This paper is devoted to the combination of several prior models in Bayesian image restoration and increasingly wide utilization in astronomical images. Bayesian methods introduce image models using prior knowledge and address the ill-posed problem in the registration parameter estimation. Employing a variational Bayesian analysis, we obtain a unique approximating distribution based on the observations that decreases the Kullback Leibler distance for more optimal posterior distribution. The estimated results on astronomical images experimentally provide higher quality and better restoration performance.


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    Title :

    Astronomical image restoration using Bayesian methods


    Contributors:
    Xiaoping Shi, (author) / Rui Guo, (author) / Zicai Wang, (author)


    Publication date :

    2016-08-01


    Size :

    321216 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Infrared Astronomical Satellite (IRAS) Image Reconstruction And Restoration

    Kennealy, J. P. / Korte, R. M. / Gonsalves, R. A. et al. | SPIE | 1987


    An Efficient Lucky Imaging System for Astronomical Image Restoration

    Zhang, S. | British Library Conference Proceedings | 2011


    Image-Modeling Gibbs Distributions for Bayesian Restoration

    Chan, M. / Levitan, E. / Herman, G. T. et al. | British Library Conference Proceedings | 1994


    Mutual information regularized Bayesian framework for multiple image restoration

    Yunqiang Chen, / Hongcheng Wang, / Tong Fang, et al. | IEEE | 2005


    Mutual Information Regularized Bayesian Framework for Multiple Image Restoration

    Chen, Y. / Wang, H. / Fang, T. et al. | British Library Conference Proceedings | 2005