• DocumentCode
    3016981
  • Title

    Radiometric Calibration from Noise Distributions

  • Author

    Matsushita, Yasuyuki ; Lin, Stephen

  • Author_Institution
    Microsoft Res. Asia, Beijing
  • fYear
    2007
  • fDate
    17-22 June 2007
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    A method is proposed for estimating radiometric response functions from noise observations. From the statistical properties of noise sources, the noise distribution for each scene radiance value is shown to be symmetric for a radiometrically calibrated camera. However, due to the non-linearity of camera response functions, the observed noise distributions become skewed in an uncalibrated camera. In this paper, we capitalize on these asymmetric profiles of measured noise distributions to estimate radiometric response functions. Unlike prior approaches, the proposed method is not sensitive to noise level, and is therefore particularly useful when the noise level is high. Also, the proposed method does not require registered input images taken with different exposures; only statistical noise distributions at multiple intensity levels are used. Real-world experiments demonstrate the effectiveness of the proposed approach in comparison to standard calibration techniques.
  • Keywords
    calibration; computer vision; image sensors; statistical analysis; camera response functions; noise distributions; noise observations; radiometric calibration; radiometric response functions; standard calibration techniques; statistical properties; Calibration; Cameras; Computer vision; Image sensors; Layout; Noise level; Noise measurement; Noise shaping; Radiometry; Working environment noise;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition, 2007. CVPR '07. IEEE Conference on
  • Conference_Location
    Minneapolis, MN
  • ISSN
    1063-6919
  • Print_ISBN
    1-4244-1179-3
  • Electronic_ISBN
    1063-6919
  • Type

    conf

  • DOI
    10.1109/CVPR.2007.383213
  • Filename
    4270238