2016
DOI: 10.1177/1748301816656298
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Primal-dual method to smoothing TV-based model for image denoising

Abstract: The total variation-based Rudin-Osher-Fatemi model is an effective and popular prior model in the image processing problem. Different to frequently using the splitting scheme to directly solve this model, we propose the primal dual method to solve the smoothing total variation-based Rudin-Osher-Fatemi model and give some convergence analysis of proposed method. Numerical implements show that our proposed model and method can efficiently improve the numerical results compared with the Rudin-Osher-Fatemi model.

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Cited by 12 publications
(8 citation statements)
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“…In this article, a variational method is applied to obtain smooth maps. The method is based on a classical variation model for image denoising, originally proposed by Rudin et al 13 The problem has been formulated as the following convex optimisation problem and solved by the primal-dual method as demonstrated by Zhi et al 14…”
Section: Variable Map Smoothingmentioning
confidence: 99%
See 1 more Smart Citation
“…In this article, a variational method is applied to obtain smooth maps. The method is based on a classical variation model for image denoising, originally proposed by Rudin et al 13 The problem has been formulated as the following convex optimisation problem and solved by the primal-dual method as demonstrated by Zhi et al 14…”
Section: Variable Map Smoothingmentioning
confidence: 99%
“…Then, the tuning parameter is introduced to obtain different levels of map smoothness, which is based on the classical total variation method proposed by Rudin et al 13 and has been extensively used in the literature. 14,15 Finally, a time-varying smoothness strategy is generated and tested, with the goal to further improve engine performance and drivability, as compared to calibration maps with a fixed level of smoothness. The main contributions of this article are as follows:…”
Section: Introductionmentioning
confidence: 99%
“…However, our paper is not the first to handle this kind of penalized estimation method with the help of the Euler-Lagrange equation. Indeed, in the image processing literature, such a method is used to smooth images disrupted by some measurement noise [12,43,48]. But, in these papers, the quite more general framework imposes an iterative resolution.…”
Section: Introductionmentioning
confidence: 99%
“…A model-based optimal calibration approach is used to obtain maps which meet a specied NO x emissions limit while minimizing the fuel consumption. Then, the tuning parameter is introduced to obtain dierent levels of map smoothness, which is based on the classical total variation method originally proposed by Rudin et al [Rudin et al 1992] and has been extensively used in the literature [Zhi et al 2016, Aubert & Kornprobst 2006.…”
Section: Discussionmentioning
confidence: 99%
“…The method is based on a classical variation model for image de-noising, originally proposed by Rudin et al in [Rudin et al 1992]. The problem is formulated as the following convex optimisation problem and solved by the primal-dual method as demonstrated by Zhi et al in [Zhi et al 2016…”
Section: Methods Descriptionmentioning
confidence: 99%