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Image Affine Inpainting

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Image Analysis and Recognition (ICIAR 2008)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5112))

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Abstract

Exemplar-based inpainting techniques demonstrate some advantages in filling both textural and structural images, based upon the simple process of patch sampling and copying. An implicit assumption of such methods is that an exemplar patch could be found for copying. But the assumption might be false for images with complex structures, resulting in inpainting artefact. To inpaint structure and texture more efficiently, this paper adopts a weak assumption that affine transformed patches could be found for filling unknown regions. The algorithm based on this assumption firstly establishes the affine relation between the unknown region and a source patch, then transform the source pixels to fill the unknowns. This algorithm generates more satisfying inpainting results, as illustrated by the provided experiments.

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Author information

Authors and Affiliations

  1. Image Processing Center, Beihang University, Beijing, 100083, China

    Zhaozhong Wang

Authors
  1. Zhaozhong Wang
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Editor information

Aurélio Campilho Mohamed Kamel

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© 2008 Springer-Verlag Berlin Heidelberg

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Wang, Z. (2008). Image Affine Inpainting. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2008. Lecture Notes in Computer Science, vol 5112. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69812-8_106

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  • DOI: https://doi.org/10.1007/978-3-540-69812-8_106

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-69811-1

  • Online ISBN: 978-3-540-69812-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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