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一种偏微分方程图像平滑方法 被引量：1

A Partial Differential Equations Smoothing Method
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摘要 在各向异性扩散图像平滑的过程中,保持图像平滑性及保留图像特征都很重要。本文将复域内的扩散过程 与实数域内的扩散过程结合起来,使扩散过程具有更好的平滑效果,并能更好保持图像边缘,用实验证明该方法的有效性。 In the course of noise removal by means of anisotropic diffusion method, it is important to keep image smoothing and to preserve image feature. In this paper , anisotropic diffusion in real field and anisotropic diffusion in complex field are combined .Therefore ,better smoothing is obtained and image edge is preserved well. Experiment result show that this method is valid.
作者 李兰兰 吴乐南
机构地区 东南大学无线电工程系
出处 《信号处理》 CSCD 2004年第6期655-657,共3页 Journal of Signal Processing
关键词 扩散过程 偏微分方程 实数域 实验证明 复域 保持 图像平滑 图像边缘 各向异性扩散 图像特征 <Keyword>anisotropic diffusion partial differential equations denoise
分类号 TP391 [自动化与计算机技术—计算机应用技术] O211 [理学—概率论与数理统计]
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参考文献5

  • 1P.Pernoa and J.Malik, "Scale-space and edge detection using anisotropic diffusion" , IEEE Trans, Pat. Anal.Machine Intel.. PAMI-12(7), 629-639(1990).
  • 2C. Andrew, et al., "Morphological anisotropic diffusion ",Proc. of International Conference on Image Processing,Vol. 3, 1997, 348-351.
  • 3Guy Gilboa, Yehoshua Y.Zeevi, and Nit A,Sochen, '+char(34)+'Complex Diffusion Procession for Image Filtering'+char(34)+' , in Proc. of Third Intemational Conference, Vancouver,Canada, July 2001.
  • 4Rene A.Carmona, Sifen Zhong, "Adaptive Smoothing Respecting Feature Directions" , IEEE Transactions, on Image Processing, 7(3), 1998.
  • 5Alvarez L,Lions P L, Morel J M.Image selective smoothing and edge detection by nonlinear diffusion Ⅱ[J].SIAM J Number Anal,1992,29(3):845-866.

同被引文献15

  • 1Rudin L l,Osher S,Fatemi E. Nonlinear Total Variation Based Noise Removal Algorithms [ J ]. physica D, 1992,60:259 - 268.
  • 2Pietro Perona, Jitendra Malik. Scale-Space and Edge Detection Using Anisotropie Diffusion[ J ]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1990,12 (7) :629 -639.
  • 3CatteFrancine, LionsPierre-Louis, Morel Jean-Michel, et al. Image selective smoothing and edge detection by nonlinear diffusion [ J ]. SIAM SIAM Journal on Numerical Analysis, 1992,29 ( 3 ) : 182 - 193.
  • 4You Y-L, Kaveh M. Fourth-Order Partial Differential Equations for Noise Removal [J ] . IEEE Trans on Image Processing,2000,9 (10) : 1723 - 1730.
  • 5Patrick Guidotti. A new well-posed nonlinear nonlocal diffusion[ J ]. Nonli-near Analysis : Theory, Methods & Applications, 2010,72 ( 12 ) : 4625 - 4637.
  • 6Patrick Guidotti ,James V Lambers. Two New Nonlinear Nonlocal Diffusions for Noise Reduction[ J]. Journal of Mathematical Imaging and Vision,2009,33 ( 1 ) :25 - 37.
  • 7Kashif Rajpoot,Nasir Rajpoot, Ahson J Noble. Discrete Wavelet Diffu- sion for Image Denoising [ J ]. Lecture Notes in Computer Science, 2008,5099 ;20 - 28.
  • 8Elhamidi A, Ménard M, Lugiez M, et al. Weighted and extended total variation for image restoration and decomposition [ J ]. Pattern Recogni- tion ,2010,43 (4) : 1564 - 1576.
  • 9Antoni Buades,Jean-Michel Morel. A non-local algorithm for image denoising[ C]//Proc. of IEEE International Conference on Computer Vision and Pattern Recognition. 2005,2 : 60 - 65.
  • 10杜宏伟.基于偏微分方程的图像去噪综合模型[J].计算机工程与应用,2008,44(20):198-201. 被引量：13

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信号处理
2004年 第6期

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