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全变分高阶模型的快速去噪算法 被引量:1

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摘要 全变分模型的图像去噪,虽然能保持图像边缘,但导致阶梯效应。为了去除阶梯效应,提出了全变分的高阶模型。本文将采用交替方向乘子法(ADMM),对该高阶模型进行求解,并对ADMM算法进行改造,在具体数值求解的过程中使用快速傅里叶变换法,通过仿真实验证明该模型的有效性和优越性。
作者 张倩
出处 《电子世界》 2016年第13期165-166,共2页 Electronics World
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参考文献9

  • 1Rudin L I,Osher S,Fatemi E.Nonlinear total variation based noise removal algorithms[J].Physics D:Nonlinear Phenomena,1992,60(1/4):259-268.
  • 2Lysaker M,Lundervold A,Tai Xuecheng.Noise removal using fourth-order partial differential equation with applications to medical magnetic resonance images in space and time[J].IEEE Transactions on Image Processing,2003,12(12):1579-1590.
  • 3M.Zhu and T.Chan,An Efficient Primal-Dual Hybrid Gradient Algorithm for Total Variation Image Restoration[R].Ucla Cam report,2008.
  • 4Wu Chunlin,Zhang Juyong,Tai Xuecheng.Augmented Lagrangian method for total variation restoration with non-quadratic fidelity[J].Inverse Problems and Imaging,2011,5(1):237-261.
  • 5R Glowinski and A Marrocco.Sur l'approximation parelements nisd'ordreun,etlan resolution par penalisation-dualite,d'une classe de problemes de Dirichlet non lineaires[M].Journal of Equine Veterinary Science,1975,31(s 5-6):41–76.
  • 6Yang J,Yin W,Zhang Y,et al.A fast algorithm foredge-preserving variational multichannel image restoration[J].SIAM Journal on Imaging Sciences,2009,2(2):569-592.
  • 7J.Eckstein and D.Bertsekas,On the Douglas-Rachford splitting method and the proximal point algorithm for maximal monotone operators[M].Mathematical Programming,1992,55:293–318.
  • 8宋锦萍,郑昌燕.高阶模型的快速图像修补[J].计算机工程与应用,2015,51(11):154-157. 被引量:2
  • 9胡学刚,张龙涛,蒋伟.基于偏微分方程的变分去噪模型[J].计算机应用,2012,32(7):1879-1881. 被引量:8

二级参考文献31

  • 1RUDIN L, OSHER S, FATEMI E. Nonlinear total variation based noise removal algorithms [ J]. Physica D: Nonlinear Phenomena, 1992, 60(1-4) : 259 -268.
  • 2AUBERT G, VESE L. A variational method in image recovery [ J]. SIAM Journal on Numerical Analysis, 1997, 34(5): 1948 -1979.
  • 3OSHER S, BURGER M, GOLDFARM D, et al. An iterative regu- larization method for total variation-based image restoration [ J]. SI- AM Multiscale Modeling and Simulation, 2005, 4(2): 460 -489.
  • 4YANG JUN-FENG, YIN WOTAO, ZHANG YIN, et al. A fast algo- rithm for edge-preserving variational multichannel image restoration [J]. SIAM Journal on Imaging Sciences, 2009, 2(2): 569 -592.
  • 5DONG YI-QIU, HINTERMILLER M, RINCON-CAMACHO M M. Automated regularization parameter selection in multi-scale total var- iation models for image restoration [ J]. Journal of Mathematical Im-aging and Vision, 2011, 40(1): 82 -104.
  • 6RUDIN L, LIONSP L, OSHER S. Multiplicative denoising and de- blurring: theory and algorithms [ M]// OSHER S, PARAGIOS N. Geometric Level Set Methods in Images, Vision, and Graphics. Ber- lin: Springer, 2003:103 - 119.
  • 7AUBERT G, AUJOL J-F. A variational approach to removing multi- plicative noise [ J]. SIAM Journal on Applied Mathematics, 2008, 68(4) : 925 -946.
  • 8JIN ZHENG-MENG, YANG XIAO-PING. A variational model to re- move the multiplicative noise in ultrasound images [ J]. Journal of Mathematical Imaging and Vision, 2011, 39(1) : 62 -74.
  • 9HUANG YU-MEI, NG K M, WEN YOU-WEI. A new total varia- tion method for multiplicative noise removal [ J]. SIAM Journal on Imaging Sciences, 2009, 2(1): 20-40.
  • 10JIN ZHENG-MENG, YANG XIAO-PING. Analysis of a new varia- tional model for muhiplicative noise removal [ J]. Journal of Mathe- matical Analysis and Applications, 2010, 262(2): 415 -426.

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