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Poisson Noise Removal Using Non-convex Total Generalized Variation

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Abstract

As is well-known that the total generalized variation model performs well in reducing the staircasing effect while removing noise, but it tends to cause the undesirable edge details blurring. To overcome this drawback, the current paper introduces the non-convex restriction into the total generalized variation regularizer and constructs an improved edge-preserving optimization model for Poissonian images restoration. For solving the minimization problem, we propose an efficient alternating minimization method by skillfully combining the classical iteratively reweighted \(\ell _1\) algorithm and primal-dual framework. Some visual experiments presented in the illustration section, which are compared with some related denoising methods, demonstrate the better performance of the developed scheme in staircase artifacts reduction and image features protection. Besides, the measurable comparisons also indicate that our outcomes enjoy the best restoration accuracy against other popular competitors.

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Data Availability

All data generated or analyzed during the current study are included in this published article.

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Acknowledgements

The authors would like to thank the editors and anonymous reviewers for their constructive comments and valuable suggestions.

Funding

This work was supported by Hunan Provincial Natural Science Foundation of China (2020JJ4285, 2020JJ5151) and Scientific Research Fund of Hunan Provincial Education Department (19B215).

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Authors and Affiliations

  1. School of Mathematics and Computational Science, Hunan University of Science and Technology, Xiangtan, 411201, Hunan, China

    Xinwu Liu & Yingying Li

Authors
  1. Xinwu Liu
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  2. Yingying Li
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Contributions

X. Liu contributed to study design, programming, manuscript writing and revisions. Y. Li wrote and revised the paper. All authors have read and approved the manuscript.

Corresponding author

Correspondence to Xinwu Liu.

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Liu, X., Li, Y. Poisson Noise Removal Using Non-convex Total Generalized Variation. Iran J Sci Technol Trans Sci 45, 2073–2084 (2021). https://doi.org/10.1007/s40995-021-01203-3

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  • DOI: https://doi.org/10.1007/s40995-021-01203-3

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