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A novel weighted anisotropic total variational model for image applications

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Abstract

In this paper, a novel weighted anisotropic total variational (WATV) model is proposed for image restoration. In this model, a weight function is defined to process degraded images, which is introduced into the \(\ell _{1}\) norm-based regularization. In order to efficiently compute the restored images, the alternating direction method of multipliers (ADMM) is explored and the according convergence is analyzed briefly. The proposed model is applied to recover images with blurring and noise. Compared experiments of deblurring, denoising as well as restoration are conducted to show the effectiveness and efficiency of the proposed WATV model.

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Acknowledgements

This work is supported by the National Natural Science Foundation of China (No. 61671063) and the Foundation for Innovative Research Groups of the National Natural Science Foundation of China (No. 61421001).

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Authors and Affiliations

  1. School of Mathematics and Statistics, Beijing Institute of Technology, Beijing, 100081, China

    Meng-Meng Li

  2. Beijing Key Laboratory on MCAACI, Beijing Institute of Technology, Beijing, 100081, China

    Bing-Zhao Li

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  1. Meng-Meng Li
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  2. Bing-Zhao Li
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Correspondence to Bing-Zhao Li.

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Li, MM., Li, BZ. A novel weighted anisotropic total variational model for image applications. SIViP 16, 211–218 (2022). https://doi.org/10.1007/s11760-021-01977-4

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