Abstract

The method of evaluating color rendering using a visual, graphical metric is presented. A two-dimensional Color Rendering Map (CRM) of a light source’s color-rendering capabilities is explained and demonstrated. Extension of this technique to three-dimensional CRMs of objects under illumination is explained, including the method of introducing numerical indices in order to evaluate standards for specific applications in lighting. Three diverse applications, having a range from subtle to significant color variation, are shown with their respective CRMs. These three applications are also used to demonstrate how three differing light sources produce different maps. The results show a flexible, simple method to obtain a clear, visual determination of color rendering performance from differing sources used in differing illumination applications. The use of numeric indices in these applications shows how specific standards can be imposed in assessing the applicability of a light source.

© 2012 OSA

Full Article  |  PDF Article

References

  • View by:
  • |
  • |
  • |

  1. CIE, “Method of specifying and measuring color rendering properties of light sources,” CIE Publ.No.13.3, (Central Bureau of the CIE, Vienna, Austria, 1995).
  2. CIE, “Color rendering of white LED light sources,” CIE Publ.No.177, (Central Bureau of the CIE, Vienna, Austria, 1995).
  3. Y. Ohno, “Color rendering and luminous efficacy of white LED spectra,” Proc. SPIE 5530, 88–98 (2004).
    [CrossRef]
  4. M. S. Rea and J. P. Freyssinier-Nova, “Color rendering: a tale of two metrics,” Color Res. Appl. 33, 192–202 (2007).
    [CrossRef]
  5. W. Davis and Y. Ohno, “Color quality scale,” Opt. Eng. 49, 033602–033616 (2010).
    [CrossRef]
  6. K. Smet, W.R. Ryckaert, M. R. Pointer, G. Deconinck, and P. Hanselaer, “Memory colours and colour quality evaluation of conventional and solid-state lamps,” Opt. Express 18, 26229–26244 (2010).
    [CrossRef] [PubMed]
  7. M. R. Luo, “The quality of light sources,” Color. Technol. 12775–87 (2011).
    [CrossRef]
  8. P. van der Burgt and J. van Kemenade, “About color rendition of light sources: the balance between simplicity and accuracy,” Color Res. Appl. 35, 85–93 (2008).
  9. D. Malacara, Color Vision and Colorimetry Theory and Applications (SPIE, 2002), Chap.4.
  10. N. Ohta and A. R. Robertson, Colorimetry: Fundamentals and Applications (Wiley, 2005), Chap. 6.
    [CrossRef]
  11. M. D. Fairchild, Color Appearance Models, 2nd ed. (Wiley, 2005), Chap. 10–16.
  12. X-Rite®, The Munsell Book of Color, Glossy Collection.
  13. K. Smet and L. A. Whitehead, “Consideration of Meta-Standards for Color rendering Metrics,” in Proceedings of the 19th Color Imaging Conference, I.S& T. Publ., (San José, CA, 2011).
  14. Josep Carreras, Catalonia Institute for Energy Research, Jardins de les Dones de Negre 1. PL2, 08930 Sant Adrià de Besòs, Barcelona, Spain and Charles E. Hunt are preparing a manuscript to be called Efficacy and color rendering limits in artificial light sources emulating natural illumnation.
  15. J. Pérez-Carpinell, M. D. de Fez, R. Baldov, and J. C. Soriano, “Familiar objects and memory color,” Color Res. Appl. 23, 416–427 (1998).
    [CrossRef]
  16. János Schanda, “Getting Color right: Improved visual matching with LED light Sources,” presented at the Professional Lighting Design Convention 2011, 19–22 Oct. 2011.

2011

M. R. Luo, “The quality of light sources,” Color. Technol. 12775–87 (2011).
[CrossRef]

2010

2008

P. van der Burgt and J. van Kemenade, “About color rendition of light sources: the balance between simplicity and accuracy,” Color Res. Appl. 35, 85–93 (2008).

2007

M. S. Rea and J. P. Freyssinier-Nova, “Color rendering: a tale of two metrics,” Color Res. Appl. 33, 192–202 (2007).
[CrossRef]

2004

Y. Ohno, “Color rendering and luminous efficacy of white LED spectra,” Proc. SPIE 5530, 88–98 (2004).
[CrossRef]

1998

J. Pérez-Carpinell, M. D. de Fez, R. Baldov, and J. C. Soriano, “Familiar objects and memory color,” Color Res. Appl. 23, 416–427 (1998).
[CrossRef]

Baldov, R.

J. Pérez-Carpinell, M. D. de Fez, R. Baldov, and J. C. Soriano, “Familiar objects and memory color,” Color Res. Appl. 23, 416–427 (1998).
[CrossRef]

Davis, W.

W. Davis and Y. Ohno, “Color quality scale,” Opt. Eng. 49, 033602–033616 (2010).
[CrossRef]

de Fez, M. D.

J. Pérez-Carpinell, M. D. de Fez, R. Baldov, and J. C. Soriano, “Familiar objects and memory color,” Color Res. Appl. 23, 416–427 (1998).
[CrossRef]

Deconinck, G.

Fairchild, M. D.

M. D. Fairchild, Color Appearance Models, 2nd ed. (Wiley, 2005), Chap. 10–16.

Freyssinier-Nova, J. P.

M. S. Rea and J. P. Freyssinier-Nova, “Color rendering: a tale of two metrics,” Color Res. Appl. 33, 192–202 (2007).
[CrossRef]

Hanselaer, P.

Luo, M. R.

M. R. Luo, “The quality of light sources,” Color. Technol. 12775–87 (2011).
[CrossRef]

Malacara, D.

D. Malacara, Color Vision and Colorimetry Theory and Applications (SPIE, 2002), Chap.4.

Ohno, Y.

W. Davis and Y. Ohno, “Color quality scale,” Opt. Eng. 49, 033602–033616 (2010).
[CrossRef]

Y. Ohno, “Color rendering and luminous efficacy of white LED spectra,” Proc. SPIE 5530, 88–98 (2004).
[CrossRef]

Ohta, N.

N. Ohta and A. R. Robertson, Colorimetry: Fundamentals and Applications (Wiley, 2005), Chap. 6.
[CrossRef]

Pérez-Carpinell, J.

J. Pérez-Carpinell, M. D. de Fez, R. Baldov, and J. C. Soriano, “Familiar objects and memory color,” Color Res. Appl. 23, 416–427 (1998).
[CrossRef]

Pointer, M. R.

Rea, M. S.

M. S. Rea and J. P. Freyssinier-Nova, “Color rendering: a tale of two metrics,” Color Res. Appl. 33, 192–202 (2007).
[CrossRef]

Robertson, A. R.

N. Ohta and A. R. Robertson, Colorimetry: Fundamentals and Applications (Wiley, 2005), Chap. 6.
[CrossRef]

Ryckaert, W.R.

Schanda, János

János Schanda, “Getting Color right: Improved visual matching with LED light Sources,” presented at the Professional Lighting Design Convention 2011, 19–22 Oct. 2011.

Smet, K.

K. Smet, W.R. Ryckaert, M. R. Pointer, G. Deconinck, and P. Hanselaer, “Memory colours and colour quality evaluation of conventional and solid-state lamps,” Opt. Express 18, 26229–26244 (2010).
[CrossRef] [PubMed]

K. Smet and L. A. Whitehead, “Consideration of Meta-Standards for Color rendering Metrics,” in Proceedings of the 19th Color Imaging Conference, I.S& T. Publ., (San José, CA, 2011).

Soriano, J. C.

J. Pérez-Carpinell, M. D. de Fez, R. Baldov, and J. C. Soriano, “Familiar objects and memory color,” Color Res. Appl. 23, 416–427 (1998).
[CrossRef]

van der Burgt, P.

P. van der Burgt and J. van Kemenade, “About color rendition of light sources: the balance between simplicity and accuracy,” Color Res. Appl. 35, 85–93 (2008).

van Kemenade, J.

P. van der Burgt and J. van Kemenade, “About color rendition of light sources: the balance between simplicity and accuracy,” Color Res. Appl. 35, 85–93 (2008).

Whitehead, L. A.

K. Smet and L. A. Whitehead, “Consideration of Meta-Standards for Color rendering Metrics,” in Proceedings of the 19th Color Imaging Conference, I.S& T. Publ., (San José, CA, 2011).

Color Res. Appl.

M. S. Rea and J. P. Freyssinier-Nova, “Color rendering: a tale of two metrics,” Color Res. Appl. 33, 192–202 (2007).
[CrossRef]

P. van der Burgt and J. van Kemenade, “About color rendition of light sources: the balance between simplicity and accuracy,” Color Res. Appl. 35, 85–93 (2008).

J. Pérez-Carpinell, M. D. de Fez, R. Baldov, and J. C. Soriano, “Familiar objects and memory color,” Color Res. Appl. 23, 416–427 (1998).
[CrossRef]

Color. Technol.

M. R. Luo, “The quality of light sources,” Color. Technol. 12775–87 (2011).
[CrossRef]

Opt. Eng.

W. Davis and Y. Ohno, “Color quality scale,” Opt. Eng. 49, 033602–033616 (2010).
[CrossRef]

Opt. Express

Proc. SPIE

Y. Ohno, “Color rendering and luminous efficacy of white LED spectra,” Proc. SPIE 5530, 88–98 (2004).
[CrossRef]

Other

János Schanda, “Getting Color right: Improved visual matching with LED light Sources,” presented at the Professional Lighting Design Convention 2011, 19–22 Oct. 2011.

CIE, “Method of specifying and measuring color rendering properties of light sources,” CIE Publ.No.13.3, (Central Bureau of the CIE, Vienna, Austria, 1995).

CIE, “Color rendering of white LED light sources,” CIE Publ.No.177, (Central Bureau of the CIE, Vienna, Austria, 1995).

D. Malacara, Color Vision and Colorimetry Theory and Applications (SPIE, 2002), Chap.4.

N. Ohta and A. R. Robertson, Colorimetry: Fundamentals and Applications (Wiley, 2005), Chap. 6.
[CrossRef]

M. D. Fairchild, Color Appearance Models, 2nd ed. (Wiley, 2005), Chap. 10–16.

X-Rite®, The Munsell Book of Color, Glossy Collection.

K. Smet and L. A. Whitehead, “Consideration of Meta-Standards for Color rendering Metrics,” in Proceedings of the 19th Color Imaging Conference, I.S& T. Publ., (San José, CA, 2011).

Josep Carreras, Catalonia Institute for Energy Research, Jardins de les Dones de Negre 1. PL2, 08930 Sant Adrià de Besòs, Barcelona, Spain and Charles E. Hunt are preparing a manuscript to be called Efficacy and color rendering limits in artificial light sources emulating natural illumnation.

Supplementary Material (2)

» Media 1: MOV (3929 KB)     
» Media 2: MOV (12512 KB)     

Cited By

OSA participates in CrossRef's Cited-By Linking service. Citing articles from OSA journals and other participating publishers are listed here.

Alert me when this article is cited.


Figures (13)

Fig. 1
Fig. 1

Flow chart depicting how to create 2D-CRM. (A) Using the 1269 Munsell Colors, the Ri values are evaluated by comparison with a Reference Set. (B) The Ri values are plotted over the CIE xy plane.

Fig. 2
Fig. 2

Three differing CCT=3000K spectra, (a) white R-G-B LED, (b) trichromatic fluorescent, and (c) filtered Plankian, all having the same CRI (Ra) values and approximately identical LER values. The Color Rendering Maps (CRMs) are depicted next to their respective spectra.

Fig. 3
Fig. 3

Flow chart for the evaluation of the 3-D CRM. (A) A calibrated digital photograph measures all luminance and color coordinates of the application object, giving the Observed Gamut. (B) The Test Set is obtained by finding the closest Euclidian distance between each pixel in the Measured Set to the Colors of the Reference Set. (C) As before, the Ri values for the complete Test Set (as well as the Ras and Ram indices) are computed. (D) Finally, the 3-D CRM is plotted using the Ri values of the Test Sample [Animation available online. Low Bit-Rate (low weight): Media 1. High Bit-Rate (high weight): Media 2].

Fig. 4
Fig. 4

Experimental viewing booth, for generating Test Sets, with a simulator of the standard illuminant CIE-D65, calibrated CCD camera and a computer for editing and selecting the areas of interest. Also seen in the booth are color-checker patches. All measurements are performed with room lights dark.

Fig. 5
Fig. 5

3-D color space depiction of the 1269 color Reference Set, analogous to 2-D representation of Figure 2d, as used in the application examples. These are seen in two views: Azimuth = 0, Elevation = 90 (left column) and Azimuth = −30, Elevation = 10 (right column). The equivalent Reference Set is demonstrated in three versions of color space: (a) CIE-1931 xyY, (b) CIE-1976 CIE L*a*b*, and (c) CIECAM02.

Fig. 6
Fig. 6

Color photograph (left column), taken under a D65 CIE standard illuminant simulator, of meat samples (a), assorted fruit (b) and artwork (c), along with corresponding luminance photographs of each scene (right column). The rectangles delineate the areas of interest to be analyzed. The color-checker cards are used to verify the calibration of the camera.

Fig. 7
Fig. 7

Observed Gamut data measured under a D65 simulator from the meat application shown in Fig. 6(a), in three versions of color space: CIE-1931 xyY (a), CIE-1976 L*a*b* (b) and CIECAM02 (c). These are seen in two views: Azimuth = 0, Elevation = 90 (left column) and approximately Azimuth = −30, Elevation = 10 (right column)

Fig. 8
Fig. 8

xyY representation of the Test Set found for the meat (a), fruit (b) and artwork (c) applications of Fig. 6.

Fig. 9
Fig. 9

Left column: Three differing light sources, CCT=3000K, (a) R-G-B LED, (b) incandescent Neodimium lamp, and (c) Phosphor-converted LED. Right column: Corresponding color rendering indices CIE-Ra, Ras and Ram, for the three applications (Test Set) Meat, Fruit and Artwork.

Fig. 10
Fig. 10

CRM representation in xyY color space of the Test Set found for the meat application of Fig. 6, and illuminated with the light sources of Fig. 9. R-G-B LED (upper row), Neodimium (middle row) and phosphor-converted LED (lower row). These are seen in two views: Azimuth = 0, Elevation = 90 (left column) and Azimuth = 10, Elevation = 24 (right column).

Fig. 11
Fig. 11

CRM representation in xyY color space of the Test Set found for the fruit application of Fig. 6, and illuminated with the light sources of the Fig. 9. R-G-B LED (upper row), Neodimium (middle row) and phosphor-converted LED (lower row). The same views as in Fig. 10 are shown.

Fig. 12
Fig. 12

CRM representation in xyY color space of the Test Set found for the artwork application of Fig. 6, and illuminated with light sources of the Fig. 9. R-G-B LED (upper row), Neodimium (middle row) and phosphor-converted LED (lower row). The same views as in Fig. 10 are shown.

Fig. 13
Fig. 13

CRM representation in xyY color space of the Test Set for the three applications shown in Fig. 6, illuminated with light sources of Fig. 9. R-G-B LED (upper row), Neodimium (middle row) and phosphor-converted LED (lower row). Only one view is shown.

Tables (1)

Tables Icon

Table 1 Comparative Results of Calculated Observed Gamut and Test Set using CIELAB and CIECAM02 Color Systems for Three Different Applications.

Equations (3)

Equations on this page are rendered with MathJax. Learn more.

R a s = 1 s i = 1 s R i
R a m = 1 u i = 1 s m i R i
u = i = 1 s m i

Metrics