Evaluating Light Source Color Rendition using IES TM ... - FC Lighting

Evaluating Light Source Color Rendition using IES TM-30-15

2016 Expo | Pittsburgh, PA October 4 – 5, 2016

Kevin W. Houser, PhD, PE, FIES, LC Professor of Architectural Engineering The Pennsylvania State University

Editor-in-Chief LEUKOS, the journal of IES

[email protected]

[email protected]

Which do you prefer?

1 Ra (CRI) = 50 R9 = -80 CCT = 3501 K Duv = 0.0000

2 Ra (CRI) = 75 R9 = 20 CCT = 3501 K Duv = 0.0000

Today’s Outline  Brief overview of CIE CRI  Introduction to TM-30-15 IES Method for Evaluating Light Source Color Rendition  Demonstration  Results from recent experiment

Today’s Outline  Brief overview of CIE CRI  Introduction to TM-30-15 IES Method for Evaluating Light Source Color Rendition  Demonstration  Results from recent experiment

CIE CRI (Ra) Reference Illuminant

Test Source

(approximately)

SAME CCT

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

CIE CRI (Ra) Approximation of Color Samples for Ra

Color Samples for R9–R14

TCS 01

TCS 02

TCS 03

TCS 04

TCS 09

TCS 10

TCS 05

TCS 06

TCS 07

TCS 08

TCS 13

TCS 14

TCS 11

TCS 12

CIE CRI (Ra) R

Y

GY

G

BG

PB

P

RP

(Illustration Only) GY

+20 +10

Y

G

R

V* -10

BG RP

-20

P

PB

+30

-20

-10

U*

+10

+20

+30

CIE CRI (Ra) R

Y

GY

G

BG

PB

P

RP

(Illustration Only) GY

+20 +10

Y

G

R

V* -10

BG RP

-20

P

PB

+30

-20

-10

U*

+10

+20

+30

CIE Method for Color Rendering Color Fidelity The accurate rendition of color so that they appear as they would under familiar (reference) illuminants

CIE CRI (Ra)

CRI = 95, Original Image

Original Image courtesy of Randy Burkett Lighting Design

CRI = 80, Desaturated Image

Original Image courtesy of Randy Burkett Lighting Design

CRI = 80, Saturated Image (Red Enhanced)

Original Image courtesy of Randy Burkett Lighting Design

“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 Positive Hue Shift

Constant CIE CRI

Decrease Saturation

CRI = 80

CRI = Fidelity 80 Perfect

Negative Hue Shift

Increase Saturation

Limitations of Considering Only Fidelity Positive Hue Shift

Constant CRI

One measure is not enough! Increase

Decrease Saturation

CRI = 80

CRI = Fidelity 80 Perfect

Negative Hue Shift

Saturation

Today’s Outline  Brief overview of CIE CRI  Introduction to TM-30-15 IES Method for Evaluating Light Source Color Rendition  Demonstration  Results from recent experiment

Two primary motivations for developing the IES Method: 1. The need for an improved measure of color

fidelity 2. The need to provide supplementary information about color rendering ability of any given light source

IES Method for Color Rendition High Level Average Values Fidelity Index (Rf) Gamut Index (Rg)

Core Calculation Engine

Modern Color Science New Color Samples

Graphical Representations Color Vector Graphic Color Distortion Graphic Detailed Values Skin Fidelity (Rf,skin) Fidelity by Hue (Rf#) Chroma Shift by Hue (Rc#) Fidelity by Sample (Rf,CES#)

IES Method for Color Rendition Color Fidelity

Color Gamut

Graphics

The accurate rendition of color so that they appear as they would under familiar (reference) illuminants

The average level of saturation relative to familiar (reference) illuminants.

Visual description of hue and saturation changes.

Color Vector Graphic

Gamut Index (Rg) Fidelity Index (Rf) (0-100)

~60-140 when Rf > 60

Fidelity Index: Rf 40 30 20

b'

10

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

0 a' Reference Source

10

20

30

Test Source

[Flattened to 2D]

40

• 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

Relative Gamut Index: Rg 40

6

5

4

40

3

30 2

20

10

10

8

1

0

b'

b'

7

9

16

-20 -30 -40

5

4

3

30

20

-10

6 7

2

8

1

9

16

10

15

0 -10 -20

10

15 11

12

-40 -30 -20 -10

0 a' Reference Source

13 10

14 20

30

Test Source

-30 -40

40

11

12

-40 -30 -20 -10

13

14

0 10 20 30 40 a' Reference Source Test Source

Relative Gamut Index: Rg 40

𝐴𝑡 𝑅𝑔 = 100 × 𝐴𝑟

6

5

4

3

30 7

2

8

1

9

16

10

15

20

Rg > 100: Average increase in saturation b'

Rg < 100: Average decrease in saturation

10

0 -10 -20 -30 -40

11

12

-40 -30 -20 -10

13

14

0 10 20 30 40 a' Reference Source Test Source

Theoretical Example

Original

Desaturated

Red-Enhanced

CRI = 95

CRI = 80

CRI = 80

Rf = 93

Rf = 78

Rf = 78

Rg = 100

Rg = 90

Rg = 110

Original Image courtesy of Randy Burkett Lighting Design

Theoretical Example

Original CRI = 95 Rf = 93

Average values can hide important information! Desaturated

Red-Enhanced

CRI = 80

CRI = 80

This is limitation of CIE Ra, = 78 R and R R = 78 and RIES f g

Rg = 100

f

Rg = 90

f

Rg = 110

Image courtesy of Randy Burkett Lighting Design

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

380 430 480 530 580 630 680 730 780

Rf Rg CCT Ra

= = = =

(Source No. 286)

Color Vector Graphic

81 101 2496 K 88

Color Vector Graphic COLOR VECTOR GRAPHIC

CES CHROMATICITY COMPARISON 6 5 4 3

40 30 7

2

8

1

9

16

10

15

20

b'

10

0 -10 -20 -30 -40

11

12

-40 -30 -20 -10

13

14

0 10 20 30 40 a' Reference Source Test Source

Color Vector Graphic CES CHROMATICITY COMPARISON 6 5 4 3

40 30 7

2

8

1

9

16

10

15

20

b'

10

0 -10 -20 -30 -40

11

12

-40 -30 -20 -10

13

14

0 10 20 30 40 a' Reference Source Test Source

Color Vector Graphic CES CHROMATICITY COMPARISON 6 5 4 3

40 30 7

2

8

1

9

16

10

15

20

b'

10

0 -10 -20 -30 -40

Increased Saturation

Decreased Saturation Hue Shift

11

12

-40 -30 -20 -10

13

14

0 10 20 30 40 a' Reference Source Test Source

Theoretical Example

Original

Desaturated

Red-Enhanced

CRI = 95

CRI = 80

CRI = 80

Rf = 93

Rf = 78

Rf = 78

Rg = 100

Rg = 90

Rg = 110

Original Image courtesy of Randy Burkett Lighting Design

Today’s Outline  Brief overview of CIE CRI  Introduction to TM-30-15 IES Method for Evaluating Light Source Color Rendition  Demonstration  Results from recent experiment

7

1

2

2 versus 3

Comparable CIE Ra and R9

3

3 versus 4

Comparable IES Rf and Rg Not Gamut Shape!

4

5 versus 4

Case 4 is eleven points higher in CRI (83 vs. 72)

5

5 versus 6

Case 6 is eight points higher in CRI (80 vs. 72)

6

7

Today’s Outline  Brief overview of CIE CRI  Introduction to TM-30-15 IES Method for Evaluating Light Source Color Rendition  Demonstration  Results from recent experiment

Human Judgements of Color Rendition Vary with Average Fidelity, Average Gamut, and Gamut Shape Michael Royer, Pacific Northwest National Laboratory Andrea Wilkerson, Pacific Northwest National Laboratory Minchen Wei, Hong Kong Polytechnic University Kevin Houser, Penn State University Robert 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

Results

Discussion

Conclusions

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.

Goals

Hypotheses

Methods

Results

Discussion

Conclusions

Apparatus and Test Space

Goals

Hypotheses

Methods

Results

Discussion

Conclusions

Independent Variables: Rf, Rg, and Gamut Shape 130

10 10

120

18 8

110

Rg

16

6

100

22

14

4

90

23

12

26 26

20

2

2

80

70 60

70

80

90

100

Rf Goals

Hypotheses

Methods

Results

Discussion

Conclusions

Independent Variables: Rf, Rg, and Gamut Shape 130 10

120

8

110

Rg

9

7 6

100

17

16 15

23 24

5

14 13

22 21

3

12 11

20 19

4

90

18

26 25

2 1

80

70 60

70

80

90

100

Rf Goals

Hypotheses

Methods

Results

Discussion

Conclusions

Independent Variables: Rf, Rg, and Gamut Shape 130

13

120

110

Rg

14 13

100

14

90

80

70 60

70

80

90

100

Rf Goals

Hypotheses

Methods

Results

Discussion

Conclusions

26

10

1

Preference varied systematically. Higher levels of Rg were generally preferred to lower levels of Rg. 130

a priori hypotheses

Like 120

3. Higher levels of Rg would be more preferred than lower levels of Rg.

4.0

4.5

IES TM-30 Rg

1 110

2

100

3

4. Higher levels of red saturation would be preferred.

90 5.0 80 5.5

Dislike

70 60

70

80

90

100

IES TM-30 Rf

Goals

Hypotheses

Methods

Results

Discussion

Conclusions

Preference varied systematically. Higher levels red saturation were preferred.

1

2

3

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

Goals

Hypotheses

Methods

Results

Discussion

Conclusions

Same fidelity and gamut, but different gamut shape, can lead to significantly different preference. 130

Like

4.0

4.5

IES TM-30 Rg

120

110

100

90 5.0 80 5.5

Dislike

70 60

70

80

90

100

IES TM-30 Rf

Goals

Hypotheses

Methods

Results

Discussion

Conclusions

Same fidelity and gamut, but different gamut shape, can lead to significantly different preference.

Goals

Hypotheses

Methods

Results

Discussion

Conclusions

Preference increased with red-saturation, with limits. 8

Dislike

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

Mean Preference Rating

7 6 5 4 3 2 Like

1 -30%

Goals

-20%

Hypotheses

-10% 0% 10% Hue Bin 16 Chroma Shift (Rcs,h16)

Methods

Results

20%

Discussion

30%

Conclusions

Participant Preference Rating

Post-hoc modeling of preference 7

Less Liked

6 5 4 3

R² = 0.9355

More Liked 2 2

3

4 5 6 TM-30 Model Predicted Preference Rating

7

Best Model for Preference:

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

Goals

Hypotheses

Methods

Results

Discussion

Conclusions

What about existing light sources? 50% 40% 30% 20%

Rcs,h16

10%

Experimental Preferred Zone*

0% -10% -20% -30% -40% -50%

Goals

Hypotheses

Methods

Results

Discussion

Conclusions

What about existing light sources? 140 Phosphor LED

Color Mixed LED

130

Hybrid LED

IES TM-30 Rg

120

Standard Halogen Experimental Preferred Zone*

110

Filtered Halogen Triphosphor Fluorescent, 7XX Triphosphor Fluorescent, 8XX

100

Triphosphor Fluorescent, 9XX 90

Metal Halide

80 70

60 50

Goals

60

Hypotheses

70 80 IES TM-30 Rf

Methods

90

100

Results

Discussion

Conclusions

Conclusions from this small study • 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

Goals

Hypotheses

Methods

Results

Discussion

Conclusions

IES

IES Technical Memorandum (TM) 30-15 (Includes Excel Calculators): IES Method for Evaluating Light Source Color Rendition http://bit.ly/1IWZxVu

Journals

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

US DOE

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

Kevin W. Houser, PhD, PE, FIES Professor of Architectural Engineering The Pennsylvania State University 104 Engineering Unit A University Park, PA 16801 USA

Collaborators: Additional TM-30-15 Resources Dr. Dale Tiller http://www.personal.psu.edu/kwh101/TM30/main.htm Dr. Xin Hu Dr. Bill Thornton Dr. Steve Fotios Mr. Mike Royer

Phone: (814)863-3555 Email: [email protected]

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