• DocumentCode
    2052922
  • Title

    Camera Response Function Recovery from Auto-Exposure Cameras

  • Author

    Aimone, Chris ; Mann, Steve

  • Author_Institution
    Toronto Univ., Toronto
  • Volume
    4
  • fYear
    2007
  • fDate
    Sept. 16 2007-Oct. 19 2007
  • Abstract
    A robust method of camera response function estimation applicable to auto-exposure cameras is presented. The method uses the superposition property of light to solve for the response function directly using superposition constraints imposed by using different combinations of two (or more) lights that illuminate the same subject matter in varying proportions. An iterative optimization is utilised to simultaneously recover the exposure ratios of the images and the camera response function. Previously published multiple exposure methods that simultaneously estimate exposure ratio and response function suffer from a fundamental ambiguity. The use of the proposed superposition constraints solves this problem. We introduce a simple method for combining both superposition and homogeneity (from multiple exposure techniques) to accurately recover the response function from auto-exposure cameras.
  • Keywords
    cameras; image registration; iterative methods; optimisation; auto-exposure camera; image registration; iterative optimization; response function recovery; superposition property; Automatic control; Cameras; Educational institutions; Layout; Lighting control; Linearity; Polynomials; Quantum computing; Robustness; Sensor arrays; Calibration; Cameras; Image color analysis; Image registration; Image sensors; Lighting;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing, 2007. ICIP 2007. IEEE International Conference on
  • Conference_Location
    San Antonio, TX
  • ISSN
    1522-4880
  • Print_ISBN
    978-1-4244-1437-6
  • Electronic_ISBN
    1522-4880
  • Type

    conf

  • DOI
    10.1109/ICIP.2007.4379997
  • Filename
    4379997