• DocumentCode
    2816114
  • Title

    On sparse representations of color images

  • Author

    Wu, Xiaolin ; Zhai, Guangtao

  • Author_Institution
    Dept. of Electr. & Comput. Eng., McMaster Univ., Hamilton, ON, Canada
  • fYear
    2011
  • fDate
    11-14 Sept. 2011
  • Firstpage
    1229
  • Lastpage
    1232
  • Abstract
    We investigate an intrinsic and useful form of sparsity of color images that was largely overlooked in the literature of image/video processing. This sparsity of multispectral images is revealed and formulated by modeling the image formation process. The underlying new sparse representations of color images are general and can be exploited to improve the performance of existing image restoration algorithms, such as denoising, deblurring, and resolution upconversion.
  • Keywords
    image colour analysis; image representation; image restoration; inverse problems; color images; image processing; image restoration algorithms; inverse problem; multispectral images; sparse representations; video processing; Color; Deconvolution; Image restoration; Materials; Noise reduction; Surface waves; Sparse representations of images; image formation model; image restoration; inverse problem;
  • 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.2011.6115654
  • Filename
    6115654