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Weighted hybrid order total variation model using structure tensor for image denoising

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Abstract

A total variation filter has the characteristic of edge protection and has been widely used in image denoising for many years. In this study, our aim was to eliminate the staircase effect generated by the total variation model effectively, while also retaining the edge details. Therefore, we propose a weighted hybrid order total variation model which uses the determinant and trace of the structural tensor to control the smoothness. We used the split Bregman iterative algorithm to numerically solve the corresponding discrete problems. A coherent enhanced diffusion filter was used for preprocessing in each iteration; then, the proposed diffusion function was used for denoising. Numerical experiments show that the model has excellent denoising and edge protection performance.

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Acknowledgements

This work is supported by Major Special Science and Technology Project of Anhui Province (No .201903a06020006) and Key Project of Education Natural Science Research of Anhui Province of China (No: KJ2017A353).

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Authors and Affiliations

  1. School of Computer and Information, Anqing Normal University, Anqing Anhui, 246011, China

    Kui Liu, Wanru Xu, Haifeng Wu & Ali Abdullah Yahya

  2. The Key Lab of Intelligent Perception and Computing of Anhui Province, Anqing Anhui, 246011, China

    Kui Liu, Wanru Xu, Haifeng Wu & Ali Abdullah Yahya

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  1. Kui Liu
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  2. Wanru Xu
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  3. Haifeng Wu
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  4. Ali Abdullah Yahya
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Correspondence to Kui Liu.

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Liu, K., Xu, W., Wu, H. et al. Weighted hybrid order total variation model using structure tensor for image denoising. Multimed Tools Appl 82, 927–943 (2023). https://doi.org/10.1007/s11042-022-12393-2

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