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基于偏微分方程的图像修复算法 被引量:8

Based on Partial Differential Equations of Image Inpainting
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摘要 针对TV模型修复算法只沿梯度垂直方向扩散,容易在平滑区域引入阶梯效应,迭代效率低,易产生假边缘的缺点,分析比较了TV图像修复模型的性能,提出了一种改进的图像修复算法。该算法同时结合了各向同性和各向异性扩散,利用区域频率差异实现了在不同的区域使用不同的迭代方程,有效避免了原始算法引入的阶梯效应,提高了迭代效率。实验结果表明,该算法与TV模型算法相比,在具有同样修复效果的前提下,避免了阶梯效应并优于TV模型的修复速度。 TV image inpainting only repairs algorithm along the vertical direction,making diffusion gradi- ent in smooth area into stair step effect, reducing iterative efficiency,producing false edge faults. We ana- lyse and compare the TV image restoration model and repair the performance of the model is put forward in this paper. Puts forward an improved image restoration algorithm,the algorithm in combination with the isotropic and anisotropic diffusion, the use of regional frequency difference in different area realized the use of different iterative equations, effectively avoid the original algorithm introduces ladder effect,to improve the iterative efficiency. The experimental results show that the algorithm and the TV algo- rithm, have the same effect on the premise of repair, the algorithm avoids the stair step effect at the same time with the model is better than TV repair speed.
出处 《吉林大学学报(信息科学版)》 CAS 2012年第1期72-77,共6页 Journal of Jilin University(Information Science Edition)
关键词 图像修复 各向同性 各向异性 TV模型 阶梯效应 image inpainting isotropic diffusion anisotropy diffusion TV model step effect
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参考文献17

  • 1张红英,彭启琮.数字图像修复技术综述[J].中国图象图形学报,2007,12(1):1-10. 被引量:163
  • 2刘树昌,刘鹏,王延海,李小明,张同.大容量高速视频图像传输技术研究[J].吉林大学学报(信息科学版),2011,29(1):21-25. 被引量:8
  • 3张春彦,赵岩,陈贺新.基于边缘检测的深度图与单视图配准算法[J].吉林大学学报(信息科学版),2011,29(3):175-180. 被引量:4
  • 4邵向鑫,郭树旭,王朗.基于边缘扩展相位相关的图像拼接算法[J].吉林大学学报(信息科学版),2010,28(1):95-99. 被引量:8
  • 5BERTALMIO M,SAPIRO G,CASELLES V,et al.Image Inpainting[C]∥Proc SIGGRA PH 2000.New Orleans,LA:[s,n.],2000:417-424.
  • 6CHAN T F,SHEN J.Mathematical Models for Local Deterministic Inpaintings[J].Journal on Applied Mathematics,2002,62(3):1019-1043.
  • 7WANG Wei-wei,FENG Xiang-chu.Anisotropic Diffusion with Nonlinear Structure Tensor[J].SIAM Joumal on Multi-scale Modeling and Simulation,2008,7(2):963-977.
  • 8MARCELO BERTALMIO,LUMINITA VESE,GUILLERMO SAPIRO,et al.Simultaneous Structure and Texture Im-age Inpainting[J].IEEE Trans on Image Processin,2003,12(8):882-889.
  • 9ESEDOGLU S,SHEN J H.Digital Inpainting Based on the Mumford Shah-Euler Image Model[J].European Journal onApplied Mathematics,2002,13(4):353-370.
  • 10CHAN T F,SHEN J.Non-Texture Inpainting by Curvature-Driven Diffusions(CDD)[J].Journal on Visual Communi-cation and Image Representation,2001,12(4):436-449.

二级参考文献124

共引文献184

同被引文献89

  • 1周贤,刘义伦.X光图像中缺陷的自动提取方法研究[J].光学学报,2006,26(7):1016-1020. 被引量:17
  • 2国九英,周兴元.F-K域等道距道内插[J].石油地球物理勘探,1996,31(2):211-218. 被引量:43
  • 3王备,王继成.图像分割中模糊聚类数目的确定[J].计算机技术与发展,2007,17(10):162-164. 被引量:7
  • 4FARID H. Image forgery detectionEJ:. IEEE Signal Processing Magazine, 2009,26(2) :16-25.
  • 5VINCENT C,CHRISTIAN R,JOHANNES J,et al. An evaluation of popular copy-move forgery detection approaches[J]. IEEE Trans on Information Forensics and Security,2012,7(6):1841-1853.
  • 6LYNCH G, SHIH F Y,LIAO H Y M. An efficient expanding block algorithm for image copy-move forgery detection[J]. Informa- tion Sciences, 2013,239 ( 1 ) : 253-265.
  • 7FRIDRICH J,SOUKAL D,LUKAS J. Detection of copy-move forgery in digital images[G]//Proceedings of the Digital Forensic Research Workshop. Cleveland OH, USA, 2003.
  • 8DONG J, WANG W,TAN T. Run-length and edge statistics based approach for image splicing deteetio[G] // Digital Watermark- ing. Springer Berlin Heidelberg, 2009 ; 76-87.
  • 9sPENG F, NIE Y Y,LONG M. A complete passive blind image copy move forensics scheme based on compound statistics features [J]. Forensic Science International,2011,212(1-3) :21-25.
  • 10MAHDIAN B, SAIC S. Detection of copy-move forgery using a method based on blur moment invariants[J]. Forensic Science In- ternational, 2007,171(2) : 180:189.

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