Abstract

We have developed a two-measure system for evaluating light sources’ color rendition that builds upon conceptual progress of numerous researchers over the last two decades. The system quantifies the color fidelity and color gamut (change in object chroma) of a light source in comparison to a reference illuminant. The calculations are based on a newly developed set of reflectance data from real samples uniformly distributed in color space (thereby fairly representing all colors) and in wavelength space (thereby precluding artificial optimization of the color rendition scores by spectral engineering). The color fidelity score Rf is an improved version of the CIE color rendering index. The color gamut score Rg is an improved version of the Gamut Area Index. In combination, they provide two complementary assessments to guide the optimization of future light sources. This method summarizes the findings of the Color Metric Task Group of the Illuminating Engineering Society of North America (IES). It is adopted in the upcoming IES TM-30-2015, and is proposed for consideration with the International Commission on Illumination (CIE).

© 2015 Optical Society of America

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    [Crossref] [PubMed]
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    [Crossref]
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  14. N. Sandor and J. Schanda, “Visual colour rendering based on colour difference evaluations,” Lighting Res. Tech. 38(3), 225–239 (2006).
    [Crossref]
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    [Crossref]
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    [Crossref]
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    [Crossref]
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    [Crossref]
  26. P. van der Burgt and J. van Kemenade, “About color rendition of light sources: the balance between simplicity and accuracy,” Color Res. Appl. 35(2), 85–93 (2010).
  27. L. Whitehead and M. Mossman, “A Monte Carlo method for assessing color rendering quality with possible application to color rendering standards,” Color Res. Appl. 37(1), 13–22 (2012).
    [Crossref]
  28. A. David, “Color fidelity of light sources evaluated over large sets of reflectance samples,” Leukos 10(2), 59–75 (2014).
    [Crossref]
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  31. Lightness shifts are also possible but are not shown for simplicity. Further, Fig. 1 only shows average color shifts; however in practice metameric colors generally undergo different shifts.
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    [Crossref]
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    [Crossref]
  35. W. A. Thornton, “A validation of the color-preference index,” J. Illum. Eng. Soc. 4(1), 48–52 (1974).
    [Crossref]
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    [Crossref] [PubMed]
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    [Crossref]
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    [Crossref]
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    [Crossref]
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  52. K. Smet, G. Deconinck, and P. Hanselaer, “Chromaticity of unique white in illumination mode,” Opt. Express 23(10), 12488–12495 (2015).
    [Crossref]
  53. K. W. Houser, M. Wei, A. David, and M. Krames, “Whiteness perception under LED illumination,” Leukos 10(3), 165–180 (2014).
    [Crossref]
  54. C. Li, M. R. Luo, M. Pointer, and P. Green, “Comparison of real colour gamuts using a new reflectance database,” Color Res. Appl. 39(5), 442–451 (2014).
    [Crossref]
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2015 (1)

2014 (6)

K. W. Houser, M. Wei, A. David, and M. Krames, “Whiteness perception under LED illumination,” Leukos 10(3), 165–180 (2014).
[Crossref]

C. Li, M. R. Luo, M. Pointer, and P. Green, “Comparison of real colour gamuts using a new reflectance database,” Color Res. Appl. 39(5), 442–451 (2014).
[Crossref]

Y. Ohno, “Practical use and calculation of CCT and Duv,” Leukos 10(1), 47–55 (2014).
[Crossref]

A. David, “Color fidelity of light sources evaluated over large sets of reflectance samples,” Leukos 10(2), 59–75 (2014).
[Crossref]

E. E. Dikel, G. J. Burns, J. A. Veitch, S. Mancini, and G. R. Newsham, “Preferred chromaticity of color-tunable LED lighting,” Leukos 10(2), 101–115 (2014).
[Crossref]

M. Wei, K. W. Houser, G. R. Allen, and W. W. Beers, “Color preference under LEDs with diminished yellow emission,” Leukos 10(3), 119–131 (2014).
[Crossref]

2013 (4)

K. Smet, J. Schanda, L. Whitehead, and M. R. Luo, “CRI2012: A proposal for updating the CIE colour rendering index,” Lighting Res. Tech. 45(6), 689–709 (2013).
[Crossref]

K. W. Houser, M. Wei, A. David, M. R. Krames, and X. S. Shen, “Review of measures for light-source color rendition and considerations for a two-measure system for characterizing color rendition,” Opt. Express 21(8), 10393–10411 (2013).
[Crossref] [PubMed]

K. W. Houser, “If not CRI, then what?” Leukos 9(3), 151–153 (2013).
[Crossref]

M. Rea and J. P. Freyssinier, “White lighting,” Color Res. Appl. 38(2), 82–92 (2013).
[Crossref]

2012 (2)

L. Whitehead and M. Mossman, “A Monte Carlo method for assessing color rendering quality with possible application to color rendering standards,” Color Res. Appl. 37(1), 13–22 (2012).
[Crossref]

C. Li, M. Ronnier Luo, C. Li, and G. Cui, “The CRI-CAM02UCS colour rendering index,” Color Res. Appl. 37(3), 160–167 (2012).
[Crossref]

2011 (1)

2010 (4)

P. van der Burgt and J. van Kemenade, “About color rendition of light sources: the balance between simplicity and accuracy,” Color Res. Appl. 35(2), 85–93 (2010).

W. Davis and Y. Ohno, “Color quality scale,” Opt. Eng. 49(3), 033602 (2010).
[Crossref]

M. Rea and J. P. Freyssinier, “Color rendering beyond pride and prejudice,” Color Res. Appl. 35(6), 401–409 (2010).
[Crossref]

K. A. 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(25), 26229–26244 (2010).
[Crossref] [PubMed]

2009 (2)

W. Davis and Y. Ohno, “Approaches to color rendering measurement,” J. Mod. Opt. 56(13), 1412–1419 (2009).
[Crossref]

A. Zukauskas, R. Vaicekauskas, F. Ivanauskas, H. Vaitkevicius, P. Vitta, and M. S. Shur, “Statistical approach to color quality of solid-state lamps,” IEEE J. Sel. Top. Quantum Electron. 15(6), 1753–1762 (2009).
[Crossref]

2008 (1)

M. S. Rea and J. P. Freyssinier-Nova, “Color rendering: a tale of two metrics,” Color Res. Appl. 33(3), 192–202 (2008).
[Crossref]

2007 (1)

Commission Internationale de l’Eclairage, “Color rendering of white LED light sources,” Technical Report CIE 177, 2007 (2007).

2006 (2)

N. Sandor and J. Schanda, “Visual colour rendering based on colour difference evaluations,” Lighting Res. Tech. 38(3), 225–239 (2006).
[Crossref]

M. R. Luo, G. Cui, and C. Li, “Uniform colour spaces based on CIECAM02 colour appearance model,” Color Res. Appl. 31(4), 320–330 (2006).
[Crossref]

2005 (1)

Y. Ohno, “Spectral design considerations for white LED color rendering,” Opt. Eng. 44(11), 111302 (2005).
[Crossref]

2004 (1)

X. Guo and K. W. Houser, “A review of colour rendering indices and their application to commercial light sources,” Lighting Res. Tech. 36(3), 183–197 (2004).
[Crossref]

2003 (1)

J. A. Worthey, “Color rendering: asking the questions,” Color Res. Appl. 28(6), 403–412 (2003).
[Crossref]

1974 (1)

W. A. Thornton, “A validation of the color-preference index,” J. Illum. Eng. Soc. 4(1), 48–52 (1974).
[Crossref]

1973 (1)

C. W. Jerome, “The flattery index,” J. Illum. Eng. Soc. 2(4), 351–354 (1973).
[Crossref]

1972 (1)

C. W. Jerome, “Flattery vs color rendition,” J. Illum. Eng. Soc. 1(3), 208–211 (1972).
[Crossref]

1967 (1)

D. Judd, “A flattery index for artificial illuminants,” Illum. Eng. 62, 593–598 (1967).

Allen, G. R.

M. Wei, K. W. Houser, G. R. Allen, and W. W. Beers, “Color preference under LEDs with diminished yellow emission,” Leukos 10(3), 119–131 (2014).
[Crossref]

Beers, W. W.

M. Wei, K. W. Houser, G. R. Allen, and W. W. Beers, “Color preference under LEDs with diminished yellow emission,” Leukos 10(3), 119–131 (2014).
[Crossref]

Burns, G. J.

E. E. Dikel, G. J. Burns, J. A. Veitch, S. Mancini, and G. R. Newsham, “Preferred chromaticity of color-tunable LED lighting,” Leukos 10(2), 101–115 (2014).
[Crossref]

Cui, G.

C. Li, M. Ronnier Luo, C. Li, and G. Cui, “The CRI-CAM02UCS colour rendering index,” Color Res. Appl. 37(3), 160–167 (2012).
[Crossref]

M. R. Luo, G. Cui, and C. Li, “Uniform colour spaces based on CIECAM02 colour appearance model,” Color Res. Appl. 31(4), 320–330 (2006).
[Crossref]

David, A.

A. David, “Color fidelity of light sources evaluated over large sets of reflectance samples,” Leukos 10(2), 59–75 (2014).
[Crossref]

K. W. Houser, M. Wei, A. David, and M. Krames, “Whiteness perception under LED illumination,” Leukos 10(3), 165–180 (2014).
[Crossref]

K. W. Houser, M. Wei, A. David, M. R. Krames, and X. S. Shen, “Review of measures for light-source color rendition and considerations for a two-measure system for characterizing color rendition,” Opt. Express 21(8), 10393–10411 (2013).
[Crossref] [PubMed]

A. David, to be published.

A. David, “Colour fidelity evaluated over large reflectance datasets,” Proceedings of the CIE meeting, Kuala Lumpur (2014).

A. David, K. A. G. Smet, and L. Whitehead, to be published.

Davis, W.

W. Davis and Y. Ohno, “Color quality scale,” Opt. Eng. 49(3), 033602 (2010).
[Crossref]

W. Davis and Y. Ohno, “Approaches to color rendering measurement,” J. Mod. Opt. 56(13), 1412–1419 (2009).
[Crossref]

Deconinck, G.

Dikel, E. E.

E. E. Dikel, G. J. Burns, J. A. Veitch, S. Mancini, and G. R. Newsham, “Preferred chromaticity of color-tunable LED lighting,” Leukos 10(2), 101–115 (2014).
[Crossref]

Fein, M.

Y. Ohno and M. Fein, “Vision experiment on acceptable and preferred white light chromaticity for lighting,” Proceedings of the CIE conference on lighting quality and energy efficiency, Kuala Lumpur (2014).

Freyssinier, J. P.

M. Rea and J. P. Freyssinier, “White lighting,” Color Res. Appl. 38(2), 82–92 (2013).
[Crossref]

M. Rea and J. P. Freyssinier, “Color rendering beyond pride and prejudice,” Color Res. Appl. 35(6), 401–409 (2010).
[Crossref]

Freyssinier-Nova, J. P.

M. S. Rea and J. P. Freyssinier-Nova, “Color rendering: a tale of two metrics,” Color Res. Appl. 33(3), 192–202 (2008).
[Crossref]

Green, P.

C. Li, M. R. Luo, M. Pointer, and P. Green, “Comparison of real colour gamuts using a new reflectance database,” Color Res. Appl. 39(5), 442–451 (2014).
[Crossref]

Guo, X.

X. Guo and K. W. Houser, “A review of colour rendering indices and their application to commercial light sources,” Lighting Res. Tech. 36(3), 183–197 (2004).
[Crossref]

Hanselaer, P.

Houser, K. W.

K. W. Houser, M. Wei, A. David, and M. Krames, “Whiteness perception under LED illumination,” Leukos 10(3), 165–180 (2014).
[Crossref]

M. Wei, K. W. Houser, G. R. Allen, and W. W. Beers, “Color preference under LEDs with diminished yellow emission,” Leukos 10(3), 119–131 (2014).
[Crossref]

K. W. Houser, “If not CRI, then what?” Leukos 9(3), 151–153 (2013).
[Crossref]

K. W. Houser, M. Wei, A. David, M. R. Krames, and X. S. Shen, “Review of measures for light-source color rendition and considerations for a two-measure system for characterizing color rendition,” Opt. Express 21(8), 10393–10411 (2013).
[Crossref] [PubMed]

X. Guo and K. W. Houser, “A review of colour rendering indices and their application to commercial light sources,” Lighting Res. Tech. 36(3), 183–197 (2004).
[Crossref]

Ivanauskas, F.

A. Zukauskas, R. Vaicekauskas, F. Ivanauskas, H. Vaitkevicius, P. Vitta, and M. S. Shur, “Statistical approach to color quality of solid-state lamps,” IEEE J. Sel. Top. Quantum Electron. 15(6), 1753–1762 (2009).
[Crossref]

Jerome, C. W.

C. W. Jerome, “The flattery index,” J. Illum. Eng. Soc. 2(4), 351–354 (1973).
[Crossref]

C. W. Jerome, “Flattery vs color rendition,” J. Illum. Eng. Soc. 1(3), 208–211 (1972).
[Crossref]

Judd, D.

D. Judd, “A flattery index for artificial illuminants,” Illum. Eng. 62, 593–598 (1967).

Krames, M.

K. W. Houser, M. Wei, A. David, and M. Krames, “Whiteness perception under LED illumination,” Leukos 10(3), 165–180 (2014).
[Crossref]

Krames, M. R.

Li, C.

C. Li, M. R. Luo, M. Pointer, and P. Green, “Comparison of real colour gamuts using a new reflectance database,” Color Res. Appl. 39(5), 442–451 (2014).
[Crossref]

C. Li, M. Ronnier Luo, C. Li, and G. Cui, “The CRI-CAM02UCS colour rendering index,” Color Res. Appl. 37(3), 160–167 (2012).
[Crossref]

C. Li, M. Ronnier Luo, C. Li, and G. Cui, “The CRI-CAM02UCS colour rendering index,” Color Res. Appl. 37(3), 160–167 (2012).
[Crossref]

M. R. Luo, G. Cui, and C. Li, “Uniform colour spaces based on CIECAM02 colour appearance model,” Color Res. Appl. 31(4), 320–330 (2006).
[Crossref]

Luo, M. R.

C. Li, M. R. Luo, M. Pointer, and P. Green, “Comparison of real colour gamuts using a new reflectance database,” Color Res. Appl. 39(5), 442–451 (2014).
[Crossref]

K. Smet, J. Schanda, L. Whitehead, and M. R. Luo, “CRI2012: A proposal for updating the CIE colour rendering index,” Lighting Res. Tech. 45(6), 689–709 (2013).
[Crossref]

M. R. Luo, G. Cui, and C. Li, “Uniform colour spaces based on CIECAM02 colour appearance model,” Color Res. Appl. 31(4), 320–330 (2006).
[Crossref]

Mancini, S.

E. E. Dikel, G. J. Burns, J. A. Veitch, S. Mancini, and G. R. Newsham, “Preferred chromaticity of color-tunable LED lighting,” Leukos 10(2), 101–115 (2014).
[Crossref]

Mossman, M.

L. Whitehead and M. Mossman, “A Monte Carlo method for assessing color rendering quality with possible application to color rendering standards,” Color Res. Appl. 37(1), 13–22 (2012).
[Crossref]

Newsham, G. R.

E. E. Dikel, G. J. Burns, J. A. Veitch, S. Mancini, and G. R. Newsham, “Preferred chromaticity of color-tunable LED lighting,” Leukos 10(2), 101–115 (2014).
[Crossref]

Ohno, Y.

Y. Ohno, “Practical use and calculation of CCT and Duv,” Leukos 10(1), 47–55 (2014).
[Crossref]

W. Davis and Y. Ohno, “Color quality scale,” Opt. Eng. 49(3), 033602 (2010).
[Crossref]

W. Davis and Y. Ohno, “Approaches to color rendering measurement,” J. Mod. Opt. 56(13), 1412–1419 (2009).
[Crossref]

Y. Ohno, “Spectral design considerations for white LED color rendering,” Opt. Eng. 44(11), 111302 (2005).
[Crossref]

Y. Ohno and M. Fein, “Vision experiment on acceptable and preferred white light chromaticity for lighting,” Proceedings of the CIE conference on lighting quality and energy efficiency, Kuala Lumpur (2014).

Pointer, M.

C. Li, M. R. Luo, M. Pointer, and P. Green, “Comparison of real colour gamuts using a new reflectance database,” Color Res. Appl. 39(5), 442–451 (2014).
[Crossref]

Pointer, M. R.

Rea, M.

M. Rea and J. P. Freyssinier, “White lighting,” Color Res. Appl. 38(2), 82–92 (2013).
[Crossref]

M. Rea and J. P. Freyssinier, “Color rendering beyond pride and prejudice,” Color Res. Appl. 35(6), 401–409 (2010).
[Crossref]

Rea, M. S.

M. S. Rea and J. P. Freyssinier-Nova, “Color rendering: a tale of two metrics,” Color Res. Appl. 33(3), 192–202 (2008).
[Crossref]

Ronnier Luo, M.

C. Li, M. Ronnier Luo, C. Li, and G. Cui, “The CRI-CAM02UCS colour rendering index,” Color Res. Appl. 37(3), 160–167 (2012).
[Crossref]

Ryckaert, W. R.

Sandor, N.

N. Sandor and J. Schanda, “Visual colour rendering based on colour difference evaluations,” Lighting Res. Tech. 38(3), 225–239 (2006).
[Crossref]

Schanda, J.

K. Smet, J. Schanda, L. Whitehead, and M. R. Luo, “CRI2012: A proposal for updating the CIE colour rendering index,” Lighting Res. Tech. 45(6), 689–709 (2013).
[Crossref]

N. Sandor and J. Schanda, “Visual colour rendering based on colour difference evaluations,” Lighting Res. Tech. 38(3), 225–239 (2006).
[Crossref]

Shen, X. S.

Shur, M. S.

A. Zukauskas, R. Vaicekauskas, F. Ivanauskas, H. Vaitkevicius, P. Vitta, and M. S. Shur, “Statistical approach to color quality of solid-state lamps,” IEEE J. Sel. Top. Quantum Electron. 15(6), 1753–1762 (2009).
[Crossref]

Smet, K.

K. Smet, G. Deconinck, and P. Hanselaer, “Chromaticity of unique white in illumination mode,” Opt. Express 23(10), 12488–12495 (2015).
[Crossref]

K. Smet, J. Schanda, L. Whitehead, and M. R. Luo, “CRI2012: A proposal for updating the CIE colour rendering index,” Lighting Res. Tech. 45(6), 689–709 (2013).
[Crossref]

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The shaded area of Fig. 2 is an approximate boundary; some SPDs far off-Planckian can in fact slightly enter the grayed-out zone.

Specifically, the small color difference sets which are most relevant for color rendition calculations.

The chromaticity of samples only weakly depends on CCT in CAM02-UCS, so that color space uniformity at a given CCT is translated to other CCTs.

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In past research, use of the RMS mean has been proposed. In our case however, the large number of samples makes the arithmetic mean a safe and simple choice. Besides, in practice, arithmetic and RMS means yield nearly identical results for most SPDs.

These boundaries were obtained by considering the 5,000 SPDs of Appendix A, together with a second library of 550,000 four-laser-line spectra with a CCT of 3000 K, whose peak wavelengths were systematically varied.

A. David, to be published.

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Lightness shifts are also possible but are not shown for simplicity. Further, Fig. 1 only shows average color shifts; however in practice metameric colors generally undergo different shifts.

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Figures (12)

Fig. 1
Fig. 1 (a) A light source can induce various color shifts, as shown here in the (a', b') plane, such as (1) desaturating (chroma decrease), (2) hue shift, and (3) saturating (chroma increase). These shifts form a vector field that varies through color space [25,28]. (b) Hypothetical light source causing purely saturating shifts; loss of fidelity is then associated with a maximal gamut increase.
Fig. 2
Fig. 2 Tradeoff between fidelity and gamut; light sources can only reside in the non-shaded area. Each dot corresponds to an SPD as described in Appendix A (red dots: ‘real’ SPDs from [8]; blue dots: synthetic SPDs).
Fig. 3
Fig. 3 Workflow of sample sets generation.
Fig. 4
Fig. 4 Gamut of three sample sets (cross-sections of CAM02UCS space). Red: large set; Blue: color-difference samples; black: NCS atlas.
Fig. 5
Fig. 5 (a) Pixelation approach. All the samples within a pixel are considered (approximately) metameric. Values are averaged over each pixel, then across pixels. (b) Map showing the local value of color error dE in (J’, a’, b’) space. The calculation is performed over the Reference Sample Set. The corresponding SPD (here a neodymium incandescent source) is shown in (c).
Fig. 6
Fig. 6 (a) Equal-energy SPD. (b) and (c) First- and second-order perturbations to the SPD with maintained chromaticity. The corresponding color errors scale with (r')2 and (r″)2. d-e) Flatness figures of merit (r')2 and (r″)2 for two sample sets. Solid lines correspond to the Reference Set (which has undergone the flattening procedure) and are approximately constant. Dashed lines correspond to a random set (where samples were selected without consideration of wavelength uniformity) and show large peaks and valleys.
Fig. 7
Fig. 7 (a) Reflectance of the 99 CES of the Final Set. Reflectance variations are distributed evenly with no privileged wavelength, in accordance with the spectral uniformity requirement. (b) Corresponding coordinates in CAM02-UCS, when the CES are illuminated by a 5000 K blackbody radiator; the CES are uniformly distributed within the NCS gamut. The colors are indicative of the samples’ perceived colors.
Fig. 8
Fig. 8 Workflow of Rf and Rg calculation. Calculations are in CAM02-UCS and use 10° color matching functions (CMFs) (except for CCT).
Fig. 9
Fig. 9 (a) Correlation between Ra and Rf for the 401 SPDs of [8]. The color of each point indicates its LER. (b) Approximate Pareto boundary for (LER-Ra) (solid line) and (LER-Rf) (dashed line).
Fig. 10
Fig. 10 Detail of Fig. 9(a), showing the correlation between Rf and Ra. The SPDs are classified by type of light source.
Fig. 11
Fig. 11 (a) Correlation between GAI and Rg. Scatter is large, even over a narrow CCT range of 2900–3100 K (blue dots). (b) Color icon. The icon draws the relative change in (a', b') coordinates between the reference illuminant and test source, averaged in each hue bin. The white circle represents reference colors, and the black line and vectors show the color distortion of the test source (here, a typical blue-pumped white LED with Ra = 82).
Fig. 12
Fig. 12 (a) Correlation between Rf computed over the Reference Set and the Final Set. Each point is an SPD. (b) Cumulative histogram of the difference δRf between the two measures. Dashed lines: 95% confidence interval.

Equations (6)

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| ( r' ) 2 ( r' ) 2 |dλ
F= k 1 | ( r' ) 2 ( r' ) 2 |dλ + k 2 | ( r" ) 2 ( r" ) 2 |dλ
C= c 1 E( R f ref , R f fin )+ c 2 E( R g ref , R g fin )+ c 3 | ( r' ) 2 ( r' ) 2 |dλ + c 4 ( I ref I fin ) 2 dθ
R f '=100k×ΔE
R f =10×ln( exp( R f '/10 )+1 )
R g =100× A test / A ref

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