Chapter

Transactions on Computational Science XIX

Volume 7870 of the series Lecture Notes in Computer Science pp 117-130

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

  • Mikhail MatrosovAffiliated withDepartment of Computational Mathematics and Cybernetics, Lomonosov Moscow State University
  • , Alexey IgnatenkoAffiliated withDepartment of Computational Mathematics and Cybernetics, Lomonosov Moscow State University
  • , Sergey SivovolenkoAffiliated withOctoNus Software Ltd.

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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