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An Adaptive Non-local Total Variation Blind Deconvolution Employing Split Bregman Iteration

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Abstract

Total variation (TV) has been used as a popular and effective image prior model in regularization-based image restoration, because of its ability to preserve edges. However, as the total variation model favors a piecewise constant solution, the processing results in the flat regions of the image are poor, and the amplitude of the edges will be underestimated; the underlying cause of the problem is that the model is based on derivation which only considers the local feature of the image. In this paper, we first propose an adaptive non-local total variation image blind restoration algorithm for deblurring a single image via a non-local total variation operator, which exploits the correlation in the image, and then an extended split Bregman iteration is proposed to address the joint minimization problem. Second, the maximum average absolute difference (MAAD) method is employed to estimate the blur support and initialize the blur kernel. Extensive experiments demonstrate that the proposed approach produces results superior to most methods in both visual image quality and quantitative measures.

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Acknowledgements

The authors would like to thank the editors and the anonymous reviewers for their valuable suggestions. We would also like to thank Professors Rafael Molina, Xiaoqun Zhang, Jianfeng Cai, and Daiqiang Chen for supplying the Matlab implementation of their algorithm. This work was supported by the Project of the key National Natural Science Foundation of China under Grant No. 60736010, No. 60902060, the Innovation Research Fund Committee of HUST (2011QN073), and the Innovation Fund of CASC (CASC 201104).

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Authors and Affiliations

  1. Institute for Pattern Recognition and Artificial Intelligence, Huazhong University of Science and Technology, Wuhan, 430074, China

    Zhiyong Zuo, Tianxu Zhang & Luxin Yan

  2. School of Mathematics and Statistics, Wuhan University, Wuhan, 430072, China

    Xia Lan

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  1. Zhiyong Zuo
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  2. Tianxu Zhang
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  3. Xia Lan
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  4. Luxin Yan
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Correspondence to Zhiyong Zuo.

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Zuo, Z., Zhang, T., Lan, X. et al. An Adaptive Non-local Total Variation Blind Deconvolution Employing Split Bregman Iteration. Circuits Syst Signal Process 32, 2407–2421 (2013). https://doi.org/10.1007/s00034-013-9581-8

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  • DOI: https://doi.org/10.1007/s00034-013-9581-8

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