• DocumentCode
    3404304
  • Title

    Video compressive sensing with 3-D Wavelet and 3-D Noiselet

  • Author

    Dao Lam ; Wunsch, D.

  • Author_Institution
    Dept. of Comput. Eng., Missouri Univ. of Sci. & Technol., Rolla, MO, USA
  • fYear
    2012
  • fDate
    Sept. 30 2012-Oct. 3 2012
  • Firstpage
    893
  • Lastpage
    896
  • Abstract
    A new compressive video sampling method is investigated. As opposed to other video sampling methods for which processing is conducted on a single-frame basis, this method is applied on multiple frames of the video stream. By exploiting the extension of Wavelet to 3-D with the support of Noiselet 3-D and combining it with fast reconstruction algorithms, this framework produces successful results quickly while maintaining the quality of the video stream. Despite its simplicty, this new approach outperforms other sophisticated methods.
  • Keywords
    compressed sensing; image reconstruction; image sampling; image sequences; video coding; video streaming; wavelet transforms; 3D noiselet; 3D wavelet; compressive video sampling method; fast reconstruction algorithms; video compressive sensing; video stream frames; video stream quality maintenance; Compressed sensing; Image coding; Image reconstruction; PSNR; Volume measurement; Wavelet transforms; ℓ1-norm; Compressive sensing; Noiselet; Wavelet; video coding;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing (ICIP), 2012 19th IEEE International Conference on
  • Conference_Location
    Orlando, FL
  • ISSN
    1522-4880
  • Print_ISBN
    978-1-4673-2534-9
  • Electronic_ISBN
    1522-4880
  • Type

    conf

  • DOI
    10.1109/ICIP.2012.6467004
  • Filename
    6467004