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  • 标题:Further Improvements of CFA 3.0 by Combining Inpainting and Pansharpening Techniques
  • 本地全文:下载
  • 作者:Chiman Kwan ; Jude Larkin
  • 期刊名称:Signal & Image Processing : An International Journal (SIPIJ)
  • 印刷版ISSN:2229-3922
  • 电子版ISSN:0976-710X
  • 出版年度:2020
  • 卷号:11
  • 期号:6
  • 页码:1-19
  • DOI:10.5121/sipij.2020.11601
  • 出版社:Academy & Industry Research Collaboration Center (AIRCC)
  • 摘要:Color Filter Array (CFA) has been widely used in digital cameras. There are many variants of CFAs in the literature. Recently, a new CFA known as CFA 3.0 was proposed by us and has been shown to yield reasonable performance as compared to some standard ones. In this paper, we investigate the use of inpainting algorithms to further improve the demosaicing performance of CFA 3.0. Six conventional and deep learning based inpainting algorithms were compared. Extensive experiments demonstrated that one algorithm improved over other approaches.
  • 关键词:CFA 3.0;color filter array;demosaicing;inpainting;deep learning;pansharpening
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