• DocumentCode
    2227191
  • Title

    Progressive compressive imaging by single-pixel imager

  • Author

    Zelong Wang ; Jubo Zhu ; Fengxia Yan

  • Author_Institution
    Dept. of Math. & Syst. Sci., Nat. Univ. of Defense Technol., Changsha, China
  • fYear
    2013
  • fDate
    5-8 Aug. 2013
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    The progressive compressive imaging by single-pixel imager is presented in this paper. We aim to offer the online control of the tradeoff between the sampling rate and the quality of the recovered image and avoid the need of a priori knowledge of the object sparsity. Moreover, we can implement the proposed approach by the innovation method to reduce the computation complexity and the memory requirements as well as improving the recovery precision. We also show the stopping rule and the finite truncation for the innovation method. The results in the numerical simulations show the feasibility of the proposed method.
  • Keywords
    computational complexity; image sampling; numerical analysis; computation complexity; finite truncation; memory requirements; numerical simulations; object sparsity; progressive compressive imaging; recovered image; sampling rate; single-pixel imager; stopping rule; Complexity theory; Compressed sensing; Image coding; Numerical simulation; Optical imaging; Technological innovation; Compressive imaging; Progressive imaging; finite truncation; innovation method; single-pixel imager; stopping rule;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing, Communication and Computing (ICSPCC), 2013 IEEE International Conference on
  • Conference_Location
    KunMing
  • Type

    conf

  • DOI
    10.1109/ICSPCC.2013.6663919
  • Filename
    6663919