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An improved regularization-based method of blur kernel estimation for blind motion deblurring

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Abstract

In engineering application, image blur is a troublesome problem due to camera shaking or relative motion. To address it, this paper proposes an efficient regularization method for blind motion deblurring of image. In the process of estimating blur kernel. The optimization energy function is improved. Smooth L0 norm is introduced instead of L0 norm to facilitate the optimization of energy function. Besides, a regular term is reduced so that the corresponding parameter is saved as well. In addition, an optimization algorithm is presented to automatically solve the optimal values of parameters through simulated annealing. Experimental results show that the proposed method is able to accurately estimates blur kernel and generate satisfactory retrieved images. Compared with the deep learning-based methods, the proposed method is simpler, faster and less dependent on hardware, which is easier to be implemented on embedded devices so that can be better applied to areas such as UAV photography.

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Acknowledgements

The authors gratefully acknowledge the Foundation for Scientific Research Projects of Universities in Guangdong Province (No. 2018GkQNCX150) and the Open Foundation of Guangdong Key Laboratory of Big Data Analysis and Processing (No. 201603).

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Authors and Affiliations

  1. Department of Computer, Shantou Polytechnic, Shantou, 515078, China

    Zhe Lin

  2. Guangdong Key Laboratory of Big Data Analysis and Processing, Guangzhou, 510006, China

    Zhe Lin

  3. Department of Mechanical and Electrical Engineering, Shantou Polytechnic, Shantou, 515078, China

    Hong Peng

  4. Department of Civil and Environmental Engineering, Shantou University, Shantou, 515063, China

    Hong Peng

  5. Network and Information Center, Shantou Polytechnic, Shantou, 515078, China

    Tian Cai

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  1. Zhe Lin
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  2. Hong Peng
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  3. Tian Cai
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Correspondence to Tian Cai.

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Lin, Z., Peng, H. & Cai, T. An improved regularization-based method of blur kernel estimation for blind motion deblurring. SIViP 15, 17–24 (2021). https://doi.org/10.1007/s11760-020-01720-5

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  • DOI: https://doi.org/10.1007/s11760-020-01720-5

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