Using RGB displays to portray color realistic imagery to animal eyes

Research output: Contribution to journalArticle


RGB displays effectively simulate millions of colors in the eyes of humans by modulating the relative amount of light emitted by 3 differently colored juxtaposed lights (red, green, and blue). The relationship between the ratio of red, green, and blue light and the perceptual experience of that light has been well defined by psychophysical experiments in humans, but is unknown in animals. The perceptual experience of an animal looking at an RGB display of imagery designed for humans is likely to poorly represent an animal’s experience of the same stimulus in the real world. This is due, in part, to the fact that many animals have different numbers of photoreceptor classes than humans do and that their photoreceptor classes have peak sensitivities centered over different parts of the ultraviolet and visible spectrum. However, it is sometimes possible to generate videos that accurately mimic natural stimuli in the eyes of another animal, even if that animal’s sensitivity extends into the ultraviolet portion of the spectrum. How independently each RGB phosphor stimulates each of an animal’s photoreceptor classes determines the range of colors that can be simulated for that animal. What is required to determine optimal color rendering for another animal is a device capable of measuring absolute or relative quanta of light across the portion of the spectrum visible to the animal (i.e., a spectrometer), and data on the spectral sensitivities of the animal’s photoreceptor classes. In this article, we outline how to use such equipment and information to generate video stimuli that mimic, as closely as possible, an animal’s color perceptual experience of real-world objects.


  • Cynthia Tedore
  • Sönke Johnsen
External organisations
  • Duke University
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Zoology


  • Colour vision, computer animation, perception, video playback, virtual reality
Original languageEnglish
Pages (from-to)27-34
JournalCurrent Zoology
Issue number1
Early online date2017
Publication statusPublished - 2017 Feb
Publication categoryResearch

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