LIGHTING DESIGN
& APPLICATION
Spectral vision of a colour scene is determined by the product of the spectral
power distribution of the light source, the spectral radiance (reflection) factor
of the scene components and the photopic spectral visibility or V() curve.
A luminance model for evaluating colour
rendering qualities of light sources
With the introduction of LED lighting, the
lighting industry is faced with an infinite
number of colour sources of light with
numerous SPDs.
The summation of SPDs can create even
more diverse sources of light through
combinations of these LED sources.
The colour appearances and colour
rendering capabilities of these sources
are currently an important topic of
debate for scientists, lighting engineers,
vision scientists and architects. The
need for improved but simple metrics
to define colour appearance and colour
rendering capabilities of light sources
is tremendous. The current metrics
mostly used in the lighting fraternity is
the CIE definitions of correlated colour
temperature (CCT) and general colour
rendering index (Ra).
The focus of this research is on colour
rendering metrics for light sources
and not colour appearance. There is
a need for a simple, single-number
rating value for basic colour rendering,
which shows good correlation with
viewer agreement. We investigated a
method for evaluating colour rendering
by determining (reflected) luminance
from 12 CIE colour samples. The
incandescent/halogen light source was
used as reference and an off-the-shelf
LED lamp of the same CCT was used
as test source. The main deficiency of
the incandescent/halogen source as
reference relates to the specific SPD of
this source with very low output in the
blue range of wavelengths and very
strong radiation in the red wavelengths.
The photopic vision curve or V() curve
by Prof. FW Leuschner and JGJ van der Westhuizen,
University of Pretoria
adds to the very low reflected luminance
from a blue colour sample (CIE colour
sample 12 – “Strong Blue”) when
illuminated by an incandescent lamp. This
is of course accentuated during scotopic
or mesopic vision at low light levels.
The reflected luminance from the two
lamp samples was compared and the
results produced a strong confirmation
of some of the deficiencies of the
general colour rendering index (CRI).
Introduction
At present, all lamps are characterised
by a number of electrical, photometric,
colorimetric, life expectancy, dimensional
and cost (capital and operating cost)
characteristics. Colour appearance and
colour rendering are the most important
factors in evaluating the colorimetric
quality of a lamp for acceptance
and comparison with other lamps,
especially in the case of retrofitting
existing light installations for electrical
energy saving or general upgrading. The
colour qualities are mainly the colour
appearance and the colour rendering
metrics, usually specified by the CIE
correlated colour temperature (CCT)
and the general CRI (Ra). Neither of
these two quantities are very realistic and
they are definitely not accurate metrics
for all light sources.
Unless the chromaticity coordinates of
two light sources are identical, they will
not appear the same and, unless the
lamp under consideration’s chromaticity
June 2013 - Vector - Page 24
coordinates are on the Planckian curve,
the CCT can be very misleading.
The CIE Ra value is limited to eight nonsaturated CIE colour samples (R1 to R8)
and the reflection from these samples
is compared to that obtained from a
reference source, which is a Planckian
radiator of the same CCT (approximated
by an incandescent or halogen lamp).
Clearly, these eight samples cannot
represent most or all of the colours
in visual environments. Neither can a
Planckian radiator (incandescent) light
source be viewed as a good reference
source as the light produced is very
low in the short (blue) wavelengths and
very high/dominant in the long (red)
wavelengths.
There are more than ten different
proposals for evaluating colour rendering.
These concentrate on colour fidelity,
colour preference, etc. It is felt that a
single number cannot fully cover all
these components of colour rendering.
It is, however, also accepted that the
mathematical calculations cannot
dominate the visual appraisal by samples
of people from different groups, as the
psychophysical variables are too diverse
to capture all colour “rendering” attributes
in one or more mathematical calculations.
Comparison of spectral
luminous flux for halogen,
LED PAR16 GU10
We started our experiments by comparing
two lamps (one incandescent/halogen
and one LED lamp) of the same CCT
and the same reference luminance on a
“white standard reflector”, but different
Ra values of 99 and 83 respectively.
 Incandescent/halogen lamp:
240 V 50 Hz 50 W PAR16 lamp
(GU10 base), beam angle ≈ 36°.
 LED lamp: 230 V 50 Hz 5 W
(GU10 base), beam angle ≈ 36°.
A KonicaMinolta CS-2000
spectroradiometer was used for all
spectral measurements.
The following was determined for both
lamps:
 Spectral power distribution from 380
to 780 nm for each lamp.
 This was used to calculate the
following: Colour rendering indices
from R 1 to R 12 , general colour
rendering index R a , correlated
colour temperature (CCT), x and y
chromaticity coordinates, dominant
wavelength and relative luminance.
The results are shown in Table 1.
Most colour quantities are similar, except
for the colour rendering metrics: Ra is
16% lower for the LED and R9 (“strong
red”) 81% lower for the LED. Comparing
the spectral luminous flux distributions
of the two lamps gives another picture.
A comparison of Figs. 1 and 2 clearly
indicates a very similar spectral luminous
flux distribution at around 575 nm,
with the halogen lamp stronger above
650 nm and weaker below 450 nm, but
no dramatic differences are evident. Both
graphs seem to be shifted to the right of
555 nm and both are stronger in the long
wavelengths than in the short wavelengths.
Reflected spectral luminous
flux, 12 CIE colour samples
The authors propose that a simple
weighted luminance comparison of all
12 colour samples be used to determine
a colour rendering value for any light
source. These include R 1 to R 8 for
calculating the Ra value, plus R9 to R12
for bright “strong” red, yellow, green
and blue respectively. One can include
R 13 “Caucasian skin” and R 14 “leaf
green”. R15 is a non-CIE colour sample
for “Asian skin” colour and a possible
“R16” for “African skin” colour can be
added. The following equation was
used to calculate the relative reflected
luminous flux of twelve colour samples
(R1 to R12) when illuminated by the two
light sources under test:
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ଷ଼଴
Where: Ri is the reflected luminous
flux from the specific colour sample
i =1 to 14.
Fig. 1: Spectral luminous flux distribution
for 50 W halogen lamp.
Fig. 2: Spectral luminous flux
distribution for 5 W LED lamp.
Quantity
50 W Halogen lamp
5 W LED lamp
Relative Luminance Lv
63,11
62,53
Correlated colour temperature CCT
2652
2651
Ra
99
83
R1
99
81
R2
99
90
R3
99
98
R4
99
80
R5
99
81
R6
99
88
R7
99
85
R8
99
63
R9
98
19
R10
98
78
R11
99
78
R12
97
74
x
0,4664
0,4663
y
0,4148
0,4145
Table 1: Colorimetric characteristics of halogen and LED lamps.
V() is the photopic eye response curve.
R() is the spectral reflectance of the
specific colour sample.
ej() is the spectral radiant flux from
the specific light source for j = 1 or 2.
The top section of Table 2 compares the
reflected luminous flux from all eight CIE
colour samples making up the general
colour rendering index Ra. The lower
section of the table compares the four
highly saturated (“strong”) CIE colour
samples 9 to 12 for red, yellow, green
and blue respectively.
Eight colour samples R1 to R8
The luminous flux reflected from the
June 2013 - Vector - Page 25
eight colour samples (R1 to R8) can be
assumed to be identical as the average
deviation is 2% and the highest is 4%,
considering the variation in source
luminance of 1%. So why should the
colour rendering of the LED be 16% lower
than that of the incandescent lamp? It is
also important to note that the values of
reflected luminous flux are all in a band
from 16,4 to 21,6 (a.u.) – low variation
and all these reflected colours will appear
to be almost equally “bright”.
Four colour samples R9 to R12
Note that these four colour samples
do not form part of the general colour
rendering index Ra.
Colour sample
50 W Incandscent
5 W LED
% Difference
Colour sample appearance
TCSO1
20,9
20,8
0
Light greyish red
TCSO2
19,4
19,4
0
Dark greyish yellow
TCS03
19,2
19,2
0
Strong yellow green
TCS04
16,8
16,5
2
Moderate yellowish gren
TCS05
17,5
17,2
2
Light bluish green
TCSO6
17,0
16,4
3
Light blue
TCS07
18,9
18,4
3
Light voilet
TCS08
21,6
20,8
4
Light reddish purple
Average
18,9
18,6
2
Ra
99,0
83,0
16
TCS09
11,0
9,9
10
Strong red
TSC010
40,6
40,7
0
Strong yellow
TSCO11
10,9
10,4
4
Strong green
TSC012
2,7
2,4
11
Strong blue
Average
30,5
27,5
10
Strong colours
Table 2: Comparing reflected luminous flux (p.u.) from twelve CIE colour samples when illuminated by two lamps.
The average luminous flux reflected from
the four colour samples (R9 to R12) is 10%
higher for the halogen lamp than for the
LED lamp, with only the “strong yellow”
colour sample showing a slightly higher
value for the LED than for the halogen
lamp. The deviations are, however,
still not significant with red and blue
10% or more. From these numbers one
can conclude that the saturated colour
sample representation is better for the
halogen lamp than for the LED lamp by
approximately 10%.
It is important that the values of reflected
luminous flux for red and blue colour
samples are much smaller than for
yellow and green, for both lamps, i.e.
around 40 (a.u.) for yellow and around
2 (a.u.) for blue. To understand the
reasons for this we have to look at two
main parameters:
 The radiant flux radiated by the source
at the peak spectral reflectance values
of the specific blue and red colour
samples (R9 and R12 respectively).
 The spectral photopic eye response
values at the same wavelengths as
mentioned here.
The blue colour sample shows a peak
at 408 nm and the photopic V(408)
value is 9,4 x 10-4. The halogen and
LED lamps show steep drops in radiant
flux below 420 nm, with the LED
peaking at about 450 nm. This is usually
suppressed through the phosphor to
produce more yellow/red light in the
LED, for a higher Ra value.
How to improve colour
rendering
Fig. 3: Spectral reflectance for four strong colours, red, yellow, green and blue.
June 2013 - Vector - Page 26
Fig. 3 shows the spectral reflectance
characteristics of the four saturated
(“strong”) CIE colour samples red,
yellow, green and blue. It is clear that
there are dramatic differences which
must be investigated further.
Once we multiply the spectral reflectance
of the colour samples with the spectral
photopic eye responsivity values, we
must understand the reflected spectral
luminous flux for different light source
SPDs.
Fig. 4 shows the effective spectral ranges
for the four colours and the dramatic
differences in producing reflected
luminous flux (proportional to the area
under each curve).
To match these spectral values to
produce the same luminous flux from
each colour sample, the different colour
sample SPDs must be multiplied by
the following factors (using yellow as
the reference): optimal colour mixing
ratios to establish constant luminous
flux from each reflector sample: red =
4,82, yellow = 1,00, green = 3,04 and
blue = 9,98.
Fig. 5 shows a clear increase in average
spectral reflectance factors for the 14
CIE colour samples, from about 0,08
at 360 nm to 0,54 at 830 nm.
To counter this tendency we require a
source SPD which should at least be the
inverse of the graph in Fig. 5 i.e. “high”
at the short wavelengths (blue) and
“low” at the long wavelengths (red). The
incandescent is the complete opposite
and even worse than the graph in
Fig. 5. This proves that the incandescent/
halogen lamp cannot be rated as 100%
CRI for all colour rendering indices R1 to
R15 and especially not the general colour
rendering Ra to be 100%.
Individual colour LEDs, however, can be
matched to produce virtually any SPD
for combinations of three or more LEDs.
The weighting factors listed here can
be included as well as compensation
for the V() curve at short and long
wavelengths. Such weighted reference
SPDs can then be accompanied by
categories of luminous efficacy of
radiation to produce a lamp comparison
matrix.
Conclusion
Luminance level reproduction of the CIE
colour samples R1 to R12 were used to
confirm one of the main deficiencies of
the general colour rendering index Ra
which uses an incandescent/halogen
source (of the same CCT) as the
reference lamp. The combined signal of
light source SPD, radiance (reflectance)
factor of the colour samples and the
Fig. 4. Spectral reflectance for four strong colours, red,
yellow, green and blue.
Fig. 5: Average spectral reflectance for
14 CIE colour samples.
photopic eye responsivity curve show
a clear weakness in short wavelength
(“blue”) light and even in the long
wavelengths (“red”), even for the
incandescent/halogen lamp itself.
Combinations of LEDs can be used to
compensate for these discrepancies.
Improved colour rendering will, however,
be accompanied by reduced luminous
efficacy of radiation. There will always
be a trade-off between the two metrics
which will be determined for each
specific application.
Note
This article is based on a paper
presented at the ninth IESSA Conference
& AGM, and is reproduced here with
permission.
June 2013 - Vector - Page 28
References
[1] CIE 13.3: "Method of measuring and
specifying colour rendering properties
of light sources," 1995 Vienna, Austria:
Commission International de I’Éclairage.
[2] Illuminating Engineering Society: The
lighting handbook: tenth edition: reference
and application, 2011, Illuminating
Engineering Society of North America,
ISBN 978-087995-241-9.
[3] W Davis and Y Ohno: “Toward an improved
color rendering metric”, Fifth international
conference on solid state lighting.
[4] V Viliuna, H Vaitkevicius, R Stanikunas,
A Svegzda and Z Bliznikas: “LED-based
metameric light sources: rendering the
colours of objects and other colour quality
criteria, Lighting research and technology,
43, Aug. 2011, p. 321 – 330.
Contact Prof. FW Leuschner,
University of Pretoria,
Tel 012 420-2283, leuschner@up.ac.za