• DocumentCode
    1338891
  • Title

    Is Denoising Dead?

  • Author

    Chatterjee, Priyam ; Milanfar, Peyman

  • Author_Institution
    Dept. of Electr. Eng., Univ. of California, Santa Cruz, Santa Cruz, CA, USA
  • Volume
    19
  • Issue
    4
  • fYear
    2010
  • fDate
    4/1/2010 12:00:00 AM
  • Firstpage
    895
  • Lastpage
    911
  • Abstract
    Image denoising has been a well studied problem in the field of image processing. Yet researchers continue to focus attention on it to better the current state-of-the-art. Recently proposed methods take different approaches to the problem and yet their denoising performances are comparable. A pertinent question then to ask is whether there is a theoretical limit to denoising performance and, more importantly, are we there yet? As camera manufacturers continue to pack increasing numbers of pixels per unit area, an increase in noise sensitivity manifests itself in the form of a noisier image. We study the performance bounds for the image denoising problem. Our work in this paper estimates a lower bound on the mean squared error of the denoised result and compares the performance of current state-of-the-art denoising methods with this bound. We show that despite the phenomenal recent progress in the quality of denoising algorithms, some room for improvement still remains for a wide class of general images, and at certain signal-to-noise levels. Therefore, image denoising is not dead - yet.
  • Keywords
    image denoising; camera manufacturers; denoising performance; image denoising; image processing; lower bound; mean squared error; noise sensitivity; Bayesian Cramér–Rao lower bound (CRLB); bias; bootstrapping; image denoising; mean squared error;
  • fLanguage
    English
  • Journal_Title
    Image Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1057-7149
  • Type

    jour

  • DOI
    10.1109/TIP.2009.2037087
  • Filename
    5339210