| MU Yun-ping,HUANG Bao-xiang,WANG Yu-xi,WANG Ming-lei,XUE Chao.otal curvature (TC) model and its alternating direction method of multipliers algorithm for noise removal[J].Optoelectronics Letters,2019,15(3):217-223 |
| otal curvature (TC) model and its alternating direction method of multipliers algorithm for noise removal |
| Author Name | Affiliation | | MU Yun-ping | School of Computer Science, Qingdao University, Qingdao 266071, China | | HUANG Bao-xiang | School of Computer Science, Qingdao University, Qingdao 266071, China | | WANG Yu-xi | School of Computer Science, Qingdao University, Qingdao 266071, China | | WANG Ming-lei | School of Computer Science, Qingdao University, Qingdao 266071, China | | XUE Chao | School of Computer Science, Qingdao University, Qingdao 266071, China |
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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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