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基于改进优先级的加权匹配图像修复算法 被引量:10

A weighted matching image restoration algorithm based on modified priority
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摘要 文章对纹理合成Criminisi算法中优先级的确定以及匹配块的选取分别作了改进,提出了一种基于改进优先级的加权匹配的图像修复算法,在优先级中考虑了图像显著结构的影响,使改进的优先级更加精确;提出了更为合理的加权匹配因子,并根据图像结构相似性特征对图像进行分块修复;实验表明,改进后的算法不仅克服了现有算法可能存在的偏差延续问题,使图像修复的结果更加符合人们的视觉效果,而且大大缩短了修复时间。 In this paper, a weighted matching image restoration algorithm based on the modified priori- ty is given by improving the priority setting and the matching block selection in the Criminisi texture systhesis algorithm. Firstly, the influence of the image significant structure is taken into account in the priority of the new algorithm, which makes the modified priority more accurate. Secondly, the matching block in the new method is given a more reasonable weighted matching factor. Finally, the image is restored by the new method based on the image segmentation according to the image structure similar characteristics. The experimental results show that the algorithm introduced in the paper a- voids the possible bias diffusion by the current image restoration algorithms, makes the restored image more consistent to human being's visual effects, and reduces greatly the time consumed.
出处 《合肥工业大学学报(自然科学版)》 CAS CSCD 北大核心 2013年第1期113-118,共6页 Journal of Hefei University of Technology:Natural Science
基金 教育部科学技术研究重大资助项目(309017) 留学回国人员科研启动基金资助项目(2010JYLH0322) 安徽省自然科学基金资助项目(11040606M06) 国家大学生创新性实验计划资助项目(101035937)
关键词 纹理合成 图像修复 优先级 匹配块 分块 texture synthesis l image restoratiom priority l matching block~ image segmentation
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参考文献22

  • 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:159
  • 2Masnou S,Model J. Level lines based disocclusion[A].1998.259-263.
  • 3Bertalmio M,Sapiro G,Caselles V. Image inpainting[A].New Orleans,Louisiana,USA,2000.417-424.
  • 4Chan T F,Shen J. Non-texture inpainting by curvaturedriven diffusions(CDD)[J].Journal of Visual Communication and Image Representation,2001,(04):436-449.
  • 5Chan T F,Shen J. Mathematical models for local nontexture inpaintings[J].SIAM Journal on Applied Math,2001,(03):1019-1043.
  • 6Lu Xiaobao,Wang Weilan,Duojie Zhuoma. A fast image inpainting algorithm based on TV model[A].Hong Kong,March,2010.1457-1460.
  • 7Li Fang,Shen Chaomin,Liu Ruihua. A fast implementation algorithm of TV inpainting model based on operator splitting method[J].Computers and Electrical Engineering,2011.782-788.
  • 8Li Fang,Bao Zheng,Liu Ruihua. Fast image inpainting and colorization by,Chambolle's dual method[J].Journal of Visual Communication and Image Representation,2011.529-542.
  • 9Lin Chang,Yu Chongxiu. New interpolation algorithm for image inpainting[J].Physics Procedia,2011.107-111.
  • 10Li Qia,Shen Lixin,Yang Lihua. Split-bregrnan iteration for framelet based image inpainting[J].Appl Comput Harmon Ana,2012.145-154.

二级参考文献42

  • 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薛峰,张佑生,江巨浪,胡敏.一种快速、有效的纹理合成方法[J].合肥工业大学学报(自然科学版),2005,28(11):1361-1364. 被引量:6
  • 3Efros A,Leung T.Texture synthesis by non-parametric sampling[C]//Proc Int Conf Computer Vision,Kerkyra Greece,September,1999:1033-1038.
  • 4Criminisi A,Perez P,Toyama K.Object removal by exemplar-based inpainting[C]//Proc Conf Comp Vision Pattern Rec,Madison WI,2003:721-728.
  • 5Bertalmio M,Sapiro G,Caselles V,et al.Image inpainting[C]//Proceedings of SIGGRAPH'2000.ACM Press,2000:411-424.
  • 6Criminisi A,Perez P,Toyama K.Region filling and object removal by exemplar-based image inpainting[J].IEEE Transactions on Image Processing,2004,13(9):1200-1212.
  • 7Chan T F,Shen J.Mathematical models for local nontexture inpaintings[J].SIAM Journal on Applied Mathematics,2001,62(3):1019-1043.
  • 8Bertalmio M,Sapiro G,Caselles V,et al.Image inpainting[A].In:Proceedings of International Conference on Computer Graphics and Interactive Techniques[C],New Orleans,Louisiana,USA,2000:417 -424.
  • 9Chan T F,Shen J H.Non-texture inpainting by curvature-driven diffusions (CDD)[J].Journal of Visual Communication and Image Representation,2001,12(4):436 -449.
  • 10Chan T F,Shen J H.Mathematical models for local non-texture inpainting[J].SIAM Journal of Applied Mathematics,2001,62(3):1019 -1043.

共引文献164

同被引文献66

  • 1唐丽,吴成柯,刘侍刚,颜尧平.基于区域增长的立体像对稠密匹配算法[J].计算机学报,2004,27(7):936-943. 被引量:27
  • 2朱晓临,陈晓冬,朱园珠,陈嫚,李雪艳.基于显著结构重构与纹理合成的图像修复算法[J].图学学报,2014,35(3):336-342. 被引量:12
  • 3周秀芝,文贡坚,王润生.自适应窗口快速立体匹配[J].计算机学报,2006,29(3):473-479. 被引量:32
  • 4闫建平,首祥云,邵在平,姚声贤,赵中明.成像测井图像的动态增强及Morphing方法[J].测井技术,2006,30(4):364-366. 被引量:11
  • 5Scharstein D, Szeliski R. A taxonomy and evaluation ofdense two-frame stereo correspondence algorithms[J]. In-ternational Journal of Computer Vision, 2002,47(1/2/3):7-42.
  • 6Sun J,Shum H Y,Zheng N N. Stereo matching using beliefpropagation[J]. IEEE Transactions on Pattern Analysisand Machine Intelligence * 2003,25 (7) : 787-800.
  • 7Bleyer M,Gelautz M. A layered stereo matching algorithmusing image segmentation and global visibility constraints[J], ISPRS Journal of Photogrammetry and Remote Sens-ing,2005,59(3):128-150.
  • 8Yoon K J, Kweon I S. Adaptive support-weight approachfor correspondence search[J]. IEEE Transactions on Pat-tern Analysis and Machine Intelligence, 2006,28(4):650-656.
  • 9Wang Z F, Zheng Z G. A region based stereo matching al-gorithm using cooperative optimization[C]//IEEE Con-ference on Computer Vision and Pattern Recognition,2008:1-8.
  • 10Mei X,Sun X,Zhou M C,et al. On building an accuratestereo matching system on graphics hardware [ C]//GPUCV,2011 :467-474.

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