• DocumentCode
    2058646
  • Title

    Extended Basis Pursuit Model and Its Application in Image De-noising

  • Author

    Liang, Dian-Nong ; Zhu Ju-Bo ; Wang Chun-Ling ; Liang Dian-Nong

  • Author_Institution
    Dept. of Math., Nat. Univ. of Defence Technol., Changsha, China
  • fYear
    2009
  • fDate
    11-14 Aug. 2009
  • Firstpage
    295
  • Lastpage
    299
  • Abstract
    Traditional Basis Pursuit model is adapted to signal de-noising under additive Gaussian noise. Based on the different fitness error term, one new kind Extended Basis Pursuit De-Noising (EBPDN) model is brought forward and applied into salt-and-pepper noise removal. A comparison study of performance of the median filter, the peak-and-valley filter, the detail preserving filter and the EBPDN model is carried out using different types of images. EBPDN model can provide good de-noising results and outperforms other filters in terms of noise suppression and detail preservation.
  • Keywords
    Gaussian noise; image denoising; median filters; additive Gaussian noise; extended basis pursuit denoising model; fitness error term; image denoising; median filter; noise suppression; peak-and-valley filter; salt and pepper noise removal; signal denoising; Additive noise; Dictionaries; Filters; Gaussian noise; Image denoising; Mathematical model; Noise reduction; Pixel; Signal denoising; Working environment noise; Basis Pursuit; Image De-noising; sparse representation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Graphics, Imaging and Visualization, 2009. CGIV '09. Sixth International Conference on
  • Conference_Location
    Tianjin
  • Print_ISBN
    978-0-7695-3789-4
  • Type

    conf

  • DOI
    10.1109/CGIV.2009.85
  • Filename
    5298848