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Remove the salt and pepper noise based on the high order total variation and the nuclear norm regularization

Author

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  • Shi, Baoli
  • Gu, Fang
  • Pang, Zhi-Feng
  • Zeng, Yuhua

Abstract

This paper proposes a new model to remove the salt and pepper (SAP) noise problem. In the proposed method, we combine the high order total variation regularization with the nuclear norm regularization in order to keep details and structures of the restored images. Since the proposed model is convex and separable, the classic alternating direction method of multipliers can be employed to solve it by introducing some auxiliary variables to transform the original problem into the saddle point problem. Theoretically, we establish the convergence analysis of the proposed numerical algorithm. Final experimental comparisons are provided to show the satisfactory performance of the proposed model, which outperforms other related competitive methods in both the SNR and the SSIM.

Suggested Citation

  • Shi, Baoli & Gu, Fang & Pang, Zhi-Feng & Zeng, Yuhua, 2022. "Remove the salt and pepper noise based on the high order total variation and the nuclear norm regularization," Applied Mathematics and Computation, Elsevier, vol. 421(C).
    • Handle: RePEc:eee:apmaco:v:421:y:2022:i:c:s009630032200011x
    DOI: 10.1016/j.amc.2022.126925
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