May 2008
Volume 49, Issue 13
Free
ARVO Annual Meeting Abstract  |   May 2008
Development and Application of a Model Based Transformation for Technical and Physiological Colour Spaces
Author Affiliations & Notes
  • S. Klee
    Institute of Biomedical Engineering and Informatics, Technical University of Ilmenau, Ilmenau, Germany
  • P. Bessler
    Institute of Biomedical Engineering and Informatics, Technical University of Ilmenau, Ilmenau, Germany
  • J. Haueisen
    Institute of Biomedical Engineering and Informatics, Technical University of Ilmenau, Ilmenau, Germany
  • Footnotes
    Commercial Relationships  S. Klee, None; P. Bessler, None; J. Haueisen, None.
  • Footnotes
    Support  BMBF: FKZ 13N8521, FKZ 03IP605
Investigative Ophthalmology & Visual Science May 2008, Vol.49, 3834. doi:
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      S. Klee, P. Bessler, J. Haueisen; Development and Application of a Model Based Transformation for Technical and Physiological Colour Spaces. Invest. Ophthalmol. Vis. Sci. 2008;49(13):3834.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose: : The cone types of the eye differ in calcium metabolism, membrane permeability, amount and distribution. That implies different vulnerabilities to specific eye diseases e.g. retinitis pigmentosa or glaucoma. To achieve a diagnostic benefit based on these properties the excitation of several cone types is needed. Therefore a free adjustable RGB-colour stimulator is required. Our aim was to develop a model of the biological effect as a basis for the right choice of a suitable stimulator.

Methods: : The spectral distribution function of the irradiance provided the basis for the model. The measured spectra of each colour and each stimulator were transformed in CIE 10° colour system using the CIE colour matching functions. In result every colour was described by a set of three virtual colour values (XYZ). In this system an adjustment to standard illuminants and other calibrations can be done very easily. For calculation of the biological effect as the amount of radiation per unit area of the retina (LMS values), we used another transformation based on spectral sensitivity functions from Hunt. Because the controlling of the stimulators was performed with a PC graphic card, we finally transformed the PC colour space (RGB) into the XYZ system.

Results: : Through the combination of all transformation steps we were able to compute the biological effect produced by various stimulators and their colours. We applied the model on different stimulator technologies and types e.g. LCD, LCoS, DMD, plasma and a novel LCD combined with LED illumination. Using the example of an S-cone stimulus (R,G,B = 0,0,255) we computed differences in the values for the biological activation level of more than 25%. By consideration of all calculated LMS values, we could find an ideal colour stimulator.

Conclusions: : The presented model allows to calculate the biological effect (LMS values) caused by any colour stimulus from the RGB space. This provides a basis for choosing a suitable colour stimulator needed for an efficient selective cone excitation. The example of an S-cone stimulus showed great differences in the biological activation level witch are closely linked to the stimulator technology. The novel LED-LCD technology looks very promising with excellent LMS values.

Keywords: color vision • brightness and lightness • electrophysiology: non-clinical 
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