Understanding TM-30 vs. CRI

Transcription

1 CORM 2016, NIST, Gaithersburg, May 16-18, 2016 Understanding TM-30 vs. CRI Yoshi Ohno (Ph.D., CIE President, IES Fellow) NIST Fellow, Sensor Science Division National Institute of Standards and Technology Gaithersburg, Maryland USA 1

2 OUTLINE 1. Outline of TM Analysis of TM-30 vs. CRI Color space Test color samples Relation to color preference 3. Position statements 4. Conclusions 2

3 IES TM-30 IES Method for Evaluating Light Source Color Rendition q Two-metric system Fidelity index R f Gamut index R g (CRI R a : fidelity) q 99 test samples (CRI: 8 samples) q Latest color space and chromatic adaptation formula q Graphic tool Color fidelity: Improvement of CRI R a Information related to preference Works accurately for all colors of object and all kinds of spectra Provide details beyond R f and R g. 3

4 99 Test Samples Data of real objects taken from the U. Leeds database The samples are distributed evenly in the 3D object color space. More considerations 4

5 Concept of Two-Metric System Gamut R g Image from Michael Royer 5 Fidelity R f Image from Michael Royer.

6 Graphic tools Calculation Tool distributed with TM-30 purchase. R f -R g Chart Color Vector Graphic Color Distortion Graphic 6

7 Comparison of CRI CQS TM-30 Score Test Sample CRI CQS TM- 30 Fidelity Ra Qf Rf Gamut area Qg Rg General Qa for hue R1- R14 Q1- Q14 Rfh,1 - Rfh,16 Graphic Saturation icon Color Vector g. Num. of samples Saturation medium saturation strong saturation Various saturation Origin Munsell samples Munsell samples Real objects data Color space CIE 1964 W*U*V* CIE LAB CIECAM02 Chromatic adaptation von Kries CMCCAT CIE CAM02 Scale no limit Reference Planck/Daylight Planck/Daylight Planck- Daylight 7

8 Scaling of CRI CQS TM-30 TM-30 Rf Scaling factor The average score for CIE F1 to F12 is made equal. CRI, # R /,' = 75.1 '., Ra CQS 9.0 Qf TM-30 Rf CIE F1-12 (reference FLs) CQS, # Q f,' = 75.1 '., TM-30, # R f,' = 75.1 '., CIE F1 CIE F2* CIE F3 CIE F4 CIE F5 CIE F6 CIE F7* CIE F8 CIE F9 CIE F10 CIE F11* CIE F12 8

9 Score differences for various sources TM#30&Rf& 100# 90# 80# 70# Others# RGB(A)# Series3# Phosphor#LED# 122 sources on CQS 9.0 sheet Score differences > 5 points are significant. 60# 50# 50# 60# 70# 80# 90# 100# CRI&Ra& 9

10 OUTLINE 1. Outline of TM Analysis of CRI and TM-30 Color space Test color samples Relation to color preference 3. Position statements 4. Conclusions 10

11 Plots of 15 CQS samples. W*U*V* used in CRI Color Space CIELAB Used in CQS CAM02UCS used in TM K Planck D65 (6500 K) 11 High weights for red and green color shifts Low weights on yellow and blue region. R9 sensitive at low CCT.

12 Examples of this effect 12

13 SPD$(arb.$un.)$ No. 117 White LED (3420 K) 1.6" Test"source" Reference"source" 1.4" 1.2" 1" 0.8" 0.6" 0.4" R a =80 R f =75 CRI samples on W*U*V* W*U*V* 60 Reference Test source " 0" 400" 450" 500" 550" 600" 650" 700" l$(nm)$ 100" CRI 8 samples 90" R f $by$hue$ 80" 70" 60" 50" Yellow-blue shifts are large in this example, resulting in higher Ra value. 13

14 No. 121 White LED (2770 K) 3" Test"source" Reference"source" 2.5" R a =82 R f =82 CRI 8 samples on W*U*V* W*U*V* Reference Test source SPD$(arb.$un.)$ 2" 1.5" 1" 0.5" " 400" 450" 500" 550" 600" 650" 700" l$(nm)$ 100" " R f $by$hue$ 80" 70" 60" 50" Yellow-blue shifts are small in this example, showing little advantage in CRI score. 14

15 No. 61 Natural FL (3900 K) R a =92 R f =86 3.5" 3" 2.5" Test"source" Reference"source" W*U*V* Reference Test source SPD$(arb.$un.)$ 2" 1.5" 1" 0.5" " 400" 450" 500" 550" 600" 650" 700" l$(nm)$ 100" CRI 8 samples 90" R f $by$hue$ 80" 70" 60" 50" Yellow-blue shifts are large in this example, resulting in higher Ra value. 15

16 The other effect of color space (for saturated lights) Lights used in NIST visual experiments (3000 K) CRI CQS 9.0 Qf TM-30 Rf peak 3012 K, Ra 70 desat peak 3020 K, desat peak 3022 K, desat peak 3000 K, desat peak 3000 K, neutral peak 3000 K, Satu 1 CRI R a value goes down sharply as red-green saturation increases peak 3010 K, Satu peak 3000 K, Satu peak 3030 K, Satu 4 16

17 No. 101 Saturated-4 (3000 K) SPD$(arb.$un.)$ 5" 4.5" 4" 3.5" 3" 2.5" 2" 1.5" 1" 0.5" 0" 400" 450" 500" 550" 600" 650" 700" l$(nm)$ 100# Test"source" Reference"source" R a =69 R f =80 CRI 8 samples on W*U*V* W*U*V* Reference Test source CRI 8 samples 90# R f!by!hue! 80# 70# 60# 50# Oversaturation is at heavily weighted red-green region. Ra values tend to go lower. 17

18 An example No. 86 Test Sample problem CRI allows very poor red rendering R9= -97 R a = 82 R f = 76 CORM 2016 Gaithersburg, MD 18

19 Spectral sensitivity of test samples CRI No. 86 TM-30 R 1 =93 R a =82 R 1 =54 R f =76 CRI fails to catch the problem with saturated red objects. TM-30 and CQS catches this problem and reflect in score. CORM 2016 Gaithersburg, MD 19

20 Color Sample problem (2) CRI anomaly / TM-30 spectral feature No. 72 (3300 K) R a =90 R f =76 (Q f =80) CQS samples on CIELAB 100 CIELAB 80 CRI samples on W*U*V* 60 Reference Test source SPD$(arb.$un.)$ 4" Test"source" Reference"source" 3.5" 3" 2.5" 2" 1.5" 1" 0.5" 0" 400" 450" 500" 550" 600" 650" 700" l$(nm)$ a* b* Ref Test CRI 8 samples 100" 90" 80" 70" R f!by!hue! 60" 50" 40" 30" 20" 10" 0" Hue shifts 20

21 CRI samples No TCS01 TCS02 TCS03 TCS04 TCS05 TCS06 TCS07 TCS08 source CQS samples Wavelength (nm) VS1 VS2 VS3 VS4 VS5 VS6 VS7 VS8 VS9 VS10 VS11 VS12 VS13 VS14 VS15 Source Test 1.0# 0.9# 0.8# 0.7# 0.6# 0.5# 0.4# 0.3# 0.2# 0.1# TM-30 samples 0.0# 400# 450# 500# 550# 600# 650# 700# Wavelength*(nm)* The CRI 8 sample curves have some tendency. The set of 8 samples allows some combinations of peaks that yield unreasonably high score (anomaly) This tends to occur with narrowband sources. 21 It is difficult to occur with 99 samples.

22 R a =86 R f = " 0.005" 0.004" Average slope of all curves (TM-30 spectral flattening) CQS" CRI" TM230" 0.003" 0.002" 0.001" 0" 400" 450" 500" 550" 600" 650" 700" CRI sample slope falls at both ends, while TM-30 is made flat. This feature of TM-30 allows fair evaluation of all colors (including strong purple), while it tends to require broader spectra. 22

23 Color Sample problem (3) CRI anomaly / TM-30 spectral feature No. 19 (3300 K) SPD$(arb.$un.)$ 3" 2.5" 2" 1.5" 1" 0.5" Test"source" R a =97 R f =87 (Q f =93) Reference"source" 0" 400" 450" 500" 550" 600" 650" 700" l$(nm)$ CQS samples on CIELAB CIELAB b* Ref a* Test CRI samples on W*U*V* W*U*V* Reference Test source CRI 8 samples CRI 8 samples # 100# # HL81# HL91# 90# # # HL94# HL85# HL36# HL86# R f!by!hue! 80# 70# 60# Hue shifts # # # 400# 450# 500# 550# 600# 650# 700# HL92# HL38# HL5# HL71# Source# 50# 23

24 Sample gamut of TM-30 reduced to the size of the NCS sample set HL1000 from U. Leads (red dots) Red:TM samples (red dots) This is from consideration that such extremely color-saturated objects are not common in our daily life. 24

25 The effect of gamut reduction Original gamut (CIE 2012) After gamut reduced (TM-30) Current version of TM-30 This version required more broader band to obtain the same score. 25

26 CRI R a response to Duv shift - Poor performance of von Kries chromatic adaptation transform 2700 K 0.18" 0.16" 0.14" 0.12" Duv=/0.015" Duv=/0.015" Duv=/0.015" 0.1" 0.08" 0.06" 0.04" 0.02" 0" 400" 450" 500" 550" 600" 650" 700" Score& 95# 90# 85# 80# Ra# Rf# 75# 70# '0.02# '0.01# 0# 0.01# 0.02# Duv& NIST vision experiment in " 2700 K 95# 0.1" 0.08" 0.06" 0.04" 0.02" Duv=/0.015" Duv=0" Duv=0.015" Score& 90# 85# 80# Ra# Ohno, Y., Fein, M., Vision Experiment on Acceptable and Preferred White Light Chromaticity for Lighting, CIE x039:2014, pp (2014). 0" 400" 450" 500" 550" 600" 650" 700" 75# Rf# 70# '0.02# '0.01# 0# 0.01# 0.02# Duv& 26

27 Relation to Color Preference CRI penalizes good preferred lights 27

28 CIELAB 2014 Vision Experiment at NIST on preferred chroma saturation level 20 subjects 3 CCTs (2700, 3500, 5000 K), D uv = K, D uv = ΔC * ab = Most saturated 20 a* ΔC * ab = b* Most de-saturated

29 Results Average Preference for ΔC 100% Percent of Participants who preferred the Point - 16 (1) Entire room 80% (2) Skin tone of subject 60% Average Room Skin Green Red 40% 20% 0% (3) Red fruits/vegetables ΔCab* à More saturated De- saturated ß (4) Green fruits/vegetables Neutral Reference: Y. Ohno, M. Fein, C. Miller, Vision Experiment on Chroma Saturation for Color Quality Preference, CIE 216 :2015, pp (2015) CORM 2016 NIST Gaithersburg 29

30 Average of all targets, all subjects (3500 K) Subjects Preference 120% 100% 80% 60% 40% 20% R a < 80 De-saturated ß à Over-saturated Subjects preference Subjects preference CRI Ra 0% Chroma difference ΔC*ab (red) 50 CRI penalizes or exclude many preferred light sources. 30

31 Average of all targets, all subjects (3500 K) Subjects Preference 120% 100% 80% 60% 40% 20% Rf < 80 De-saturated ß à Over-saturated Subjects preference CRI Ra TM-30 Rf 0% Chroma difference ΔC*ab (red) 50 Problem is less in TM-30 R f. 31

32 Gamut index R g Average of all targets, all subjects (3500 K) 160% 140% Subjects preference Subjects Preference 120% 100% 80% 60% 40% 20% CRI Ra TM-30 Rf CQS Qg TM-30 Rg 0% Chroma difference ΔC*ab (red) 50 R g is not proportional to preference, but it can tell if light is de-saturating or saturating (preferred side). 32

33 Limitation of R g - ave. of all hues R g equal but different shapes R g =100 R f =75 R g =100 R f =75 Perceived rendering of these two lights is very different. Gamut area is not sufficient to address color preference. 33

34 OUTLINE 1. Outline of TM Analysis of CRI and TM-30 Color space Test color samples Relation to color preference 3. Position statements 4. Conclusions 34

35 IES Position statement on CRI 2015 Issued Sep IES recognize that CIE CRI has shortcomings, especially with new lighting technologies. TM-30 was developed to solve this problem. TM is not a required standard, and it does not provide design guidance or criteria for best practices. the issuance of TM will enable the international lighting community to carefully evaluate it, providing a path leading to improved standards and design guidance. Link: 35

36 CIE Position statement on CRI and Color Quality Metrics Issued Oct CRI has several significant sources of colorimetric inaccuracy. CRI needs to be updated. CIE TC1-90 is developing a new color fidelity metric. CIE supports the study of the recently published IES TM-30. TC1-90 accepted TC-30 R f metric as basis for the TC s first draft. An orderly transition is needed when a new metric is to be introduced. Both TC reports to be completed by end of Link: The colour fidelity metrics including the CRI do not assess other important aspects of the colour qualities of light sources, in particular, those related to colour preference. CIE TC 1-91 is developing a Technical Report on this subject. 36

37 Future perspective Color Rendition (Ohno s personal perspective) Color Fidelity Current int l std. CRI R a (CIE 13.3) TM-30 R f Use these as tools Color Preference No standards TM-30 R g Many other inputs CIE TC1-90 Proposal to update CRI Int l recommendation of new fidelity metric Use of two metrics CIE TC1-91 New TC Tech. report (no recommendation) More research Int l recommendation on color-preference metric(s)

38 38 Summary TM-30 R f provides a more (scientifically) accurate color fidelity metric for all colors of object. CRI scores can be biased due to only one type of test sample used (Munsell samples). à TM-30 R f avoids bias by using test samples from real objects database. CRI score can have anomaly due to only eight samples. à TM-30 R f avoids anomaly (by using varieties of 99 test samples.) However, we do not expect that R f will correlate with visual impression of lit scenes better than R a (due to inherent limitation of the fidelity metric). Color fidelity is only one aspect of color quality. A preference-related metric(s) is in urgent need. THANK YOU for your attention.