计算机科学 ›› 2016, Vol. 43 ›› Issue (Z6): 214-216.doi: 10.11896/j.issn.1002-137X.2016.6A.051

• 模式识别与图像处理 • 上一篇    下一篇

用于彩色图像复原的带有高阶耦合项的TV模型

马洪华,黄永林,丁岩岩   

  1. 湖北工程学院物理与电子信息工程学院 孝感432000,湖北工程学院物理与电子信息工程学院 孝感432000,湖北工程学院新技术学院 孝感432000
  • 出版日期:2018-12-01 发布日期:2018-12-01
  • 基金资助:
    本文受湖北省自然科学基金项目(2015CFC770)资助

Total Variance with High-order Coupling Term for Color Image Restoration

MA Hong-hua, HUANG Yong-lin and DING Yan-yan   

  • Online:2018-12-01 Published:2018-12-01

摘要: 提出了一种改进的TV(Total Variance)彩色图像复原方法。为消除TV模型的各向异性扩散导致的块效应,采用在TV模型的基础上耦合高阶项的新模型;并将这个新的模型推广到彩色图像,利用多通道的耦合机制实现各单色通道图像复原过程的相互制约。新模型保持了各向异性扩散的特性,图像的边缘得到了保持。实验结果证明, 与其它模型的复原 彩色图像相比,新模型复原的图像的峰值信噪比(PSNR)有了更大的提高,图像的非边缘区看上去更加平滑自然。

关键词: 整体方差,四阶偏微分,各向异性扩散,彩色图像复原

Abstract: A new total variance for color image restoration method was proposed.To overcome blocky effect produced by anisotropic diffusion of TV model,high-order term was added to TV model.In the process of color image restoration,multi-channel coupled mechanism was used to realize mutual constraints between different monochrome channels.The new model is able to preserve edges because of the characteristic of anisotropic diffusion.The experimental results show that the images processed by the proposed model have higher PSNR (Peak Signal to Noise Ratio) than these processed by other models,and the non-boundary region looks more natural.

Key words: Total variance,Fourth-order PDE,Anisotropic diffusion,Restoration of color image

[1] Yao Min.Digital image process[M].Beijing:China Machine Press,2006:97-103
[2] Chan T F,Golub G,Mulet P.A nonlinear primal-dual method for total variation-based image restoration[J].SIAM J.Sci.Comp,1999,20:1964-1977
[3] You Y,Xu W,Tannenbaum A,et al.Behavioral Analysis of Anisotropic Diffusion in Image Processing[J].IEEE Trans on Ima-ge Process,1996,5(11):1539-1553
[4] Xie Mei-hua,Wang Zheng-ming.Image restoration based onedge-directed diffusion[J].Journal of Optoelectronics·Laser,2005,6(9):1107-1111
[5] Strong D M.Adaptive Total Variational Minimizing Image Restoration[D].Los Angeles:University of California,1997
[6] Fu Shui-jun,Ruan Qiu-qi,Wang Wen-qia.A Shock-diffusion Equation with Local Coupling Term for Image Sharpening[J].Journal of Optoelectronics·Laser,2007,8(2):245-248
[7] Wu Ji-ying,Ruan Qiu-qi.Helmholtz vorticity equation and third order PDE coupled image inpainting model[J].Journal of Optoelectronics·Laser,2008,9(8):1104-1107
[8] Blomgren P,Chan T F.Color TV:Total variation method forrestoration of vector valued image[J].IEEE,IP,1998,7(3):304-309
[9] Sochen N,Kimmel R,Malladi R.A general framework for low level vision[J].IEEE Trans.Image Processing,1998,31(7),310-318
[10] Sochen N,Zeevi Y Y.Representation of colored images by manifolds embedded in higher dimensional non-Euclisean space[C]∥Proc.IEEE ICIP’98.Chicago,1998
[11] Guy Gil-boa.Super-resolution Algorithms Based on Inverse Diffusion-type Processes[D].USA:University of California at Los Angeles,2004:55-62
[12] Rudin L,Osher S,Fatemi E.Nonlinear Total Variation basednoise removal algorithms[J].Physica D 60, 1992:259-268
[13] Rudin L,Osher S.Total Variation Based Image Restoration with Free Local Constraints[C]∥Proceedings of the First IEEE International Conference on Image Processing.Austin,Texas,USA:IEEE Press,1994
[14] You Y L,Kaveh M.Fourth-order partial differential equation for noise removal[J].IEEE Transactions on Image Processing,2000,9:1723-1730
[15] Zhang Yu-jing.Image Segmentation[M].Beijing:Science Press,2001:9-16

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