• DocumentCode
    605628
  • Title

    Combining the power of Internal and External denoising

  • Author

    Mosseri, I. ; Zontak, M. ; Irani, M.

  • Author_Institution
    Dept. of Comput. Sci. & Appl. Math., Weizmann Inst. of Sci., Rehovot, Israel
  • fYear
    2013
  • fDate
    19-21 April 2013
  • Firstpage
    1
  • Lastpage
    9
  • Abstract
    Image denoising methods can broadly be classified into two types: “Internal Denoising” (denoising an image patch using other noisy patches within the noisy image), and “External Denoising” (denoising a patch using external clean natural image patches). Any such method, whether Internal or External, is typically applied to all image patches. In this paper we show that different image patches inherently have different preferences for Internal or External de-noising. Moreover, and surprisingly, the higher the noise in the image, the stronger the preference for Internal De-noising. We identify and explain the source of this behavior, and show that Internal/External preference of a patch is directly related to its individual Signal-to-Noise-Ratio (“PatchSNR”). Patches with high PatchSNR (e.g., patches on strong edges) benefit much from External Denoising, whereas patches with low PatchSNR (e.g., patches in noisy uniform regions) benefit much more from Internal Denoising. Combining the power of Internal or External denoising selectively for each patch based on its estimated PatchSNR leads to improvement in denoising performance.
  • Keywords
    image denoising; natural scenes; PatchSNR; denoising performance; external clean natural image patches; external denoising; image denoising methods; internal denoising; noisy image; noisy patches; noisy uniform regions; signal-to-noise-ratio; Databases; Image edge detection; Noise level; Noise measurement; Noise reduction; Signal to noise ratio;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Photography (ICCP), 2013 IEEE International Conference on
  • Conference_Location
    Cambridge, MA
  • Print_ISBN
    978-1-4673-6463-8
  • Type

    conf

  • DOI
    10.1109/ICCPhot.2013.6528298
  • Filename
    6528298