• DocumentCode
    42928
  • Title

    Exemplar-Based Image Inpainting Using Multiscale Graph Cuts

  • Author

    Yunqiang Liu ; Caselles, Vicent

  • Author_Institution
    Barcelona Media - Innovation Center, Barcelona, Spain
  • Volume
    22
  • Issue
    5
  • fYear
    2013
  • fDate
    May-13
  • Firstpage
    1699
  • Lastpage
    1711
  • Abstract
    We present a novel formulation of exemplar-based inpainting as a global energy optimization problem, written in terms of the offset map. The proposed energy function combines a data attachment term that ensures the continuity of reconstruction at the boundary of the inpainting domain with a smoothness term that ensures a visually coherent reconstruction inside the hole. This formulation is adapted to obtain a global minimum using the graph cuts algorithm. To reduce the computational complexity, we propose an efficient multiscale graph cuts algorithm. To compensate the loss of information at low resolution levels, we use a feature representation computed at the original image resolution. This permits alleviation of the ambiguity induced by comparing only color information when the image is represented at low resolution levels. Our experiments show how well the proposed algorithm performs compared with other recent algorithms.
  • Keywords
    computational complexity; graph theory; image colour analysis; image reconstruction; image representation; image resolution; optimisation; color information; computational complexity; energy function; exemplar-based image inpainting; feature representation; global energy optimization; image reconstruction; image resolution; multiscale graph cuts algorithm; Image color analysis; Image reconstruction; Image resolution; Labeling; Minimization; Optimization; Vectors; Feature vector; graph cuts; image inpainting; offset map;
  • fLanguage
    English
  • Journal_Title
    Image Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1057-7149
  • Type

    jour

  • DOI
    10.1109/TIP.2012.2218828
  • Filename
    6302193