The RGYB color geometry

Abstract

Background:

The gamut of a color CRT is defined by its three primary colors, each produced by a phosphor/electron gun combination. Light from the primaries combines additively, so the color gamut is a subset of a three dimensional vector space [1]. With the primaries as basis vectors normalized to 1.0, the color gamut is a unit cube, known as the RGB color geometry, since the three primaries are usually red, green, and blue. User interaction via RGB is generally thought to be counterintuitive, and transformations of RGB, such as Smith's HSV geometry [10] which is derived from centuries old artists' models [2], are more popular. More recent color theories, based on psychophysical and physiological models of early visual processing, suggest that more intuitive geometries may be possible.

The RGYB geometry is based on two recent discoveries about the human visual system. First, the three color signals from the cone receptors are organized into three opponent channels [1, 7]. A single achromatic channel indicates lightness or brightness. Two chromatic channels, red/green and yellow/blue, signal the chromatic quantities. Second, signals on the achromatic channel are easily distinguishable from signals on the chromatic ones [6]. Consequently, it is usual to represent colors as a set of surfaces of colors that vary in chromaticity, each at a different level of brightness. Examples are as diverse as CIE chromaticity coordinates, the CIELUV uniform color space, the Munsell color system, and computer graphics color spaces such as HSV and HLS [10, 12].

References

1. 1 BOYNTON, R.M. Human Cvlour Vision. Holt, Rinehart, and Winston, New York, 1979.
2. 2 CHEVREUL, M.E. Principle,~ of Harmony and Contrast in Colours. Bell and Daldy, London, 1870.
3. 3 COWAN, W.B. An inexpensive scheme for the calibration of a color monitor in terms of CIE standard coordinates. (ACM SIGGRAPH Proceedings) Comput. Gr. 17, 3 (1983), 315-321.
4. 4 COWAN, W. S., AND WARE, W. On the brightness of colours that differ in hue or saturation. In Proceedings of the Society for Information Display 28, 4, (1988), 312-314.
5. 5 CROW, F.C. A comparison of antialiasing techniques. IEEE Comput. Gr. Appl. I (Jan. 1981), 40-49.
6. 6 FAVREAU, O. E., AND CAVANAGH, P. Color and luminance: Independent frequency shifts. Science 212 (1981), 831-832.
7. 7 HURVICH, L.M. Color Vision. Sinauer Associates, Sunderland Mass., 1981.
8. 8 NAIMAN, A. Colour spaces and colour contrast. In Graphics Interface '85, Proceedings (1985), 313-320.
9. 9 SCHWARZ, M. W., COWAN, W. B., AND BEATTY, J.C. An experimental comparison of RGB, YIQ, LAB, HSV, and opponent colour models. ACM Trans. Gr. 6, 2 (1987), 123-158.
10. 10 SMITH, A.R. Colour gamut rzansform pairs. Comput. Gr. I3 (1979), 12-19.
11. 11 WARE, C., AND BAXTER, C. Bat brushes: On the uses of six position and orientation parameters in a paint program. In Proceedings of CHI, 1989 (Austin, Tex., May 1989). ACM, New York, 1989, 159-162.
12. 12 WYSZECKI, G. W., AND STILES, W.S. Color Science: Concepts and Methods, Quantitative Data and Formulae. Wiley, New York, 1982.

Index Terms

• Computing methodologies

  • Computer graphics

    • Graphics systems and interfaces

    • Image manipulation

      • Texturing

    • Rendering

      • Rasterization

• Hardware

  • Communication hardware, interfaces and storage

    • Displays and imagers