China Univ. of Technol., Guangzhou, China
Volume
1
fYear
2009
fDate
11-14 Dec. 2009
Firstpage
372
Lastpage
375
Abstract
In this paper, an algorithm under Bayesian framework is proposed using the variational method to estimate the original image and parameters simultaneously and iteratively. The harmonic model and the gamma model are introduced as prior models for the original image and parameters separately. The harmonic model is a kind of smoothing model which is computationally efficient compared with nonlinear models, and it can preserve edges in the image better than most other smoothing models. The gamma can incorporate more prior knowledge for than the way that supposes the parameters as certain constants. The experimental results show the competitive performance of the proposed algorithm when used to estimate the parameters.
Keywords
Bayes methods; image restoration; parameter estimation; fast parameter estimation; gamma model; harmonic model; hierarchical Bayesian framework; image restoration; smoothing model; Bayesian methods; Computational intelligence; Computer security; Deconvolution; Image restoration; Parameter estimation; Random processes; Smoothing methods; Stochastic resonance; TV;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Security, 2009. CIS '09. International Conference on
Conference_Location
Beijing
Print_ISBN
978-1-4244-5411-2
Type
conf
DOI
10.1109/CIS.2009.192
Filename
5376533
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