Colour perception and rendering
Sophia Sotiropoulou
Hellenic Open University
• With starting point the definition and
explanation of several measures / metrics
available for evaluating the quality of artficial
lighting sources we will refer and discuss on
more general aspects of the quality of lighting
with reference to the principal mechanisms of
our vision and more precisely of colour
perception.
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Nowadays investment to SSL
• “…Widespread adoption of solid-state lighting
(SSL), which, as claimed, can achieve 50-70%
efficiency and could cut lighting-electricity
consumption by half, thereby cutting overall
electricity use by over 10%. By contrast,
fluorescents are limited to about 25%
efficiency and incandescents only 6%, with
most of the electrical energy converted to
waste heat….”
http://science.energy.gov/bes/highlights/2012/bes-2012-04-d/
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Nowadays investment to SSL
….Public lighting represents a significant share
of their total electricity costs, accounting for
up to the 60% of that budget.
“ …SSL is the most innovative lighting technology emerging on the
market. It offers high quality light and visual performance, while
providing substantial cost saving opportunities, reducing
light pollution in cities and driving innovation in the lighting and
construction sectors. When combined with intelligent light
management systems, SSL can save up to 70% of electricity used for
lighting and significantly reduce energy and maintenance costs
compared to current lighting installations…”
http://cordis.europa.eu/fp7/ict/photonics/docs
/ssl-cip/lighting-the-cities_en.pdf
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LED lighting quality
• cost saving: money and energy saving
• energy saving
• High LER (Luminous Efficacy of Radiation) of LEDs
is certain, but, what about their quality of lighting
(colour rendition, visual performance, etc)?
• reducing light pollution
• high visual performance
• Refers to achromatic vision
• high quality light
• Usually refers to colour quality, thus to colour
vision
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Colour and achromatic vision
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Visual information encoded in the
retina (light converted to signal)
According to the dual process theory (1957), in a first stage receptors (cones)
operate trichromatically and then the output signals of the first stage are the inputs
to the second stage, in which the signals are processed according to the opponent
colours theory.
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Colour perception - trichromaticity
B
[Livingstone, 2002]
G R
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Luminance perception
1
20
[Livingstone, 2002]
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L* channel - lightness
Daniil, 1974. Hellenic Postbank Collection
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Colour contrasts in art
[Livingstone, 2002]
Monet, “Impression Sunrise” (1872)
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Colour contrasts in nature
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Opponent colours theory – CIE LAB 1976
According to the theory of the opponent process
theory, developed by Ewald Hering (1834 -1918) in
the late 19th century, vision sensitivity is such that
colours are perceived in three dimensions: the
green-red axis , the blue-yellow axis and the black –
white axis.
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L* channel - lightness
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a* channel - (R/G information)
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L* + a* channels
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b* channel - (Y/B information)
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L* + b* channels
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Visual pathways to the brain
Hierarchical and parallel organisation
Source: http://thebrain.mcgill.ca/avance.php
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Two major pathways of the visual
information processing in the cortex.
Source: http://thebrain.mcgill.ca/avance.php
The “where system”: the dorsal visual pathway, for determining the position of the
objects in space (perception of movement and position)
The “what system”: the ventral visual pathway, for identifying objects (their shape
and their colour)
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The “action” pathway (dorsal) and
the “conscious” pathway (ventral)
Source: http://thebrain.mcgill.ca/avance.php
The “where system” (dorsal cortex (higher visual cortex areas)): by integrating the
spatial relationships between our bodies and our environment, it lets us interact
with this environment effectively (processing believed to be unconscious)
The “what system” (ventral cortex (midbrain)): forming conscious representations
of the identity of objects
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Colour and achromatic vision
“where” system - Magnocellular pathway – achromatic
“what” system – parvocellular pathway – colour vision
Magno Cells
Minority of cells in LGN: 1015%
Large receptive field
Fast conduction rate
High contrast sensitivity
Parvo Cells
Majority of cells in LGN: 8590%
Small receptive field
Slow conduction rate
Low contrast sensitivity
Able to differentiate only
coarse stimuli (low res)
Able to differentiate detailed
stimuli (high resolution)
Colour Blind
Colour Sensitive
Processes information about Processes information about
depth & motion
colour & detail
The parvocellular pathway must be double- duty: it supports finely detailed luminance
vision as well as colour vision
http://pip.ucalgary.ca/psyc-369/mod2-the-visual-system/unit2.3-visual-pathways/geniculostriate2.html
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Central and peripheral vision
R G B cones
distribution on the
retina
•
•
•
High acuity and spatial resolution in the centre of the gaze (foveal zone ~2 degree)
Need to align fovea with relevant features (focal points)
Explore our visual environment with gaze movements
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Central and peripheral vision
Anstis, S. ‘A chart demonstrating variation in acuity with
retinal position’, Vision Research, 14 , (1974): 589-592.
Sophia Sotiropoulou, HOU
Courtesy National Gallery of Art, Washington
24
26/6/2014
LED lighting quality
• high visual performance (refers to achromatic vision)
– How do we evaluate the visual performance of
lighting?
• high quality light (refers to colour vision)
– How do we measure the quality of light? Often we
refer to colour (rendering) quality…
– what are the most pertinent metrics for evaluating
colour quality, which are also appropriate for SSL?
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Visual performance
• Visual performance is referring to the speed and accuracy of processing
achromatic information (e.g., black print on white paper) by the human
visual system, (the speed and accuracy with which a visual task is
performed).
• The visual performance depends on the degree of contrast but also on the
luminance level, therefore also on the light intensity (lighting enhances
acuity) and the adaptation time that is needed for different light sources.
– At relatively high light levels (e.g. found in schools and offices), visual
performance is essentially unaffected by the spectral power
distribution of the light source, so full-spectrum light sources are no
better than any other light source.
– At relatively low light levels (e.g. outdoor lighting for orientation,
identification, and safety – in roads in the night, etc), the sensitivity of
the human eye is described by the mesopic conditions
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LER (Luminous Efficacy of Radiation)
• P (λ) is the spectral power density (SPD) of the white light source
• V(λ) is the eye sensitivity function, with maximum at 555 nm (photopic
conditions)
• 683 lm/W is a normalization factor
• Notice: Luminous efficacy of the source (LES) is defined as the ratio of
luminous flux to input electrical power.
• Practically we can calculate LER, if we know the SPD of the light source
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LER (Luminous Efficacy of Radiation)
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CRI-R96a, based on Munsell Atlas
test colours (CIE 1995)
CRI (Ra) = <Ri>
Sophia Sotiropoulou, HOU
Me
Appr. Munsell
Appearance under
daylight
TCS01
7,5 R 6/4
Light greyish red
TCS02
5 Y 6/4
Dark greyish
yellow
TCS03
5 GY 6/8
Strong yellow
green
TCS04
2,5 G 6/6
Moderate
yellowish green
TCS05
10 BG 6/4
Light bluish green
TCS06
5 PB 6/8
Light blue
TCS07
2,5 P 6/8
Light violet
TCS08
10 P 6/8
Light reddish
purple
TCS09
4,5 R 4/13
Strong red
TCS10
5 Y 8/10
Strong yellow
TCS11
4,5 G 5/8
Strong green
TCS12
3 PB 3/11
Strong blue
TCS13
5 YR 8/4
Light yellowish
pink
TCS14
5 GY 4/4
Moderate olive
green
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Swatch
29
CRI-R96a, based on Munsell Atlas
test colours (CIE 1995)
CIE (1995), 8 Munsell Test Colour Samples (TCS).
Sophia Sotiropoulou, HOU
Me
Appr. Munsell
Appearance under
daylight
TCS01
7,5 R 6/4
Light greyish red
TCS02
5 Y 6/4
Dark greyish
yellow
TCS03
5 GY 6/8
Strong yellow
green
TCS04
2,5 G 6/6
Moderate
yellowish green
TCS05
10 BG 6/4
Light bluish green
TCS06
5 PB 6/8
Light blue
TCS07
2,5 P 6/8
Light violet
TCS08
10 P 6/8
Light reddish
purple
TCS09
4,5 R 4/13
Strong red
TCS10
5 Y 8/10
Strong yellow
TCS11
4,5 G 5/8
Strong green
TCS12
3 PB 3/11
Strong blue
TCS13
5 YR 8/4
Light yellowish
pink
TCS14
5 GY 4/4
Moderate olive
green
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Swatch
30
XYZ colour space, CIE 1931
90
80
R (%)
70
60
50
X= 57,9
40
Y =51,3
Z= 31,1
30
20
400
450
500
550
600
650
700
λ (nm)
A tristimulus specification of the
objective colour of an object is derived
by weighting the light power spectrum
(reflected by an object) by the three
sensitivity curves (colour matching
curves) corresponding to the three
cones types.
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Full-spectrum light sources and
and color perception
•
•
•
•
Color in the human perception is constructed from the combination of the spectral
power distribution (SPD) of the light source, the spectral reflectance of the
materials being illuminated, and the tri-chromatic nature of the human visual
system.
Full-spectrum light sources certainly provide excellent color rendering. Color
rendering index (CRI) values for full-spectrum lighting sources are typically greater
than 90.
If there are gaps or large variations in the SPD of a light source, there is a potential
for failure in the perception of the apparent colors of objects.
In the contrary, full-spectrum light sources provide radiant power throughout the
visible spectrum, therefore subtle differences in the spectral reflectance
characteristics of different objects are discernible. So, when color identification is
part of the visual task, such as for graphic arts, museums and color printing
applications, full-spectrum light sources will ensure good color discrimination.
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LER (efficiency) vs. CRI (colour quality)
•
•
There is an effort in the spectral design of the SDP of LEDs to
optimise both.
However there is a fundamental trade-off relation between CRI
and (LER): improvements in one are generally detrimental to the
other. Therefore there is always a compromise….
LER
CRI (quality of light)
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LER vs. CRI, a compromise…
LER becomes high, when there is a good correlation between SPD and V(λ)
Photopic Luminous Efficacy V(λ)
Luminous Efficacy
1,0
0,8
0,6
0,4
0,2
0,0
400
500
600
700
λ (nm)
CRI becomes high, when there is a good correlation between SPD and x(λ), y(λ), z(λ)
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Chromatic adaptation
Chromatic adaptation is the ability of the human visual system to discount the colour
of the illumination.
Chromatic adaptation is based
on the adaptation property of
the receptors – they become
less reactive - in constant
stimulus of the same
wavelength of light.
Thanks to a mechanism of
independent sensitivity
regulation of the three
cone responses.
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Quality vs. energy cost
2,5
• When we increase the number
of LEDs in the spectral design of
a LED white source, we may
increase the CRI.
• Studies have shown that
trichromatic and tetrachromatic
white-light LED lamps achieve a
great balance between CRI and
LER.
• However, a key element
associated with the success of
LEDs into the solid-state lighting
market is LER, and this
parameter is reduced when
increasing LEDs quantity.
Ph-LED YAG
------ 3-LED (455/547/623) gamut expanded
------ 4-LED (461/526/576/624) max Ra
2,0
SPD
1,5
1,0
0,5
0,0
400
500
600
700
λ(nm)
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CRI: Colour Rendering Index
• CRI advantages:
– Universal, widely used, easy and rational method (it served
the lighting community successfully for almost 50 years
(introduced in 1965))
• CRI limitations
– The score refers to the average score on specific 8 or 14 or
10 samples,
– It is designed for light sources of broad band (continuous)
spectrum
– ‘‘White’’ sources composed of multiple narrowband LED
spectra have illustrated more clearly the limits of CRI for
characterizing the color rendering properties of electric
light sources.
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Color Rendering vs. Color Quality
http://www.iald.org/userfiles/file/PDFs/DOESSLMaterials/09_NIST%20Color%20Quality%20Index.pdf
• Colour rendering is actually defined as the “effect of
an illuminant on the colour appearance of objects by
conscious or subconscious comparison with their
color appearance under a reference illuminant”.
• Colour rendering often refers only to colour fidelity,
the accurate representation of object colours
compared to those same objects under a reference
source, and does not include other aspects of colour
quality, such as chromatic discrimination and colour
preference.
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Colour quality of white light sources
• Colour fidelity is only one aspect of the quality of white light.
• Other important aspects and dimensions are:
– Visual clarity (Feeling of Contrast Index (FCI))
• the feeling of “clearness” or “distinctness” between object colours
– Colour discrimination ability
• Colour Discrimination index (CDI)
– Colour preference (increased chroma)
• Colour Preference index (CPI)
– ‘‘Flattery index’’ (FI) to characterize how ‘‘vivid’’ or
‘‘flattering’’ objects, particularly skin, might be rendered by
light sources.
• Colour Saturation - colours appear ‘vivid’ and easily
distinguishable
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CIE Technical Commitees
•
CIE TC1-62 Colour Rendering of White LED Light Sources, established in 2002, concluded
that Ra is not appropriate to rank-order the color-rendering ability of light sources
when LEDs are included, but, the committee did not recommend an alternative
measure.
• CIE TC1-69 Colour Rendition by White Light Sources, established in 2006, was formed
“to investigate new methods for assessing the color rendition properties by white-light
sources used for illumination, including solid-state light sources, with the goal of
recommending new assessment procedures.” At the CIE September 2012 meeting in
Taipei, TC1-69 agreed to produce a technical report based on work to date, after which
it will close. It is anticipated that the draft report will not make a single
recommendation.
Two new TCs will continue where TC1-69 left off.
• TC1-90 Colour Fidelity Index was established “to evaluate available indices based on
colour fidelity for assessing the colour quality of white-light sources with a goal of
recommending a single colour fidelity index for industrial use”.
• TC1-91 New Method for Evaluating the Colour Quality of White-Light Sources was
established “to evaluate available new methods for evaluating the colour quality of
white-light sources with a goal of recommending new methods for industrial use.
• Both committees have been given four years to perform their work.
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Colour Quality Scale (CQS)
A Colour Quality Scale (CQS) is being developed at NIST, which is
adequate for evaluating and communicating several aspects of the
quality of a light source illuminating colourful objects. This metric
involves several facets of color quality, including color rendering,
chromatic discrimination, and observer preferences.
•
•
Davis, W. & Ohno, Y., “Color Quality Scale,” Optical Engineering, Optical Engineering 033602-1 March
2010/Vol. 49_3 (2010)
http://colorqualityscale.com/ (Wendy Davis, Yoshi Ohno, and the general Lighting Community.)
•
Davis, W. and Ohno, Y., Development of a Color Quality Scale, National Institute of Standards and Technology,
http://physics.nist.gov/Divisions/Div844/facilities/vision/color.html
•
Rupak Raj Baniya, Study of various metrics evaluating color quality of light sources, Master of Science Thesis,
Aalto University, Department of Electronics Lighting Unit Science, http://lib.tkk.fi/Dipl/2012/urn100575.pdf
http://physlab2.nist.gov/Divisions/Div844/facilities/photo/Publications/DavisOhnoSPIE2005.pdf
Davis, W. and Ohno, Y.. "Toward an improved color rendering metric". Proc. of SPIE 5941, 59411G-1.
•
•
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Colour Quality Scale (CQS)
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Colour Quality Scale (CQS) vs CRI
Saturation factor
•
•
•
The CRI penalizes lamps for shifts in hue, chroma (chromatic saturation), and
lightness, in any direction.
While a decrease in chroma always has negative effects, an increase in the chroma of
objects is considered desirable in many cases. Increases in chroma yield better visual
clarity and enhance perceived brightness. These are positive effects and are
generally preferred, though they cause deviations in color fidelity (compared to
reference).
In the CQS, lamps are not penalized for increasing object chroma relative to the
reference source, though their scores are also not increased. The net result is that a
lamp’s score is only penalized for hue shifts, lightness shifts, and reductions in
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chroma.
44
Gamut Area Scale GAI (Qg)
Gamut area of light source is defined as the area of polygon
defined by the chromaticities of the eight CIE standard color
sample (same used in CIE CRI) in CIE 1976 L*a*b* color space
when illuminated by the light source under examination.
• GAI is based on the idea that an increase in the chroma of
coloured objects has a positive impact on the perceived color
quality.
• When gamut area of light source is larger, objects’ colour will
appear more saturated under the light source.
• GAI is more sensitive to saturation and hue discriminability
than to colour fidelity.
•
•
Mark S. Rea, Jean P. Freyssinier-Nova, 2008. Color Rendering: A Tale of Two Metrics, COLOR research and
application, p. 192-202.
Mark S. Rea, Jean P. Freyssinier-Nova, 2010. Color Rendering: Beyond Pride and Prejudice, COLOR research
and application, p. 401-409.
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Gamut Area Scale GAI (Qg)
[Sandor, 2006]
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Gamut Area Scale GAI (Qg)
• Rea and Freyssinier (Lighting Research Center, Rensselaer PI) demonstrated
that gamut area index (GAI) was much better than CRI as a predictor of
color discrimination.
• Rea and Freyssinier also showed that GAI and CRI were sometimes
negatively correlated with each other (CRI- high, GAI – low score); one
metric would be positively related to subjective judgments of ‘‘vividness’’
and of ‘‘naturalness’’ while the other would be negatively.
• A Two-metric system (CRI and GAI) of colour rendering is proposed for
general illumination applications.
• As colour rendering index (CRI) and of gamut area index (GAI) seem to
counteract the weaknesses of one another, together they can be used in
choosing a source that will provide good color rendering of most objects in
most applications.
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Towards a new two-measure
system for characterizing color rendition assessment
of the colour quality of white light sources
One measure that is consistent with the concept of color
fidelity or quality and the other is a measure of relative gamut.
Review of 22 colour rendition indexes, based on the
calculation of the indexes for 401 illuminants (SPD) of
various types.
• Kevin W. Houser, Minchen Wei, Aurélien David, Michael R. Krames, and
Xiangyou Sharon Shen, Review of measures for light-source color
rendition and considerations for a two-measure system for
characterizing color rendition, Optics Express, 21(8), pp. 10393-10411
(2013)
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Review of 22 colour rendition indexes
All 22 idexes are clustered into 3 groups:
“fidelity-based” F measures (like Ra)
“preference-based” P measures (like CPI)
“gamut-based” (discrimination) D
measures, like CDI or GAI)
P and D are also related to
the feeling of contrast
Kevin et al, 2013
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Review of 22 colour rendition indexes
Kevin et al, 2013
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Review of 22 colour rendition indexes
For different CCTs
Colour Fidelity (Ra) vs. Gammut Area (GAI)
High CCT is not associated with
high preference, but,
CCT is moderately correlated with the
gamut-based measures: gamut tends to
increase with CCT for CIE reference
illuminants.
GAI is favoured by higher CCTs
because gamut area increases with CCT.
The plot illustrates also that higher CCT
light sources are strongly favoured in
simultaneously achieving high values of
both Ra and GAI.
However, lower CCT light sources can have
excellent color qualities, including
excellent color-discrimination
performance despite having a smaller
gamut.
But a measure of color rendition should
Sophia Sotiropoulou, HOU
not to be correlated with CCT.
Kevin et al, 2013
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Review of 22 colour rendition indexes
The role of illuminance.
The magnitude of illuminance strongly
affects the appearance of colored objects.
Perceived hues are dependent upon
illuminance (Bezold-Brucke effect), colors
appear more saturated (colourful) under
higher illuminance (Hunt effect), and
color discrimination performance
is dependent upon illuminance level.
If an electric light source increases object
saturation relative to a reference
illuminant at a typical indoor illuminance
level, then the object may appear more
like it would under daylight (high
illuminance) at a typical outdoor daytime
illuminance level.
Nevertheless, a colour rendition system
should be independent of the illuminance
level.
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Bezold-Brucke effect
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Review of 22 colour rendition indexes
Conclusions
One number (e.g. CRI) cannot fully
encapsulate the multidimensional problem
of color rendition. However, the lighting
industry needs a simple and readily
interpretable tool for communicating color
quality.
A two-measures system:
one reference-based (fidelity) measure
and one gamut-based measure
A set of saturated reference colours
Kevin et al, 2013
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Conclusions
• Although CRI remains the only one CIE established and universally used
index for assessing Colour rendering of artificial white light sources, there
is a significant progress in the metrics of colour rendition quality taking
into account physiological mechanisms, psychological factors and cognitive
functions involved in the perception of colour.
• Waiting the results of the CIE – TCs, towards a two-measures system: one
reference-based (fidelity) measure and one gamut-based measure
• Emerging technologies and SSL in particular, provide with technological
solutions to shape the Specral Power Distribution (SPD) – thus optimise
the quality of light in function to applications in performing specific visual
tasks, as well as more generally in commercial, architectural, and
entertainment lighting.
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Bibliography - webresources
•
•
Colour vision - colour perception
– Livingstone, M., Hubel, D. (2002) Vision and Art : The Biology of Seeing, Harry N Abrams
– Palmer, S. (1999) Vision Science: Photons to Phenomenology Cambridge, MA: The MIT
Press.
– Web Exhibits,
• Causes of colour: http://www.webexhibits.org/causesofcolor/1B.html
• Colour vision and art: http://www.webexhibits.org/colorart/
http://www.handprint.com/LS/CVS/color.html
Colour rendering assessment of white light sources
• http://www.nist.gov/pml/div685/grp03/vision_color.cfm
• Lighting Research Center, Rensselaer Polytechnic Institute, Troy, NY USA
http://www.lrc.rpi.edu/programs/solidstate/colorResearch.asp /
http://www.lrc.rpi.edu/programs/nlpip/lightinganswers/fullspectrum/lightSources.asp
• Guo, Xin; Houser, Kevin W. (2004), "A review of colour rendering indices and their
application to commercial light sources", Lighting Research and Technology 36 (3): 183–
199
• Kevin W. Houser, Minchen Wei, Aurélien David, Michael R. Krames, and Xiangyou Sharon
Shen, (2013) “Review of measures for light-source color rendition and considerations for a
two-measure system for characterizing color rendition”, Optics Express, 21(8): 1039310411
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