Remove the salt and pepper noise based on the high order total variation and the nuclear norm regularization. (English) Zbl 1510.94022
Summary: 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.
MSC:
| 94A08 | Image processing (compression, reconstruction, etc.) in information and communication theory |
| 68U10 | Computing methodologies for image processing |
| 90C25 | Convex programming |
Keywords:
image denoising; salt and pepper (SAP) noise; high order total variation (HOTV) regularization; nuclear norm regularization; alternating direction method of multipliers (ADMM)References:
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