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Image Restoration by Second-Order Total Generalized Variation and Wavelet Frame Regularization

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  • Jianguang Zhu
  • Kai Li
  • Binbin Hao

Abstract

It has been proved that total generalized variation (TGV) can better preserve edges while suppressing staircase effect. In this paper, we propose an effective hybrid regularization model based on second-order TGV and wavelet frame. The proposed model inherits the advantages of TGV regularization and wavelet frame regularization, can eliminate staircase effect while protecting the sharp edge, and simultaneously has good capability of sparsely estimating the piecewise smooth functions. The alternative direction method of multiplier (ADMM) is employed to solve the new model. Numerical results show that our proposed model can preserve more details and get higher image visual quality than some current state-of-the-art methods.

Suggested Citation

  • Jianguang Zhu & Kai Li & Binbin Hao, 2019. "Image Restoration by Second-Order Total Generalized Variation and Wavelet Frame Regularization," Complexity, Hindawi, vol. 2019, pages 1-16, March.
    • Handle: RePEc:hin:complx:3650128
    DOI: 10.1155/2019/3650128
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    References listed on IDEAS

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    1. Jianguang Zhu & Binbin Hao, 2014. "A New Noninterior Continuation Method for Solving a System of Equalities and Inequalities," Journal of Applied Mathematics, Hindawi, vol. 2014, pages 1-6, April.
    2. Wang, Zhen & Xie, Yingkang & Lu, Junwei & Li, Yuxia, 2019. "Stability and bifurcation of a delayed generalized fractional-order prey–predator model with interspecific competition," Applied Mathematics and Computation, Elsevier, vol. 347(C), pages 360-369.
    3. Ming Chen & Gang Li, 2013. "Forming Mechanism and Correction of CT Image Artifacts Caused by the Errors of Three System Parameters," Journal of Applied Mathematics, Hindawi, vol. 2013, pages 1-7, April.
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