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Bregman Iterative Model Using the G-norm

Yuying Shi North China Electric Power University Xiaozhong Yang North China Electric Power University Yonggui Zhu Communication University of China

Numerical Analysis and Scientific Computing mathscidoc:1702.25079

Acta Mathematicae Applicatae Sinica,English Series, 30, (1), 179-186, 2014.1
In this paper, we analyze the Bregman iterative model using the G-norm. Firstly, we show the convergence of the iterative model. Secondly, using the source condition and the symmetric Bregman distance, we consider the error estimations between the iterates and the exact image both in the case of clean and noisy data. The results show that the Bregman iterative model using the G-norm has the similar good properties as the Bregman iterative model using the L2-norm.
Bregman distance; image restoration; total variation; error estimation; iterative regularization.
[ Download ] [ 2017-02-10 02:55:17 uploaded by ygzhu ] [ 656 downloads ] [ 0 comments ] 
@inproceedings{yuying2014bregman,
  title={Bregman Iterative Model Using the G-norm},
  author={Yuying Shi, Xiaozhong Yang, and Yonggui Zhu},
  url={http://archive.ymsc.tsinghua.edu.cn/pacm_paperurl/20170210025517506966422},
  booktitle={Acta Mathematicae Applicatae Sinica,English Series},
  volume={30},
  number={1},
  pages={179-186},
  year={2014},
}
Yuying Shi, Xiaozhong Yang, and Yonggui Zhu. Bregman Iterative Model Using the G-norm. 2014. Vol. 30. In Acta Mathematicae Applicatae Sinica,English Series. pp.179-186. http://archive.ymsc.tsinghua.edu.cn/pacm_paperurl/20170210025517506966422.
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