Image Inpainting Considering Brightness Change and Spatial Locality of Textures and Its Evaluation

  • Authors:
  • Norihiko Kawai;Tomokazu Sato;Naokazu Yokoya

  • Affiliations:
  • Graduate School of Information Science, Nara Institute of Science and Technology, Nara, Japan 630-0192;Graduate School of Information Science, Nara Institute of Science and Technology, Nara, Japan 630-0192;Graduate School of Information Science, Nara Institute of Science and Technology, Nara, Japan 630-0192

  • Venue:
  • PSIVT '09 Proceedings of the 3rd Pacific Rim Symposium on Advances in Image and Video Technology
  • Year:
  • 2009

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Abstract

Image inpainting techniques have been widely investigated to remove undesired objects in an image. Conventionally, missing parts in an image are completed by optimizing the objective function using pattern similarity. However, unnatural textures are easily generated due to two factors: (1) available samples in the image are quite limited, and (2) pattern similarity is one of the required conditions but is not sufficient for reproducing natural textures. In this paper, we propose a new energy function based on the pattern similarity considering brightness changes of sample textures (for (1)) and introducing spatial locality as an additional constraint (for (2)). The effectiveness of the proposed method is successfully demonstrated by qualitative and quantitative evaluation. Furthermore, the evaluation methods used in much inpainting research are discussed.