Color Research and Application
OPTIMIZATION OF LED-BASED LIGHT BLENDINGS FOR OBJECT
PRESENTATION
Journal: Color Research and Application
Manuscript ID: Draft
Wiley – Manuscript type: Research article
Date submitted by the authors: 2007, October 15th
Authors: Boissard, Sophie; Fontoynont, Marc;
Ecole Nationale des Travaux Publics de l'Etat
Key words: Light-emitting diodes, color rendering, color
perception, colorimetry
Corresponding author:
Sophie Boissard
Ecole Nationale des Travaux Publics de l'Etat
2 rue Maurice Audin
69518 Vaulx-en-Velin
France
Phone: + 33 (0)4 72 04 77 19
E-mail: [email protected]
Number and figures: 18
Number and tables: 6
Number and pages (including this page): 17
John Wiley and Sons
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Color Research and Application
OPTIMIZATION OF LED-BASED LIGHT BLENDINGS FOR OBJECT
PRESENTATION
Sophie Boissard, Marc Fontoynont
Ecole Nationale des Travaux Publics de l'Etat, Vaulx-en-Velin, Lyon, France
ABSTRACT
This study looks at the perceived quality of LED-based lighting of various colors. The
objective was to find out whether LEDs could provide better (i.e. more relevant and
acceptable) lighting than that which is obtained with standard halogen or fluorescent
sources. The perception of objects was assessed under different lighting schemes.
Subjects were invited to add red, cyan and/or amber to white LED-based light in
order to match the halogen and fluorescence rendering on specific targets: a color
chart and a painting. They were also asked to rate the difference between the two,
and to express their preference.
The results obtained for the perception of LED-based lighting were quite positive.
Color blendings of LED light were found to provide illuminated situations similar to
halogens or fluorescent sources. These blendings were well accepted, and indeed
often preferred, although the Color Rendering Index (CRI) was always low. This
indicates that the CRI as it stands is inadequate to characterize the color rendering
of solid-state light sources, and needs to be updated.
LED-based lighting systems seem to have considerable potential for use in shops
and display units, where they may well outperform existing lighting systems.
Key words: colorimetry, LED, color rendering, color perception
1. INTRODUCTION
The Light-Emitting Diode (LED) is gradually taking over many lighting applications. It
has changed the concept of lighting, in terms of "smart" applications with easily
adjustable power, chromaticity control, and higher efficiency than tungsten-halogen
sources
1-3
. Its characteristics are very different from standard sources. Its specific
radiation distribution pattern over the visual spectrum raises questions about
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whether conventional CIE colorimetry and the CRI calculation method are applicable
to it 4, and work is currently being done to qualify the color rendering of LEDs
5-9
, with
a view to developing new practical and professional applications. Of particular
interest is the question of color quality, including that of color rendering, but also
color preference, color discrimination, color harmony, etc.
10
The emission spectra of colored LED sources are narrow, and mono-peaked in the
visible range, unlike "conventional" light sources. There are several ways of using
them to produce white light, but the spectrum still contains gaps
11
. Differences in
spectral power distributions of light sources imply differences in perceived colors,
and this can play an important role in the appearance of objects. But LED-based
light sources can produce saturated colors, and can also make them appear more
vivid.
Hence our question: Would this type of spectral distribution be capable of
adequately rendering the colors of different objects? More precisely, we wanted to
find out whether it is possible to match fluorescent and halogen light with blendings
of LED light. We also wanted to look at the acceptability of LED-based lighting, and
to assess the degree of opinion in its favour.
2. EXPERIMENTAL SETUP
In order to study these questions, we developed an experimental apparatus that
could be used to match different light sources, and to evaluate object perception
under LED light. A team from Philips Lighting, Lyon, France, assisted us in the
development process.
Presentation of the apparatus
The equipment was made up of three identical compartments (600 x 300 x 300 mm)
placed side by side. In each compartment there was a luminaire concealed by a
polycarbonate double diffuser on its upper surface. A diffusing ceiling allowed the
light to be perfectly blended, thus providing homogenous illumination. The three
compartments were lit by different light sources. The central compartment and the
one on the left were lit by six different varieties of LED, the one on the right by
halogen or fluorescence. In this particular experiment, we used just two
compartments, namely the one on the right (fluorescence and halogen sources) and
the one in the centre (LEDs). The test device is shown in Figure 1.
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Color Research and Application
Figure 1: Test apparatus for chromatic comparison (developed by Philips/ENTPE)
Sources
The compartments with LEDs were lit with six types of LED:
-
8 LUXEON I red
-
8 LUXEON I cyan
-
8 LUXEON I green
-
8 LUXEON I amber
-
8 LUXEON I cool white
-
18 LUXEON I warm white
During the experiment, we only used and tested these sources.
The temperature in the compartment with the LEDs was checked and stabilized prior
to the experiment. The color specification of each LED is given in Table 1.
Table 1: Color specification of the light emitted by the LEDs (DW = dominant
wavelength, CCT = correlated color temperature)
The reference compartment was lit by halogen or fluorescence. It contained:
-
2 fluorescent tubes (TL5 24W/940)
-
5 halogen lamps (Philips Master 45W)
The sources' characteristics are given in Table 2.
Table 2: Color specification of the light emitted by the reference sources
Spectral power distributions were measured at the surface of a spectral reflectance
standard
from
Gigahertz-Optik
(BN-R986SQ2C)
using
a
Specbos
1200
spectroradiometer in the same configuration as a normal observer (Figure 2).
Figure 2: Spectral power distribution of the light sources used in the experiment,
measured by a Specbos 1200 spectroradiometer
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The intensity of the sources was adjusted by using a mixing console, giving different
colors and levels of illumination.
Characteristics and calibration of the apparatus
Uniformity
We first checked the luminous uniformity of the light diffuser by measuring the
exitance at different points on each diffusing ceiling. We discretized the ceiling and
measured the exitance for different graduations. We obtained less than 2%
difference in luminous exitance over the entire surface of each compartment. We
check the uniformity in the vertical plan at the bottom of the box and we find at least
10 % difference in illuminace.
Exitance as a function of the position of the slider
We measured luminous exitance at 10%, 20%, 30%…100% graduation, then used
linear approximation with the least square method to construct our model. We
obtained a very good linear approximation, with coefficients of determination close to
1. In fact the worst coefficient was R 2 = 0.987 (Figure 3).
We then checked the model for 15%, 25%…95% of graduation, and again the
coefficient of correlation was close to one. We concluded that our model was
representative.
We obtained a linear relation between the exitance of the ceiling and the position of
the slider in the mixing console. And knowing the maximal exitance of the ceiling
(when graduation is at 100%) and the slider’s position of the sources, we could
deduce the exitance at this graduation. Moreover, the exitances were additive, so
that knowing the sliders’ position of all the sources, allow to calculate the exitance
for the whole ceiling.
Figure 3: Linear approximation of the exitance as a function of graduation, for amber
LEDs
Spectrum as a function of the position of the sliders
The aim of the calibration exercise was to determine the spectral power distribution
for all the different blendings of LEDs.
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We have test and verified that the spectral power distribution is proportional to the
luminous flux, and thereby also to the exitance. As a result, if we know the spectral
distribution at the maximum graduation for each source, we can deduce the
spectrum at different proportions of the source. Furthermore, the fact that the
spectra are additive means that if we know the proportion of each source, we can
determine the total spectrum of a given blending.
In order to do this, we developed a program which calculates the spectral power
distribution for every position of the slider on the mixing console.
This program was checked by comparing the spectrum calculated by the program
and the spectrum measured with a Specbos 1200 spectroradiometer.
The results showed that the differences between measured and calculated spectra
were less than 5% in the worst case (Figure 4).
Figure 4: Comparison of the measured and calculated spectra
Having done the calibration, we were able to determine the spectral power
distribution of blendings of LED light for each position of the slider.
3. EXPERIMENTAL PROTOCOL
The experiment consisted of testing the acceptability and quality of white LED
sources. We also wanted to study blendings of LED-light similar to standard
sources, reproducibility errors and users' opinions about LED-based lighting.
The aim of the experiment was to compare the perception of objects under LED and
standard (fluorescence and halogen) sources, and to find out the acceptability of,
and preferences for, the different types of lighting.
We specifically wanted to:
-
find out how to visually simulate fluorescent and halogen lighting with LEDs;
-
determine which lighting people tend to prefer, based on color rendering;
-
look for other parameters that might influence the perception of LED light.
The first part of the experiment examined the possibility of using white and colored
LED light to produce blendings which would be seen as equivalent in color rendering
to light produced by halogen or fluorescent sources. To do this, we carried out color
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matching tests. That is to say, subjects were asked to match the color of an object
illuminated by a standard source and the same object illuminated by LEDs.
Experimental conditions
Physical surroundings
The experiment took place in a room with no daylight or ambient light. The
compartments were painting in black (Munsell N1).
Illuminance level
The experiment consisted of matching two copies of pictures presented under
different lighting condition. The subjects were asked to adjust the LED light so that it
would be as close as possible to the reference light source. The addition of LED light
increased the overall illuminance level, and, given that white LEDs on their own can
give a maximum of around 180 lux, we considered that by the end of the matching
process, the level would reach around 250 lux in the vertical plan at the bottom of
the box. So we set the standard sources at this level for the duration of the
experiment.
It might be noted that in his comparison experiment with LED lighting, Schanda
12
also used an illuminance of 250 lux.
For the fluorescence and halogen sources, this illuminance level was obtained by
dimming them. Their color specifications are given in Table 3.
Table 3: Characteristics of the fluorescent tubes and halogen lamps
Targets
Our targets were a color chart and and a painting by the Dutch painter Vermeer, in
other words a figurative and a non-figurative target. The Gretag Macbeth color
checker is a standard for visual comparison, but to use the entire chart seemed
unsuitable for this experiment, because it would have been difficult for the subjects
to match 24 colors; we therefore decided to use a chart comprising 8 colors from the
Gretag Macbeth range which covered the complete hue circle and were saturated
(Figure 5). The color specifications are given in Table 4, and the spectral radiance
factors in Figure 6. We printed the charter on a HP 5500hdn color LaserJet.
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Figure 5: Target 1: the 8-color chart
Table 4: Characteristics of colors used in our color chart
Figure 6: Spectral radiance factors of the colors used in the color chart
As for the second target, we did not want to introduce unnecessary differences, so
we printed our chosen picture on the same printer. But we wanted to make
polychromatic comparisons. We found that the most difficult colors to reproduce
were the yellow and the green, and as a result we looked for a picture in which both
of them were to be found. Vermeer worked a lot on the use of daylight, and this
played an important part in our choice of picture, his Astronomer (Figure 7).
Figure 7: Target 2: Vermeer's The Astronomer, (1668)
Choice of LEDs
As noted previously, the matching process began with white LEDs (warm or cool) in
order for there to be sufficiently high illuminance levels. Cyan and green LEDs have
neighbouring spectra, and we decided to use only cyan because it fills the gap in the
white spectrum. We used red as a principal color, and amber as a secondary color.
The comparisons began with white (cool or warm), followed by the addition of red
and cyan (in different orders), and finally amber, for the final retouching.
Subjects
Forty-six people – eleven females and thirty-five males – took part in the experiment.
Screening with Ishihara plates prior to the start of the experiment
13
showed that all
of them had normal color vision. Seventeen had had training in lighting or in color,
but the others had no specific experience in these fields (Figure 8). Their ages
ranged from 22 to 62 years.
Figure 8: Composition of the subject group (46 members)
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Experimental procedure
Prior to the start of the experiment, the subjects were screened for color vision
deficiencies, and they were asked some questions about their age, sex, eyesight,
etc. Then, the observers were permitted to accommodate to the dark room,
observing test samples in one or other booth for approximately 5 minutes. During
this time, they had an oral explanation of the experiment and they were invited to
familiarize themselves with the experimental apparatus.
Two identical scenes were placed side by side. At the beginning of the experiment,
the subjects viewed the color chart under fluorescent light and cool white LED light.
They then added red and cyan, firstly beginning with the red, then with the cyan
LEDs, and then both, until they achieved a match with the light produced by the
fluorescent source. They then added amber to the optimal blending until the
reference light source was reproduced.
The subjects were then asked to perform the same matching procedure again, but
this time using warm white LEDs.
After this, the color chart was presented under halogen light and white LED light
(cool or warm), and the subjects added cyan, red and amber until they achieved a
match with the halogen light.
When they had finished the comparison with the chart, each subject was asked to
repeat the first step (i.e. to match the fluorescence with cool white LED light) in order
to estimate his or her reproducibility error.
Then the same matches were carried out for Vermeer's painting.
The subjects could take as long as they wanted to complete the experiment. The
actual time taken turned out to be around 30 minutes.
Figure 9: Test apparatus, with a subject adjusting LEDs
At the end of each matching, all the light sources were at the same illuminance level
(250 ± 20 lux), and each subject was asked to:
-
estimate how close the LED blending was to the reference source (the same,
very close, close, different, very different);
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Color Research and Application
-
state which light seemed to be the "best" (in terms of quality or if they don’t
know what to state, they have to express their preference);
-
say whether or not the LED-based lighting was "acceptable".
4. RESULTS
Reproducibility errors
The experiment relied upon the subjects' perception and judgment. There were
many factors that could influence their opinions, and if a subject carried out the
same experiment twice, the same results were not obtained. In order to understand
the phenomenon, and to work out the degree of uncertainty involved, we calculated
"reproducibility errors", by asking the subjects to repeat their first matching, namely
that of fluorescence and cool white, red, cyan and amber LEDs. Box-and-whisker
plots for the different colors showed that 75% of the results had an uncertainty of 1.5
graduations for each color and in each situation. The higher the number of colors,
the larger the uncertainty. In chromaticity coordinates, the mean error was 0.016 in
x, and 0.01 in y, i.e. 4% error in x and 3% in y (Figure 10). This level of
reproducibility error implies that there is visual tolerance.
Figure 10: Reproducibility errors
Influence of secondary parameters
Influence of targets
We wanted to know if the matching depended on the nature of the target, and/or the
colors present. Figure 11 shows that the dispersion in the chromaticity diagram was
the same for the chart (red points) as for the picture (blue points).
Figure 11: Dispersion in the chromaticity diagram for the matching of the halogen
source with warm white, cyan, red and amber LEDs, both for the Vermeer painting
(blue) and the color chart (red)
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The two sets of matchings (with the chart and with Vermeer's painting) produced the
same conclusions on the estimation of differences and color rendering. But the
subjects found that matching was easier with Vermeer's picture, because they could
connect the colors with objects.
It would thus seem that if we want to find optimal blendings of LEDs, it is better to
use actual scenes than non-figurative color samples.
Influence of the order of use of the LEDs
We wanted to find out if the color of LED with which a subject started off had any
influence on the final lighting. We asked them to begin with either red or blue LEDs,
or to adjust both at will. The comparison showed that the order did not seem to
make a significant difference (Figure 12). The results were similar whether the
subjects began with cyan or red LEDs before adding amber.
Figure 12: Differences in adjustment between beginning with red LEDs and cyan LEDs
Sensitivity to color shifts
It was found that certain colors had more influence than others, and that for a given
amount of variation they gave different changes in perception. For example, adding
a given amount of red changed the appearance of the picture more than adding the
same amount of amber. Comparing the standard deviation for the different colors
during the matchings, we found that red LEDs had more influence than amber. For
example, even if the red was just 20% more luminous, we were in the 1:4 range with
regard to the positions of the sliders. We conclude that variations in red have more
influence on the perception of light than variations in amber.
Other influences
We found no differences related to the subjects' sex, eyesight or level of expertise.
The "experts" and the "naive" subjects had the same levels of reproducibility errors,
and similar positions in the chromatic diagram (Figure 13). This shows that, overall,
the experts (red points) did the same type of matching as the naive subjects (blue
points).
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Figure 13: Dispersion in the chromaticity diagram for the matching of halogen with
warm white, cyan, red and amber LEDs for "naive" subjects (blue) and "experts" (red)
Similarities in lighting between LEDs and standard sources
After each matching between LEDs (white, red, cyan and amber) and the reference
sources, the subjects were asked to estimate how close the LED blending was to the
reference source (i.e. the same, very close, close, different, very different).
The histograms in Figure 14 represent the estimation of the proximity for the
halogen and fluorescent sources, and for the LED-based sources.
Figure 14: Estimation of the proximity of LED light to that of the halogen and
fluorescent sources
Figure 14 shows that the lighting obtained with LEDs was judged to be close to that
which was obtained with halogen or fluorescent sources, except when the subjects
tried to match halogen sources beginning with cool white LEDs. In this case, more
than 70% of them estimated the lighting to be "different", or "very different".
There may be blendings of LED light that are similar to halogen or fluorescent
sources. In particular, cool white LEDs seem to give better approximations to
fluorescent sources, and warm white LEDs to halogen sources. 85% of the subjects
reported that fluorescent light was "close", "very close" or "the same", compared to
cool white, cyan, red and amber LEDs, and 70% successfully matched halogen
sources with warm white, cyan, red and amber LEDs.
The characteristics of the visual blendings seem to be:
-
for halogen: 67% warm white, 8% cyan, 14% amber and 11% red; or 45% cool
white, 17% cyan, 20% amber and 18% red.
-
for fluorescence: 58% cool white, 19% cyan, 11% amber and 12% red; or 78%
warm white, 16% cyan, 2% amber and 4% red.
As regards perception, LEDs seems to be quite suitable for matching both
fluorescent and halogen sources. But what happens if we consider a chromatic
approach?
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Chromatic comparisons
For each observation, we converted the graduation results into chromaticity
coordinates (x, y), using the calibration.
In order to get an idea of the color differences, we plotted the MacAdam ellipses
onto the chromaticity diagram. The ellipses were centred on the locus of halogen or
fluorescence, and represented the boundaries between small, medium and large
differences.
Figure 15: Representation of the matching of reference sources with LEDs in the
chromaticity diagrams
The chromaticity diagrams (Figure 15) show the values to be scattered. This
confirms the hypothesis of visual tolerance, but also underlines the difficulties
involved in the task of adjustment. If we consider the chromaticity diagram for the
matching of halogen sources with cool white LEDs, we see that there is a
considerable amount of dispersion, and that none of the subjects makes it into the
"small difference" ellipse. From this we may conclude that when the types of light are
too different, it is very difficult for people to match them, and the values are
scattered.
In the other diagrams, even where the values are scattered, they regress to the
locus of the standard source.
Comparing the chromaticity diagrams, we see that for the matching of halogen
sources with cool white, red, cyan and amber LEDs, as expected, none of the
subjects felt that the lighting was close to that of the halogen source, and more than
25% of the subjects were outside the "medium differences" ellipse. As regards the
matching of halogen with warm white LEDs, few people (5%) recorded large
differences, the others being within the "small differences" ellipse, or very close to it.
For matchings with fluorescent light, the subjects got closer with cool white LEDs
than with warm white. Around 45% of the subjects were in the "small differences"
ellipse.
If we look at the chromatic coordinates of fluorescence, halogen and the mean
values of LED blending, we see that the subjects were quite successful at
reproducing the chromaticity coordinates (Table 5).
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Table 5: Color specification of LED blendings (CW = cool white, WW = warm white, R
= red, C = cyan, A = amber)
Blendings of LED light thus seem capable of reproducing lighting situations that are
quite similar to those of fluorescent and halogen light. And as we have already seen,
it is easier to approximate fluorescence with cool white LEDs, and halogen light with
warm white LEDs. The results obtained by the subjects correspond to MacAdam
ellipses in the chromaticity diagram.
Spectral comparisons
As we have seen, matchings with halogen sources give: 67% warm white, 8% cyan,
14% amber and 11% red, or 45% cool white, 17% cyan, 20% amber and 18% red.
For fluorescence, the figures are: 58% cool white, 19% cyan, 11% amber and 12%
red, or 78% warm white, 16% cyan, 2% amber and 4% red. The spectral power
distributions of these blendings are given in Figure 16.
Figure 16: Spectral power distribution for the visual blendings of LEDs
LEDs and color rendering
Some studies have found no correlation between the Test-Color method
recommended by the CIE
4,14
and visual experiments
7,15
. In order to examine this
question, we asked our subjects to give their opinion about perception of color with
LEDs and standard light sources. At the end of each match, they were asked which
light seemed to be "best for color rendering", and whether or not they considered
LED-based light acceptable. When they had a problem about the interpretation of
"color rendering", we asked them to define which was of the best quality, which light
allowed them to distinguish best between the different colors, and the type of lighting
they preferred.
In most cases, the subjects preferred LED-based light, considering it to be of higher
quality than halogen (73%) or fluorescence (44%) (Figure 17).
Figure 17: Comparison of the perceived quality of three types of light: blendings of
LEDs, fluorescence and halogen
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We calculated the particular and general CRI according to the Test-Color Method,
as recommended by the CIE
4,14
. Ra8 is the general color rendering index, i.e. the
average of the indices of the 8 test samples specified by the CIE, and Ra14 is the
average of the indices of the 14 test samples specified by the CIE. We also
calculated the provisional NIST Color Quality Scale (CQS) values
5,16,17
. CRI and
CQS values are given in
Table 6.
Table 6: CRIs and provisional CQS values (CW = cool white, WW = warm white, R =
red, C = cyan, A = amber)
All the LED blendings had lower CRIs than the fluorescent and halogen sources.
For the LEDs, Ra8 was in the 75-85 range, and Ra14 in the 75-82 range, whereas
fluorescent light had Ra8 at 91, and Ra14 at 85, and halogen had Ra8 at 96 and Ra14 at
95. But LED light was more popular. In other words, although it has low CRIs, as
computed with standard CIE method, LED light is well accepted, and indeed often
preferred to fluorescent or halogen light. This means that people's perception of
color does not correlate well with CRI values. As a result, we feel that the CRI does
not properly express color rendering preferences with regard to LED-based light
sources, and that further work is necessary.
With the CQS values, the differences are less, and blending cool white, red, cyan
and amber LEDs gives better CQS scores than halogen. Fluorescent lamps produce
the best scores, which is in keeping with the perception of the subjects in this
experiment.
It might therefore be concluded that the CQS is better than the CRI at expressing
the color quality of LED-based light sources. But further studies are needed, in order
to find out if the CQS also performs better for other types of light source.
Further investigations
Further the subjects’ comments; their preference for LEDs light sources in
comparison with standard light source is due to an increase of colourfulness and in
the perceived chroma of colour. When they have to make the comparison with
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halogen and LEDs, they also mentioned that with LEDs there was an increase in
color contrast. The last point should be minimised because the halogen was
graduated and thus the light emitted was very reddish and do not permit to well
distinguished the adjacent color.
Checking chromaticity distortions and changes in gamut area in chromaticity
diagram is a possibility for investigating the cause of the preferences in term of color
rendering. The comparison of the gamut area of the different light sources was
adapted to the color of our charter of color for the blendings of LEDs and for
fluorescence and halogen.
Figure 18: CIELAB coordinates of the 8 color of our color chart when illuminated by
the reference sources and by the blendings of LEDs
The two graphs, show the gamut of the color of the color chart span in a*, b* plane
of CIELAB space illuminated by the reference sources (halogen and fluorescence)
and the mixing of LEDs which are the closer according to the subjects given in
Figure 16.
The much larger distortion in case of blendings of cool white, cyan, amber and red to
match fluorescence compared to the fluorescence source, are obvious. The lateral
distortion on the left and right side (in the direction of green and red) is bigger with
LEDs in both cases.
The larger gamut means that these sources can render more colors and the more
saturated the colors will appear. That may be the reason why despite the fact that
their general color rendering indexes are low, the subjects thought that LEDs are
better in color quality.
5. CONCLUSION
The results obtained for the perception of LED-based light are quite positive,
suggesting that it should be possible to find blendings of LED light which are similar
to halogen or fluorescent light. LED blendings are also well accepted, and are often
the preferred type of light. So they offer a plausible alternative to standard light
sources, and this is an encouragement to future developments in LED technology.
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The preference for LED-based lighting that was found in this study suggests that for
LED lighting, the CRI in its current form correlates poorly with people's personal
judgment. It is common believed that a light source with a high CRI renders colors
better than a source with a low CRI, and is better liked. But the CRI only functions
well the color fidelity of standard light sources, and does not include aspects of color
quality such as color preference or chromatic discrimination. Other studies have
found inadequacies and shortcomings in the CRI metric, and have shown that it
does not always provide a reliable description of visual perception of color rendering,
especially in the case of LED-based light sources
6,10,18-20
. In other words, the
present CIE test method needs to be modified if it is to characterize with precision
the color-rendering properties of LED-based light sources. The CRI cannot be
recommended as a metric in the development of solid-state light sources, in that it
may underestimate overall performance. A metric for the accurate quantification of
color quality is needed. More experimentation based on visual assessment can be
expected to improve the qualification of color rendering. And this is part of the work
we will be doing in partnership with the TC1-69.
The acceptability of, and indeed preference for, LED-based lighting suggest that it
could have many applications, especially in the area of shop and display lighting,
and that it could be even more appropriate for other uses, e.g. in the home or the
street. Further progress and improvements in this technology should find numerous
practical applications, and in any case will certainly change our way of thinking about
lighting.
ACKNOWLEDGEMENTS
The authors gratefully acknowledge the contribution of the R&D team at Philips
Lighting, Miribel, Lyon, France, in the development of the experimental apparatus.
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