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Total curvature (TC) model and its alternating direction method of multipliers algorithm for noise removal

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Abstract

This paper develops a variational model for image noise removal using total curvature (TC), which is a high-order regularizer. The TC has the advantage of preserving image feature. Unfortunately, it also has the characteristics of nonlinear, non-convex and non-smooth. Consequently, the numerical computation with the curvature regularization is difficult. In order to conquer the computation problem, the proposed model is transformed into an alternating optimization problem by importing auxiliary variables. Furthermore, based on alternating direction method of multipliers, we design a fast numerical approximation iterative scheme for proposed model. Finally, numerous experiments are implemented to indicate the advantages of the proposed model in image edge preserving, image contrast and corners preserving. Meanwhile, the high computational efficiency of the designed model is verified by comparing with traditional models, including the total variation (TV) and total Laplace (TL) model.

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Authors and Affiliations

  1. School of Computer Science, Qingdao University, Qingdao, 266071, China

    Yun-** Mu  (牟云**), Bao-xiang Huang  (黄宝香), Yu-xi Wang  (王誉熹), Ming-lei Wang  (王明磊) & Chao Xue  (薛超)

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  1. Yun-** Mu  (牟云**)
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  2. Bao-xiang Huang  (黄宝香)
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  3. Yu-xi Wang  (王誉熹)
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  4. Ming-lei Wang  (王明磊)
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  5. Chao Xue  (薛超)
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Corresponding author

Correspondence to Bao-xiang Huang  (黄宝香).

Additional information

This work has been supported by the National Natural Science Foundation of China (No.61602269), the China Postdoctoral Science Foundation (No.2015M571993), the Shandong Provincial Natural Science Foundation of China (No.ZR2017MD004), and the Qingdao Postdoctoral Application Research Funded Project.

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Mu, Yp., Huang, Bx., Wang, Yx. et al. Total curvature (TC) model and its alternating direction method of multipliers algorithm for noise removal. Optoelectron. Lett. 15, 217–223 (2019). https://doi.org/10.1007/s11801-019-8145-y

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  • DOI: https://doi.org/10.1007/s11801-019-8145-y

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