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采用TV及纹理合成技术的分层图像修复 被引量:5

Total variation and texture synthesis applied to multi-level image inpainting
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摘要 整体变分(TV)模型在图像修复中能够保持图像的边缘且数值实现方便,但在图像修复中对于人类视觉连通性的处理还有所不足。根据图像遗失或者损坏的不同类型,针对TV、CDD模型在图像修复中存在的问题,提出了一种结合TV、CDD模型及基于块的纹理合成算法的分层图像修复算法。实验结果表明,这种分层修复的方法在图像的结构修复和纹理修复两方面实现了较好的统一,而且在较大区域图像修复上表现出良好的效果。 Although the Total Variation(TV) model is good at maintaining the edge of damaged images and reducing numerical calculation in image inpainting,it needs more improvement in the vision connectivity.A new image multi-level-inpainting method based on TV model and texture synthesis is proposed.The TV model is used to restore the shape information of missing area in an image.The inpainting result visual connectivity is improved by the CDD model.To the large texture area of the inpainted image,the patch based texture restoration model is used to process the obvious trace insulted from two previous levels inpainting.Experimental results show that the inpainting performance is better both in the structure and the texture.Moreover,the approach can be used in the image inpainting with bigger damaged area.
出处 《计算机工程与应用》 CSCD 北大核心 2011年第23期201-203,211,共4页 Computer Engineering and Applications
基金 国家自然科学基金No.60802047 浙江省科技计划重点项目(No.2008C21092)~~
关键词 图像修复 整体变分(TV) 曲率驱动扩散(CDD)模型 分层修复算法 纹理合成 最小均方误差(MSE) image inpainting Total Variation(TV) Curvature Driven Diffusions(CDD) model multi-level inpainting texture synthesis Mean Square Errors(MSE)
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  • 1王树根,郑精灵.基于纹理匹配的影像缺损信息填充方法[J].测绘通报,2004(12):21-23. 被引量:11
  • 2冈萨里斯.数字图像处理[M].2版.北京:电子工业出版社,2003.
  • 3Perona P, Malik J. Scale Space and Edge Detection Using Anisotropic Diffusion[J]. IEEE Trans. on Pattern Analysis and Machine Intelligence, 1990, 30(12): 629-630.
  • 4陆金甫.偏微分方程差分方法[M].2版.北京:高等教育出版社,1998.
  • 5Goldenberg R, Kimmel R, Rudzsky M. Fast Geodesic Active Contour[J]. IEEE Trans. on Image Processing, 2001, 10(10): 539- 540.
  • 6陈刚.基于偏微分方程的图像处理[M].北京:高等教育出版社,2004.
  • 7Bertalmio M, Sapiro G, and Caselles V, et al.. Image Inpainting. Proceedings of the 27th annual conference on Computer graphics and interactive techniques, New Orleans, 2000: 417-424.
  • 8Chan T and Shen J. Mathematic method for local non-texture inpainting[J]. SIAM J. Appl. Math., 2001, 62(3): 1019-1043.
  • 9Chan T and Shen J. Non-texture inpainting by curvature- driven diffusions (CDD) [J]. Visual Communication and Image Representation, 2001, 12(4): 436-449.
  • 10Criminisi A, Perez P, and Toyama K. Region filling and object removal by exemplar-based image inpainting[J]. IEEE Trans. on Image Processing, 2004, 13(9): 1200-1212.

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  • 1张红英,彭启琮,吴亚东.数字破损图像的非线性各向异性扩散修补算法[J].计算机辅助设计与图形学学报,2006,18(10):1541-1546. 被引量:21
  • 2吴斌,吴亚东,张红英.基于变分偏微分方程的图像复原技术[M].北京:北京大学出版社,2008.
  • 3BERTALMIO M,SAPIRO G,CASELLES V,et al.Image Inpainting[C]∥Proc SIGGRA PH 2000.New Orleans,LA:[s,n.],2000:417-424.
  • 4CHAN T F,SHEN J.Mathematical Models for Local Deterministic Inpaintings[J].Journal on Applied Mathematics,2002,62(3):1019-1043.
  • 5WANG 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.
  • 6MARCELO 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.
  • 7ESEDOGLU S,SHEN J H.Digital Inpainting Based on the Mumford Shah-Euler Image Model[J].European Journal onApplied Mathematics,2002,13(4):353-370.
  • 8CHAN 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.
  • 9CHAN T F,SHEN J H.Mathematieal Models for Local Non-Texture Inpainting[J].SIAM J APPl Math,2001,62(3):1019-1043.
  • 10WEICKERT J.A Review of Nonlinear Diffusion Filtering[C]∥Scale-Space Theory in Computer Vision.London:Springer-Verlag,1997,1252:3-28.

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