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  • 标题:Image Inpainting and Enhancement using Fractional Order Variational Model
  • 本地全文:下载
  • 作者:G. Sridevi ; Srinivas Kumar
  • 期刊名称:Defence Science Journal
  • 印刷版ISSN:0976-464X
  • 出版年度:2017
  • 卷号:67
  • 期号:3
  • 页码:308-315
  • 语种:English
  • 出版社:Defence Scientific Information & Documentation Centre
  • 摘要:The intention of image inpainting is to complete or fill the corrupted or missing zones of an image by considering the knowledge from the source region. A novel fractional order variational image inpainting model in reference to Caputo definition is introduced in this article. First, the fractional differential, and its numerical methods are represented according to Caputo definition. Then, a fractional differential mask is represented in 8-directions. The complex diffusivity function is also defined to preserve the edges. Finally, the missing regions are filled by using variational model with fractional differentials of 8-directions. The simulation results and analysis display that the new model not only inpaints the missing regions, but also heightens the contrast of the image. The inpainted images have better visual quality than other fractional differential filters.
  • 关键词:Fractional calculus;Image inpainting;PDE models;Variational model
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