ies tm30-15 introduction and latest updates
TRANSCRIPT
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TM-30: Introduction and Latest DevelopmentsMichael Royer, PhD | Pacific Northwest National Laboratory
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Credit(s) earned on completion of this course will be reported to AIA CES for AIA members. Certificates of Completion for both AIA members and non-AIA members are available upon request.
This course is registered with AIA CES for continuing professional education. As such, it does not include
content that may be deemed or construed to be an approval or endorsement by the AIA of any material of construction or any method or manner ofhandling, using, distributing, or dealing in any material or product.
___________________________________________
Questions related to specific materials, methods, and services will be addressed at the conclusion of this presentation.
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TM-30 was developed, through a consensus process, to provide a comprehensive set of objective information—going beyond simple average values—that can be used collectively to make informed decisions about subjective perceptions, such as preference or naturalness, given a context. New research has shown the value of this robust system in capturing human judgements of lighting quality. Nonetheless, TM-30 is a tool, not an answer. Its limitations must be understand, and it must be combined with other color information, such as chromaticity, luminance, and distribution of light, when choosing a source.
Abstract:
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Summarize the process that led to the recommendation by the IES Color Metrics Task Group
Describe the components of the color rendition evaluation system and how they can be interpreted to aid design and specification
Comprehend the conceptual framework for the underlying calculations
Recognize the limitations of the this system, and more generally recognize the limitations of all measures for color rendition
Understand how the objective information in TM-30 can be used to aid in subjective design decisions (i.e., matching the right source to an application).
Learning Objectives:
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Ra (CRI) = 78R9 = -11
Ra (CRI) = 68R9 = -37
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Ra (CRI) = 78R9 = -11
Ra (CRI) = 68R9 = -37
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Fidelity Index (Rf)Gamut Index (Rg)
High Level Average Values
Core Calculation EngineModern Color ScienceNew Color Samples
Color Vector GraphicColor Distortion Graphic
Graphical Representations
Skin Fidelity (Rf,skin)
Fidelity by Hue (Rf,h#)
Chroma Shift by Hue (Rcs,h#)
Fidelity by Sample (Rf,CES#)
Detailed Values
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Color Fidelity
Fidelity Index (Rf)
TM-30 Method for Evaluating Color Rendition
The accurate rendition of color so that they appear as they would under familiar (reference) illuminants
(0-100)
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Perfect Fidelity
Increase Saturation
DecreaseSaturation
Positive Hue Shift
Negative Hue Shift
CRI = 80 CRI = 80
Constant Fidelity (CRI)
(Also possible to change lightness, not shown)
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Color Fidelity
Fidelity Index (Rf)
TM-30 Method for Evaluating Color Rendition
The accurate rendition of color so that they appear as they would under familiar (reference) illuminants
(0-100)
Color Gamut
The average level of saturation relative to familiar (reference) illuminants.
Gamut Index (Rg)~60-140 when Rf > 60
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50 60 70 80 90 10060
70
80
90
100
110
120
130
140
Fidelity Index, Rf
Gam
ut In
dex,
Rg
Combinations not
possible for white light.
Reduced Fidelity
Incr
ease
d Sa
tura
tion
Decr
ease
d Sa
tura
tion Reference
IlluminantTwo-
Axis
Syst
em • Evaluate tradeoffs between fidelity and saturation.
• Cohesive system from the same calculation engine.
• But average values don’t tell the whole story…
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Color Fidelity
Fidelity Index (Rf)
The accurate rendition of color so that they appear as they would under familiar (reference) illuminants
Color Gamut
The average level of saturation relative to familiar (reference) illuminants.
Gamut Index (Rg)
(0-100)~60-140 when Rf > 60
Gamut Shape
Changes over different hues
Color Vector Graphic
TM-30 Method for Evaluating Color Rendition
Hue Bin FidelityHue Bin Chroma Shift
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Rf = 75 | Rg = 100 | CCT = 3500 K Rf = 75 | Rg = 100 | CCT = 3500 K
Decreased Saturation
IncreasedSaturation
Hue Shift
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15
0
20
40
60
80
100
76 7264
7485 82
75 72 7568 72 71
83 87 84 81
Fide
lity
Inde
x by
Hue
, Rcs
,hj
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16-40%-30%-20%-10%
0%10%20%30%40%
12% 11%5%
-3% -6%
3%10%
16% 14%10%
4%
-1% -4% -5%
2%9%
Chro
ma
Chan
ge b
y Hu
e, R
cs,h
j
0
20
40
60
80
100
74 7363
7280 80 79
85 8374 70 72
83 78 74 73
Fide
lity
Inde
x by
Hue
, Rcs
,hj
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16-40%-30%-20%-10%
0%10%20%30%40%
-14%-11%-3%
5%11% 11%
4%
-2%-8%
-13%
-3%
7% 9% 11%2%
-5%
Chro
ma
Chan
ge b
y Hu
e, R
cs,h
j
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Sum
mar
y of
Upg
rade
sCRI Calculation Engine (1974) TM-30 Calculation Engine (2015)
CIE 1964 U*V*W* CAM02-UCS (CIECAM02)
Von Kries CAT CIE CAT02
8 color samples 99 color samplesMedium chroma/lightnessSpectral sensitivity varies
Uniform color space coverageSpectral sensitivity neutralVariety of real objectsMunsell samples only
Technical Improvement
Ref Illuminant Step Function Ref Illuminant Continuous(Uses same reference sources, but blended between 4500 K and 5500 K)
No lower limit for scores 0 to 100 scale (fidelity)
Nice to Have
Fidelity Only Fidelity, Gamut, Graphical, Hues Philosophical Change
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70 75 80 85 90 95 10070
75
80
85
90
95
100
CIE Ra (CRI)
TM-3
0 R
f
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70 75 80 85 90 95 10070
75
80
85
90
95
100R² = 0
CIE Ra (CRI)
TM-3
0 R
f
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~16 point spread in Rf scores at Ra = ~80
70 75 80 85 90 95 10070
75
80
85
90
95
100 FilamentDaylight ModelsNarrowband Fluo-rescentBroadband FluorescentHIDHybrid LED
CIE Ra (CRI)
TM-3
0 R
f
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49 point spread (error) in fidelity score at CRI of 80.
50 60 70 80 90 10040
50
60
70
80
90
100
CIE Ra
TM-3
0 Rf
5,000 Real and Modelled* SPDs*All modelled SPDs composed of combinations of Gaussian primaries; chromaticity on Planckian locus between 2700 K and 7000 K
For more information:Smet KAG, David A, Whitehead L. 2015. Why color space uniformity and sample set spectral uniformity are essential for color rendering measures. Leukos 12(1–2):39–50.
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0 20 40 60 80 10060
70
80
90
100
110
120
130
140
CIE Ra
TM-3
0 Rg
0 20 40 60 80 10060
70
80
90
100
110
120
130
140
TM-30 Rf
TM-3
0 Rg
Is the error systematic?
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Illuminance: ~20 fcCCT: 3500 KLighting Conditions: 26Objects: Generic Consumer, balanced huesApplication: UndefinedParticipants (28): 18-65, 16 females 12 malesRating Questions: Normal-Shifted, Saturated-Dull, Like-Dislike
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60 65 70 75 80 85 90 95 10070
80
90
100
110
120
130
TM-30 Fidelity Index, Rf
TM-3
0 Ga
mut
Inde
x, R
g
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60 65 70 75 80 85 90 95 10070
80
90
100
110
120
130
TM-30 Fidelity Index, Rf
TM-3
0 Ga
mut
Inde
x, R
g
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60 65 70 75 80 85 90 95 10070
80
90
100
110
120
130
TM-30 Fidelity Index, Rf
TM-3
0 Ga
mut
Inde
x, R
g
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60 65 70 75 80 85 90 95 10070
80
90
100
110
120
130
TM-30 Fidelity Index, Rf
TM-3
0 Ga
mut
Inde
x, R
g
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60 65 70 75 80 85 90 95 10070
80
90
100
110
120
130
TM-30 Fidelity Index, Rf
TM-3
0 Ga
mut
Inde
x, R
g
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60 65 70 75 80 85 90 95 10070
80
90
100
110
120
130
TM-30 Fidelity Index, Rf
TM-3
0 Ga
mut
Inde
x, R
g
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60 65 70 75 80 85 90 95 10070
80
90
100
110
120
130
TM-30 Fidelity Index, Rf
TM-3
0 Ga
mut
Inde
x, R
g
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17 22 26 15 16 23 6 24 18 9 8 7 25 14 10 12 5 20 4 21 13 11 3 19 1 20
102030405060708090
100
Setting ID in Rank Order
Fide
lity
Inde
x Rf
Most Liked Least Liked
Fidelity and Preference?
R2 = 0.06
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1 2 3
(These aren’t necessarily the most preferred sources possible, just the most preferred sources from this experiment).
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60 70 80 90 10070
80
90
100
110
120
130
IES TM-30 Rf
IES
TM-3
0 Rg
Model r2 = 0.68
p =
0.00
0
p = 0.042
Dislike
Like
5.5
5.0
4.5
4.0
3.5
Fidelity + Gamut and Preference?
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Same Fidelity, Same Gamut, Significantly Different Rating.
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-30% -20% -10% 0% 10% 20% 30%1
2
3
4
5
6
7
8
f(x) = 85.457325247 x³ + 12.74591052 x² − 9.620714244 x + 4.1387295218R² = 0.813215625190091
Hue Bin 16 Chroma Shift (Rg,h16)
Mea
n Pr
efer
ence
Rati
ng
Dislike
Like
Red Chroma Shift and Preference?
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Best Fit Model for Preference: Like-Dislike = 7.396 - 0.0408(Rf) + 103.4(Rcs,h163) - 9.949(Rcs,h16)
2 2.5 3 3.5 4 4.5 5 5.5 6 6.5 72.02.53.03.54.04.55.05.56.06.57.0
R² = 0.935547960432472
TM-30 Model Predicted Rating
Parti
cipa
nt R
ating
(Pre
fere
nce)
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Normalness = Fidelity + Red Fidelity/Saturation
Saturation = Red Saturation
Preference = Fidelity + Red Saturation
Rf > 80 Rf,h1 > 80 0% < Rcs,h1 < 8%
Maximize Rcs,h16, Rcs,h1
Rf > 74 0% < Rcs,h16 < 15% 0% < Rcs,h1 < 15%
(Rg > 100)
Context =
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50 60 70 80 90 10060
70
80
90
100
110
120
130
140Phosphor LED
Color Mixed LED
Hybrid LED
Standard Halogen
Filtered Halogen
Triphosphor Fluorescent, 7XX
Triphosphor Fluorescent, 8XX
Triphosphor Fluorescent, 9XX
Metal Halide
Fidelity Index, Rf
Gam
ut In
dex,
Rg
Experimental Preferred Zone*
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-50%
-40%
-30%
-20%
-10%
0%
10%
20%
30%
40%
50%
Rcs,h
16
Experimental Preferred Zone*
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Same Fidelity, Same Gamut, Significantly Different Rating.LER = 343 LER = 311
Why so few red-enhancing sources?
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CIE R a
IES
TM-3
0 R f
Why so few red-enhancing sources?M
odel
r2 = 0
.06
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Common Commercially Available Sources (Developed for Ra):
Ra 74, LER 348 Ra 85, LER 343 Ra 83, LER 309
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Ra 80, LER 272
“Enhanced” Sources:
Ra 77, LER 136 Ra 87, LER 295
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Context…
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Und
erst
andi
ng T
he To
ol1. A metric value doesn’t tell you how the product will perform in any
given environment.
2. The “accuracy”/applicability of the metric depends on if the sample set is similar to the actual space.
3. An average color rendering metric shouldn’t be used to predict how a source will render reds, or skin tones, or any specific set of objects.
4. TM-30 offers substantially more information, which is essential for evaluating color rendering characteristics.
5. The best source is depends on the context (objects, type of space/application, illuminance, occupants, etc.)
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Reso
urce
sIES Technical Memorandum (TM) 30-15 (Includes Excel Calculators):IES Method for Evaluating Light Source Color Renditionhttp://bit.ly/1IWZxVu
Optics Express journal article that provides overview of the IES method:Development of the IES method for evaluating the color rendition of light sourceshttp://bit.ly/1J32ftZ
Application webinar co-sponsored by US Department of Energy and Illuminating Engineering Society:Understanding and Applying TM-30-15: IES Method for Evaluating Light Source Color Renditionhttp://1.usa.gov/1YEkbBZ
Technical webinar co-sponsored by US Department of Energy and Illuminating Engineering Society:A Technical Discussion of TM-30-15: Why and How it Advances Color Rendition Metricshttp://1.usa.gov/1Mn15LG
LEUKOS journal article supporting TM-30’s technical foundations:Smet KAG, David A, Whitehead L. 2015. Why Color Space and Spectral Uniformity Are Essential for Color Rendering Measures. LEUKOS. 12(1,2):39-50.http://dx.doi.org/10.1080/15502724.2015.1091356
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sLEUKOS editorial discussing next steps:Royer MP. 2015. IES TM-30-15 Is Approved—Now What? Moving Forward with New Color Rendition Measures. LEUKOS. 12(1,2):3-5.http://dx.doi.org/10.1080/15502724.2015.1092752
Lighting Research and Technology, Open Letter:Correspondence: In support of the IES method of evaluating light source colour rendition (More than 30 authors) http://dx.doi.org/10.1177/1477153515617392
DOE Fact Sheet on TM-30http://energy.gov/eere/ssl/downloads/evaluating-color-rendition-using-ies-tm-30-15
DOE TM-30 FAQs Page:http://energy.gov/eere/ssl/tm-30-frequently-asked-questions
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This concludes The American Institute of Architects
Continuing Education Systems Course