Evaluating Light Source Color Rendition using IES TM-30-15...Sep 07, 2016 · TCS 01 TCS 02 TCS 03...

Evaluating Light Source Color

Rendition using IES TM-30-15

Kevin W. Houser, PhD, PE, FIES, LCProfessor of Architectural Engineering Editor-in-Chief

The Pennsylvania State University LEUKOS, the journal of IES

[email protected] [email protected]

Which do you prefer?

Ra (CRI)= 50

R9 = -80

CCT = 3501 K

Duv = 0.0000

Ra (CRI)= 75

R9 = 20

CCT = 3501 K

Duv = 0.0000

1 2

Today’s Outline

Brief overview of CIE CRI

Introduction to TM-30-15 IES Method for

Evaluating Light Source Color Rendition

Demonstration

Resources

CIE CRI (Ra)

SAME CCT

Test SourceReference Illuminant

(approximately)

For further reading see CIE 13.3-1995, or Houser K, Mossman M, Smet K, Whitehead L. 2015. Tutorial: Color Rendering and Its Applications in Lighting. LEUKOS. http://dx.doi.org/10.1080/15502724.2014.989802

http://dx.doi.org/10.1080/15502724.2014.989802

CIE CRI (Ra)

TCS 01 TCS 02 TCS 03 TCS 04


Approximation of Color Samples for Ra


TCS 13 TCS 14

Color Samples for R9–R14

CIE CRI (Ra)

(Illustration Only)

R Y GY G BG PB P RP

U*

V*

-10

-20

+20

+10

-10-20 +20+10+30 +30

GY

BG

Y

PB

R

RP

P

G

CIE Method for Color Rendering

Color Fidelity

CIE CRI (Ra)

The accurate rendition of

color so that they appear as

they would under familiar

(reference) illuminants

Original Image courtesy of Randy Burkett Lighting Design

CRI = 95, Original Image


CRI = 80, Desaturated Image


CRI = 80, Saturated Image (Red Enhanced)

“Original” Baseline

Original image courtesy of Randy

Burkett Lighting Design

“CRI = 80” - Hue Shift

“CRI = 80” + Hue Shift

“CRI = 80” Saturated

“CRI = 80” Desaturated

Limitations of Considering Only Fidelity

Perfect Fidelity

Increase

Saturation

Decrease

Saturation

Positive Hue Shift

Negative Hue Shift

CRI = 80 CRI = 80

Constant CIE CRI

Perfect Fidelity

Increase

Saturation

Decrease

Saturation

Positive Hue Shift

Negative Hue Shift

CRI = 80 CRI = 80

Constant CRI

One measure is not enough!

Limitations of Considering Only Fidelity

Today’s Outline




Demonstration

Resources

Two primary motivations for developing the

IES Method:

1. The need for an improved measure of color

fidelity

2. The need to provide supplementary informationabout color rendering ability of any given light source

Fidelity Index (Rf)

Gamut Index (Rg)

High Level Average Values

Core Calculation Engine

Modern Color Science

New Color Samples

Color Vector Graphic

Color Distortion Graphic

Graphical Representations

Skin Fidelity (Rf,skin)

Fidelity by Hue (Rf#)

Chroma Shift by Hue (Rc#)

Fidelity by Sample (Rf,CES#)

Detailed Values

IES Method for Color Rendition

Color Fidelity

Fidelity Index (Rf)

IES Method for Color Rendition

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

Graphics

Visual description of

hue and saturation

changes.


• Quantifies average similarity in appearance of test and reference sources

• Analogous to CIE Ra, but more accurate

• Scores of 0 to 100• Scale similar to CIE Ra, but high scores

harder to achieve• Equal weight to all directions of shift• Should not be expected to correlate

with any single object color

Fidelity Index: Rf

[Flattened to 2D]

-40

-30

-20

-10

0

10

20

30

40

-40 -30 -20 -10 0 10 20 30 40

b'

a' Reference Source Test Source

-40

-30

-20

-10

0

10

20

30

40

-40 -30 -20 -10 0 10 20 30 40

b'

a' Reference Source Test Source

1

2

16

15

8

7

9

10

3456

14131211-40

-30

-20

-10

0

10

20

30

40

-40 -30 -20 -10 0 10 20 30 40b

'a'

Reference Source Test Source

1

2

16

15

8

7

9

10

3456

14131211

Relative Gamut Index: Rg

-40

-30

-20

-10

0

10

20

30

40

-40 -30 -20 -10 0 10 20 30 40b

'a'


1

2

16

15

8

7

9

10

3456

14131211

𝑅𝑔 = 100 ×𝐴𝑡𝐴𝑟

Rg > 100: Average increase in saturation

Rg < 100: Average decrease in saturation

Relative Gamut Index: Rg

Original Desaturated Red-Enhanced

CRI = 95 CRI = 80 CRI = 80

Theoretical Example

Rf = 93 Rf = 78 Rf = 78

Rg = 100 Rg = 90 Rg = 110



CRI = 95 CRI = 80 CRI = 80

Theoretical Example

Rf = 93 Rf = 78 Rf = 78

Rg = 100 Rg = 90 Rg = 110

Image courtesy of Randy Burkett Lighting Design

Average values can hide

important information!

This is limitation of CIE Ra,

and IES Rf and Rg

380 430 480 530 580 630 680 730 780

Rf = 81Rg = 101CCT = 2496 KRa = 88

(Source No. 286)

“Gamut” is not a dimension of perception. It is best interpreted with reference to a complementary graphic.



COLOR VECTOR GRAPHIC

-40

-30

-20

-10

0

10

20

30

40

-40 -30 -20 -10 0 10 20 30 40b

'a'


CES CHROMATICITY COMPARISON

1

2

16

15

8

7

9

10

3456

14131211


-40

-30

-20

-10

0

10

20

30

40

-40 -30 -20 -10 0 10 20 30 40b

'a'



1

2

16

15

8

7

9

10

3456

14131211


-40

-30

-20

-10

0

10

20

30

40

-40 -30 -20 -10 0 10 20 30 40b

'a'



1

2

16

15

8

7

9

10

3456

14131211

Decreased Saturation

Hue Shift

IncreasedSaturation



Theoretical Example


CRI = 95 CRI = 80 CRI = 80

Rf = 93 Rf = 78 Rf = 78

Rg = 100 Rg = 90 Rg = 110


Today’s Outline




Demonstration

Resources

32 versus 3Comparable

CIE Ra and R9

55 versus 4

Case 4 is eleven

points higher in

CRI (83 vs. 72)

65 versus 6

Case 6 is eight

points higher in

CRI (80 vs. 72)

Today’s Outline




Demonstration

Resources

IES Technical Memorandum (TM) 30-15 (Includes Excel Calculators):

IES Method for Evaluating Light Source Color Rendition

http://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 sources

http://bit.ly/1J32ftZ

LEUKOS 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

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

Lighting Research and Technology article showing applicability of TM-30-15 to human perceptions:

Royer MP, Wilkerson A, Wei M, Houser K, Davis R. 2016. Human perceptions of colour rendition vary with

average fidelity, average gamut, and gamut shape. Online before print

http://dx.doi.org/10.1177/1477153516663615

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 Rendition

http://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 Metrics

http://1.usa.gov/1Mn15LG

DOE Fact Sheet on TM-30

http://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

IES

Journals

US DOE

http://bit.ly/1IWZxVuhttp://bit.ly/1J32ftZhttp://dx.doi.org/10.1080/15502724.2015.1091356http://dx.doi.org/10.1177/1477153515617392http://dx.doi.org/10.1177/1477153516663615http://1.usa.gov/1YEkbBZhttp://1.usa.gov/1Mn15LGhttp://energy.gov/eere/ssl/downloads/evaluating-color-rendition-using-ies-tm-30-15http://energy.gov/eere/ssl/tm-30-frequently-asked-questions

46

These slides are available to download:

http://www.personal.psu.edu/kwh101/LysetsDag2016/main.htm

Or

http://bit.ly/2cq0NG4

http://www.personal.psu.edu/kwh101/LysetsDag2016/main.htmhttp://bit.ly/2cq0NG4

Bonus Slides

Human Judgements of Color Rendition Vary with Average Fidelity, Average Gamut, and Gamut ShapeLighting Research & Technology: http://dx.doi.org/10.1177/1477153516663615

Michael Royer, Pacific Northwest National LaboratoryAndrea Wilkerson, Pacific Northwest National LaboratoryMinchen Wei, Hong Kong Polytechnic UniversityKevin Houser, Penn State UniversityRobert Davis, Pacific Northwest National Laboratory

Funding• Royer, Wilkerson, and Davis supported by U.S. Department of Energy Laboratory

Directed Research and Development (LDRD) award• Houser subcontracted by Pacific Northwest National Laboratory.• Wei supported by Penn State, with later stages supported by Hong Kong

Polytechnic.

Goals Hypotheses Methods ConclusionsDiscussionResults

http://dx.doi.org/10.1177/1477153516663615

a priori hypotheses

1. As Rf increases, color would be

judged as more normal.

2. As Rg increases, color would be

judged as more saturated.

3. Higher levels of Rg would be

more preferred than lower levels

of Rg.

4. Higher levels of red saturation

would be preferred.


Apparatus and Test Space


Independent Variables: Rf, Rg, and Gamut Shape

26

10

2

2

4

6

8

10

12

14

16

18

20

22

23

26

70

80

90

100

110

120

130

60 70 80 90 100

Rf

Rg


2

4

6

8

10

12

14

16

18

20

22

23

26

70

80

90

100

110

120

130

60 70 80 90 100

19

1

3

5

7

9

11

13

15

17

21

24

25

Rf

Rg



13

14

14

70

80

90

100

110

120

130

60 70 80 90 100

13

Rf

Rg



70

80

90

100

110

120

130

60 70 80 90 100

IES

TM-3

0 R

g

IES TM-30 Rf

1

2 3


Preference varied systematically.Higher levels of Rg were generally preferred to lower levels of Rg.

a priori hypotheses

3. Higher levels of Rg

would be more

preferred than lower

levels of Rg.

4. Higher levels of red

saturation would be

preferred.

Dislike

Like

5.5

5.0

4.5

4.0

1 2 3

(These aren’t necessarily the most preferred sources possible, just the most preferred sources from this experiment).


Preference varied systematically.Higher levels red saturation were preferred.

70

80

90

100

110

120

130

60 70 80 90 100

IES

TM-3

0 R

g

IES TM-30 Rf


Same fidelity and gamut, but different gamut shape, can

lead to significantly different preference.

Dislike

Like

5.5

5.0

4.5

4.0


Same fidelity and gamut, but different gamut shape, can

lead to significantly different preference.

y = 85.457x3 + 12.746x2 - 9.6207x + 4.1387R² = 0.8132

1

2

3

4

5

6

7

8

-30% -20% -10% 0% 10% 20% 30%

Me

an P

refe

ren

ce R

atin

g

Hue Bin 16 Chroma Shift (Rcs,h16)

Dislike

Like


Preference increased with red-saturation, with limits.


Best Model for Preference:

Like-Dislike = 7.396 - 0.0408(Rf) + 103.4(Rcs,h163) - 9.949(Rcs,h16)

R² = 0.93552

3

4

5

6

7

2 3 4 5 6 7

Par

tici

pan

t P

refe

ren

ce R

atin

g

TM-30 Model Predicted Preference Rating

More Liked

Less Liked

Post-hoc modeling of preference


-50%

-40%

-30%

-20%

-10%

0%

10%

20%

30%

40%

50%

Rcs

,h1

6

Experimental Preferred Zone*

What about existing light sources?


60

70

80

90

100

110

120

130

140

50 60 70 80 90 100

IES

TM-3

0 R

g

IES TM-30 Rf

Phosphor LED

Color Mixed LED

Hybrid LED

Standard Halogen

Filtered Halogen

Triphosphor Fluorescent, 7XX



Metal Halide

Experimental

Preferred

Zone*

What about existing light sources?


• TM-30 measures demonstrated excellent correlation with participant evaluations

• Sources that increased saturation in red were liked(Chroma shift in “red” of about 2% to 16%)

• Today’s commercially available sources are unlikely to be optimized for preference

Conclusions from this small study

Evaluating Light Source Color Rendition using IES TM-30-15...Sep 07, 2016 · TCS 01 TCS 02 TCS 03...

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