Sources, Surfaces, Eyes

Transcription

1 Sources, Surfaces, Eyes An investigation into the interaction of light sources, surfaces, eyes IESNA Annual Conference, 2003 Jefferey F. Knox David M. Keith, FIES

2 Sources, Surfaces, & Eyes - Research * Research Scientific activity dedicated to discovering what makes grass green. Russell Baker

3 Sources, Surfaces, and Eyes Overview * Why is the spectral nature of light important? Human color perception * Why is a new calculation technique necessary? The Lumen is spectrally ignorant * What are the ramifications of a new calculation procedure? more colorful predictions of our world * For Instance..

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5 Spectral Information is Important

6 Spectral Information is Important

7 Spectral Information is Important

8 Spectral Information is Important * Both Brightness and Color are needed to complete the human visual process * In order to understand how including spectral information effects lighting, we need to understand the basics of radiation and light

9 Lighting Basics: The Lumen Lumens = K * [ P(λ) * v(λ) ] Spectral Power Distribution 150 HPS Photopic Spectral Luminous Efficiency Function 1.40E Power (Watts) 1.20E E E E E E-01 Series Sensitivity Series1 0.00E Wavelength (nm) Wavelength Lumens source = K * [ S(λ) * v(λ) ] Sum λ from 360 to 770 nanometers

10 Lighting Basics: Reflectance * Luminous reflectance: Any of the geometric aspects of reflectance in which both the incident and the reflected flux are weighted by the spectral luminous efficiency of radiant flux V( ). Note: Unless otherwise qualified, the term reflectance means luminous reflectance. GLOSSARY OF LIGHTING TERMINOLOGY IESNA Lighting Handbook

11 Lighting Basics: Reflectance * Reflectance = Lumens off Lumens on * Average Reflectance What is average reflectance? Is it related to a specific source?

12 Lighting Basics: Contrast C mod = (L max - L min ) / (L max + L min ) For a perfectly diffuse reflector Luminance = Exitance π Exitance = Lumens on * Reflectance C mod = (p max - p min ) / (p max + p min )

13 Basic Problems: The Lumen * The Lumen is Spectrally Ignorant It contains no information about its spectral composition.

14 Basic Problems: The Lumen * A Lumen is a Lumen is a Lumen

15 Basic Problems: The Lumen * A Lumen is a Lumen is a Lumen Every lumen from a source is the same as every other lumen from that source!

16 Basic Problems: The Lumen * A Lumen is a Lumen is a Lumen Every lumen from a sources is the same as every other lumen from that source! BUT! Every lumen from one source is not the same as every lumen from a different source.

17 Basic Problems: Reflectance * Reflectance = Lumens off Lumens on * Because reflectance is lumen-based, it too is Spectrally Ignorant * Every interaction of light with a surface changes the spectral distribution of every lumen reflected

18 Basic Problems: Reflectance * Reflectance = Lumens off Lumens on * Because reflectance is lumen-based, it too is Spectrally Ignorant * Every interaction of light with a surface changes the spectral distribution of every lumen reflected * WHAT WE SEE IS REFLECTED LIGHT!

19 Basic Problems: Contrast Can You See This?

20 Basic Problems: Contrast Obviously we need to find some way to make better predictions that include color and color difference...

21 Why a New Calc. Technique * Our world is not all shades of gray

22 Why a New Calc. Technique * Our world is not all shades of gray * The effects of Color Difference need to be evaluated and taken into consideration

23 New Calculation Basics * Treat light as radiation not as some compressed unit that follows energy theory * Do not convert the radiation into lumens until it strikes the retina and only if value information is all that is important

24 The New Basics - Reflectance * Lumens on Lumens on = K* [S(λ)*v(λ)] * Lumens off Lumens off classic = average * {K* [S(λ)*v(λ)]} Lumens off revised = K * [ S(λ) * v(λ) * (λ) ]

25 Spectral Power Distribution Illum A Spectral Power X 100% wavelength (nm) FHWA Blue Paint Spectral Reflectance 90% 80% 70% Reflectivity 60% 50% 40% 30% 20% 10% 0%

26 Product of Illum A & Blue Spectral Reflectance = Spectral Power wavelength (nm)

27 250 Product of Illum A & Blue Spectral Reflectance 200 Spectral Power X 100% wavelength (nm) Photopic Spectral Luminous Efficiency Function 90% 80% Relative Magnitude 70% 60% 50% 40% 30% 20% 10% 0% wavelength (nm)

28 Stimulus Produced by Illum A & Blue = Spectral Power wavelength (nm) 683 * Stimulus = Lumens off

29 Spectral Reflectance Calculation 100% 90% 80% Relative Magnitude 70% 60% 50% 40% 30% Source Surface Off Surface vlambda Stimulus 20% 10% 0% wavelength (nm)

30 Sample Surface Wavelength Reflectivity Series1 Sample Surface Wavelength Reflectivity Series1 Sample Surface Wavelength Reflectivity Series1 Sample Surface Wavelength Reflectivity Series1 Sample Surface Wavelength Reflectivity Series1 Sample Surface Wavelength Reflectivity Series1

31 What does all this mean? Reflectance of sample surfaces under different sources Samp0 Samp1 Samp2 Samp3 Samp4 Samp5 wrt D65 x y EqEnergy 20% 20% 20% 20% 20% 20% D65 20% 22% 21% 20% 19% 18% Illum A 20% 12% 17% 20% 23% 28% HPS 20% 3% 2% 21% 45% 27% M25H 20% 14% 19% 19% 34% 13% M25U 20% 11% 21% 17% 40% 10% M40H 20% 15% 19% 20% 32% 13% M40U 20% 12% 19% 17% 38% 13%

32 What does all this mean? Reflectance of sample surfaces under different sources Samp0 Samp1 Samp2 Samp3 Samp4 Samp5 wrt D65 x y EqEnergy 20% 20% 20% 20% 20% 20% D65 20% 22% 21% 20% 19% 18% Illum A 20% 12% 17% 20% 23% 28% HPS 20% 3% 2% 21% 45% 27% M25H 20% 14% 19% 19% 34% 13% M25U 20% 11% 21% 17% 40% 10% M40H 20% 15% 19% 20% 32% 13% M40U 20% 12% 19% 17% 38% 13%

33 What does all this mean? Reflectance of sample colors under different sources Samp0 Samp1 Samp2 Samp3 Samp4 Samp5 wrt D65 x y EqEnergy 20% 20% 20% 20% 20% 20% D65 20% 22% 21% 20% 19% 18% Illum A 20% 12% 17% 20% 23% 28% HPS 20% 3% 2% 21% 45% 27% M25H 20% 14% 19% 19% 34% 13% M25U 20% 11% 21% 17% 40% 10% M40H 20% 15% 19% 20% 32% 13% M40U 20% 12% 19% 17% 38% 13%

34 What does all this mean? Reflectance of sample surfaces under different sources Samp0 Samp1 Samp2 Samp3 Samp4 Samp5 wrt D65 x y EqEnergy 20% 20% 20% 20% 20% 20% D65 20% 22% 21% 20% 19% 18% Illum A 20% 12% 17% 20% 23% 28% HPS 20% 3% 2% 21% 45% 27% M25H 20% 14% 19% 19% 34% 13% M25U 20% 11% 21% 17% 40% 10% M40H 20% 15% 19% 20% 32% 13% M40U 20% 12% 19% 17% 38% 13%

35 Sample Color Reflectances Sample Surfaces' Reflectances 50% 45% 40% 35% 30% 25% 20% 15% 10% 5% 0% Samp0 Samp1 Samp2 Samp3 Samp4 Samp5 EqEnergy D65 Illum A HPS M25H M25U M40H M40U

36 Sign Colors Orange % Daytime 33% X Y Refl D65*vl rho*x*s rho*y*s rho*z*s Wave S*rho E E E E E E E E E E E E E E E E E E E E E E

37 Color Reproduction

38 Sign Colors

39 New Reflectance Data Reflectances of FHWA Sign and Pavement Paints Under Different Sources of Illumination Black Blue Green Yellow Orange Red White PMWhite PMYellow x y EqEn 2% 19% 31% 75% 35% 16% 90% 75% 68% D65 2% 21% 33% 73% 33% 14% 90% 75% 66% Illum A 2% 12% 23% 83% 44% 22% 90% 75% 74% HPS 2% 4% 6% 95% 58% 20% 90% 74% 87% M25H 2% 13% 24% 82% 39% 14% 90% 75% 74% M25U 2% 11% 22% 84% 39% 13% 90% 76% 76% M40H 2% 15% 26% 80% 38% 13% 90% 75% 73% M40U 2% 12% 22% 84% 41% 14% 90% 76% 76%

40 New Reflectance Data Reflectances of FHWA Sign and Pavement Paints Under Different Sources of Illumination Black Blue Green Yellow Orange Red White PMWhite PMYellow x y EqEn 2% 19% 31% 75% 35% 16% 90% 75% 68% D65 2% 21% 33% 73% 33% 14% 90% 75% 66% Illum A 2% 12% 23% 83% 44% 22% 90% 75% 74% HPS 2% 4% 6% 95% 58% 20% 90% 74% 87% M25H 2% 13% 24% 82% 39% 14% 90% 75% 74% M25U 2% 11% 22% 84% 39% 13% 90% 76% 76% M40H 2% 15% 26% 80% 38% 13% 90% 75% 73% M40U 2% 12% 22% 84% 41% 14% 90% 76% 76%

41 New Reflectance Data Reflectances of FHWA Sign and Pavement Paints Under Different Sources of Illumination Black Blue Green Yellow Orange Red White PMWhite PMYellow x y EqEn 2% 19% 31% 75% 35% 16% 90% 75% 68% D65 2% 21% 33% 73% 33% 14% 90% 75% 66% Illum A 2% 12% 23% 83% 44% 22% 90% 75% 74% HPS 2% 4% 6% 95% 58% 20% 90% 74% 87% M25H 2% 13% 24% 82% 39% 14% 90% 75% 74% M25U 2% 11% 22% 84% 39% 13% 90% 76% 76% M40H 2% 15% 26% 80% 38% 13% 90% 75% 73% M40U 2% 12% 22% 84% 41% 14% 90% 76% 76%

42 New Reflectance Data Reflectances of Asphalt and Concrete Under Seven Different Sources of Illumination As1 As2 As3 Co1 Co2 Co3 Co4 Co5 x y EqEn 7.4% 7.3% 7.6% 33.3% 33.3% 26.0% 18.2% 25.9% D65 7.3% 7.3% 7.6% 33.2% 33.2% 25.7% 18.1% 25.7% Illum A 7.6% 7.5% 7.6% 33.7% 33.6% 26.8% 18.8% 26.6% HPS 7.7% 7.6% 7.7% 34.1% 34.0% 28.0% 19.4% 27.7% M25H 7.4% 7.4% 7.6% 33.5% 33.5% 26.4% 18.5% 26.3% M25U 7.5% 7.4% 7.6% 33.6% 33.6% 26.5% 18.6% 26.5% M40H 7.4% 7.3% 7.6% 33.5% 33.4% 26.3% 18.4% 26.2% M40U 7.5% 7.4% 7.6% 33.6% 33.6% 26.6% 18.6% 26.5%

43 New Basics - Contrast * Same standard equation C mod = (p max - p min ) / (p max + p min ) Still calculated in lumens * Different method for calculating reflectance

44 New Basics Color Difference * Threshold The difference in chromaticity or luminance between two colors that makes them just perceptibly different. The difference may be in hue, saturation, brightness(lightness for surface colors) or a combination of the three.

45 New Basics CIE L*a*b* * First, the illuminant in the local context can be specified, also in terms of the R, G and B cone outputs, as a reference white. That is, the model treats all colors as a combination of surface color and illuminant color, which allows the model to be applied across a wider range of viewing conditions.

46 New Basics CIE L*a*b* * Second, the trichromatic XYZ "primaries" are transformed mathematically to represent the Y/B and R/G opponent dimensions (along with a lightness or white/black dimension), which allows the models to reproduce the basic structure of color experience.

47 New Basics CIE L*a*b* * Finally, CIELAB is based on a set of imaginary primary lights that have been chosen specifically to make the color space perceptually uniform (at least, to the degree possible in a three dimensional model). That is, a difference of 10 units on the lightness dimension has the same perceptual impact as a 10 unit difference on the Y/B or R/G dimensions -- either separately or in combination.

48 New Basics CIE L*a*b* * dellab is the Euclidean distance between two color loci * LAB = {( L) 2 + ( a) 2 + ( b) 2 } 1/2

49 Sign Colors Contrast & dellab White on Red Black on White Black on Orange Black on Yellow White on Green Contrast dellab Contrast dellab Contrast dellab Contrast dellab Contrast dellab EqEnergy CIE D CIE A HPS M25H M25U M40H M40U

50 Sign Colors Contrast & dellab White on Red Black on White Black on Orange Black on Yellow White on Green Contrast dellab Contrast dellab Contrast dellab Contrast dellab Contrast dellab EqEnergy CIE D CIE A HPS M25H M25U M40H M40U

51 Sign Colors Red & White

52 Sign Colors Black & Orange

53 Sign Colors Black & Yellow

54 Asphalt & Paint Contrasts and del L*a*b* PmWhite on As1 PmWhite on As2 PmWhite on As3 Contrast dellab Contrast dellab Contrast dellab CIE D CIE A EqEnergy HPS M25H M25U M40H M40U PmYellow on As1 PmYellow on As2 PmYellow on As3 Contrast dellab Contrast dellab Contrast dellab CIE D CIE A EqEnergy HPS M25H M25U M40H M40U

55 Concrete & Paint Contrasts & del L*a*b* PmWhite on Co1 PmWhite on Co2 PmWhite on Co3 PmWhite on Co4 PmWhite on Co5 Contrast dellab Contrast dellab Contrast dellab Contrast dellab Contrast dellab CIE D CIE A EqEn HPS M25H M25U M40H M40U PmYellow on Co1 PmYellow on Co2 PmYellow on Co3 PmYellow on Co4 PmYellow on Co5 Contrast dellab Contrast dellab Contrast dellab Contrast dellab Contrast dellab CIE D CIE A EqEn HPS M25H M25U M40H M40U

56 Summary * Keep the spectral information in the calc. * Spectral effects of illuminants cannot be evaluated without considering the spectral reflectance of the lighted surfaces * All this is evaluated as single bounce applications (no inter-reflections!) * The significance of spectral effects can be greater when inter-reflections occur

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58 Sources, Surfaces, Eyes An investigation into the interaction of light sources, surfaces, eyes. IESNA Annual Conference, 2003 Jefferey F. Knox David M. Keith, FIES