• DocumentCode
    2456009
  • Title

    Power Iteration Denoising

  • Author

    Gomo, Panganai ; Spann, Mike

  • Author_Institution
    EECE, Univ. of Birmingham, Birmingham, UK
  • fYear
    2010
  • fDate
    12-14 Dec. 2010
  • Firstpage
    846
  • Lastpage
    850
  • Abstract
    We present a simple method for image denoising called power iteration denoising (PID). PID finds a low dimensional embedding of the image data using a truncated power iteration on a normalized pair-wise similarity matrix generated from the image. This embedding turns out to be an effective denoising algorithm outperforming the widely used non-local means algorithm. We apply this method to the denoising of noisy digital camera images producing visually pleasing results.
  • Keywords
    cameras; image denoising; denoising algorithm; image data; image denoising; low dimensional embedding; noisy digital camera images; nonlocal means algorithm; normalized pairwise similarity matrix; power iteration denoising; truncated power iteration; Clustering algorithms; Image denoising; Laplace equations; Noise measurement; Noise reduction; PSNR; Pixel; harmonic functions; non-local means; power iteration; semi-supervised machine learning; spectral clustering;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Applications (ICMLA), 2010 Ninth International Conference on
  • Conference_Location
    Washington, DC
  • Print_ISBN
    978-1-4244-9211-4
  • Type

    conf

  • DOI
    10.1109/ICMLA.2010.131
  • Filename
    5708954