• Title/Summary/Keyword: exemplar-based techniques

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Exemplar-Based Image Inpainting for Spherical Panoramic Image (구면 파노라마 영상을 위한 표본 기반 영상 인페인팅)

  • Kim, Bosung;Park, Jong-Seung
    • Journal of KIISE
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    • v.43 no.4
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    • pp.437-449
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    • 2016
  • Previous image processing techniques based on plane-to-plane transformations cannot be utilized for spherical panoramic images. In this paper, we propose a new method to inpaint a spherical panoramic image using exemplar, which is deformed by the location of the patch. Our proposed method makes the deformed exemplar patch by latitude and uses it as the reference patch to restore the damaged area. The exemplar-based inpainting method is based on the planar image coordinate system and thus the classical method cannot be applied to the spherical panoramic image. The merit of our proposed method is the fact that it is not dependent on the location of the damaged area. From the experimental results, we proved that our proposed method satisfies the original purpose of the exemplar-based inpainting technique for the spherical panoramic image.

Patch size adaptive image inpainting

  • Liu, Huaming;Lu, Guanming;Bi, Xuehui;Wang, Weilan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.10
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    • pp.3642-3667
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    • 2021
  • Texture synthesis technology has the advantages of repairing texture and structure at the same time. However, during the filling process, the size of the patch is fixed, and the content of the filling is not fully considered. In order to be able to adaptively change the patch size, we used the exemplar-based inpainting technique as the test algorithm, considering the image structure and texture, calculated the image structure patch size and texture patch size, and comprehensively determined the image patch size. This can adaptively change the patch size according to the filling content. In addition, we use multi-layer images to calculate the priority, so that the order of image repair was more stable. The proposed repair algorithm is compared with other image repair algorithms. The experimental results showed that the proposed adaptive image repair algorithm can better repair the texture and structure of the image, which proved the effectiveness of the proposed algorithm.