An Image Inpainting Algorithm Based on Local Geometric Similarity

  • Pan Qi
  • Xiaonan Luo
  • Jiwu Zhu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5371)


This paper proposes a novel noniterative orientation adaptive image inpainting algorithm. Assuming the image can be locally modeled, the filling process is formulated as a linear optimization problem, which the optimal coefficients can be adapted to match an arbitrary-oriented edge based on local geometric similarity. We provided A Weighted Least Square (WLS) method is provided to offer a convenient way of finding the optimal solution, which the weight function is selected based on the non local means. We also present Group Marching method (GMM) as the propagation scheme such that sharp edges are well propagated into the missing region layer by layer while maintaining the local geometric similarity. A number of examples on real and synthetic images demonstrate the effectiveness of our algorithm.


Edge-directed Fast Marching Method (FMM) Inpainting Interpolation Least Square Method 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Pan Qi
    • 1
    • 2
  • Xiaonan Luo
    • 1
    • 2
  • Jiwu Zhu
    • 3
  1. 1.Computer Application InstituteSun Yat-Sen UniversityGuangzhouChina
  2. 2.Key Laboratory of Digital Life(Sun Yat-Sen University)Ministry of EducationChina
  3. 3.Dept. MarketingGuangdong Pharmaceutical UniversityGuangzhouChina

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