• DocumentCode
    2816676
  • Title

    Multi-scale Non-Local Kernel Regression for super resolution

  • Author

    Zhang, Haichao ; Yang, Jianchao ; Zhang, Yanning ; Huang, Thomas S.

  • Author_Institution
    Sch. of Comput. Sci., Northwestern Polytech. Univ., Xi´´an, China
  • fYear
    2011
  • fDate
    11-14 Sept. 2011
  • Firstpage
    1353
  • Lastpage
    1356
  • Abstract
    In this paper, we propose an extension of the Non-Local Kernel Regression (NL-KR) method and apply it to super-resolution (SR) tasks. The proposed method extends NL-KR via generalizing the self-similarity from single-scale to multi-scale, and propose an effective SR algorithm using the proposed multi-scale NL-KR model. Experimental results on both synthetic and real images demonstrate the effectiveness of the proposed method.
  • Keywords
    image resolution; regression analysis; multiscale nonlocal kernel regression; real images; self similarity; super resolution; synthetic images; Image edge detection; Image resolution; Image restoration; Kernel; PSNR; Strontium; Non-Local Kernel Regression; image restoration; local structural regularity; multi-scale self-similarity; super resolution;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing (ICIP), 2011 18th IEEE International Conference on
  • Conference_Location
    Brussels
  • ISSN
    1522-4880
  • Print_ISBN
    978-1-4577-1304-0
  • Electronic_ISBN
    1522-4880
  • Type

    conf

  • DOI
    10.1109/ICIP.2011.6115688
  • Filename
    6115688
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2816676