Locally Adapted Detection and Correction of Unnatural Purple Colors in Images of Refractive Objects Taken by Digital Still Camera

  • Mikhail Matrosov
  • Alexey Ignatenko
  • Sergey Sivovolenko
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7870)

Abstract

We discovered significant error in color in images produced by a digital still camera used to capture scenes with a special setup. Setup includes several LEDs as point light sources and a light-refractive object. Due to light dispersion in the object, vivid monochromatic colored flares appear. However, images captured with a digital still camera occasionally exhibit bright purple (almost pink) colors, which do not correspond to any monochromatic color.

In this paper, we analyze the origins of this effect by examining different properties of the setup and analyzing RAW images. We propose a simple and efficient algorithm for correction of unnatural purple colors by using only a final JPEG image produced by camera. We develop a continuous transform which maps all unnatural colors to the natural ones in a perceptually uniform color space. We also propose a simple segmentation technique to identify image areas to be corrected.

Keywords

color management color calibration segmentation color correction monochromatic colors RAW-processing perceptually uniform color spaces light dispersion digital still camera 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Bruce lindbloom’s web site, http://brucelindbloom.com (accessed: May 27, 2012)
  2. 2.
    CGAL - computational geometry algorithms library, http://www.cgal.org (accessed: May 27, 2012)
  3. 3.
    Decoding raw digital photos in linux, http://cybercom.net/~dcoffin/dcraw (accessed: November 27, 2012)
  4. 4.
    Intel integrated performance primitives, http://software.intel.com/en-us/intel-ipp (accessed: November 28, 2012)
  5. 5.
    Adams, J., Parulski, K., Spaulding, K.: Color processing in digital cameras. IEEE Micro 18(6), 20–30 (1998)CrossRefGoogle Scholar
  6. 6.
    ANSI, I.: 7/2-1993 (ISO 12641). Graphic Technology-Color Reflection Target for Input Scanner CalibrationGoogle Scholar
  7. 7.
    Hong, G., Luo, M., Rhodes, P.: A study of digital camera colorimetric characterisation based on polynomial modelling (2001)Google Scholar
  8. 8.
    Matrosov, M., Ignatenko, A., Sivovolenko, S.: Detection and correction of unnatural purple colors in images of refractive objects taken by digital still camera. In: Graphicon (2012)Google Scholar
  9. 9.
    McCamy, C., Marcus, H., Davidson, J.: A color-rendition chart. J. App. Photog. Eng. 2(3), 95–99 (1976)Google Scholar
  10. 10.
    Newhall, S., Nickerson, D., Judd, D.: Final report of the OSA subcommittee on the spacing of the munsell colors. JOSA 33(7), 385–411 (1943)CrossRefGoogle Scholar
  11. 11.
    Park, J., Park, K.: Professional colour communicator-the definitive colour selector. Journal of the Society of Dyers and Colourists 111(3), 56–57 (1995)CrossRefGoogle Scholar
  12. 12.
    Smith, T., Guild, J.: The CIE colorimetric standards and their use. Transactions of the Optical Society 33, 73 (1931)CrossRefGoogle Scholar
  13. 13.
    Spaulding, K., Vogel, R., Szczepanski, J.: Method and apparatus for color-correcting multi-channel signals of a digital camera, US Patent 5,805,213 (September 8, 1998)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Mikhail Matrosov
    • 1
  • Alexey Ignatenko
    • 1
  • Sergey Sivovolenko
    • 2
  1. 1.Department of Computational Mathematics and CyberneticsLomonosov Moscow State UniversityMoscowRussia
  2. 2.OctoNus Software Ltd.Russia

Personalised recommendations