J Schanda University Veszprém, Department of Image Processing and Neurocomputing, Hungary...

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J Schanda University Veszprém, Department of Image Processing and Neurocomputing, Hungary Characterizing illumination systems Colour rendering and beyond

Transcript of J Schanda University Veszprém, Department of Image Processing and Neurocomputing, Hungary...

Page 1: J Schanda University Veszprém, Department of Image Processing and Neurocomputing, Hungary Characterizing illumination systems Colour rendering and beyond.

J Schanda

University Veszprém, Department of Image Processing and Neurocomputing, Hungary

Characterizing illumination systemsColour rendering and beyond

Page 2: J Schanda University Veszprém, Department of Image Processing and Neurocomputing, Hungary Characterizing illumination systems Colour rendering and beyond.

CIE Standards for assessing quality of light sources

• Introduction

• Characterisation of the light source

• Colour rendering

• Assessing daylight simulators

• CIE Technical Committees working on the above questions

• New approaches

• Summary

Page 3: J Schanda University Veszprém, Department of Image Processing and Neurocomputing, Hungary Characterizing illumination systems Colour rendering and beyond.

CIE Standards and Guides

• CIE colorimetric illuminants– ISO/CIE 10526, CIE S005

• CIE colorimetric observers– ISO/CIE 10527

• International Lighting Vocabulary– CIE 17.4

• Colorimetry: CIE 15.2, new edition coming• Colour rendering: CIE 13.3, outdated -

experiments needed• Quality of daylight simulators: CIE 51,

possible improvements

Page 4: J Schanda University Veszprém, Department of Image Processing and Neurocomputing, Hungary Characterizing illumination systems Colour rendering and beyond.

Illuminant, source, simulator

• CIE Standard Illuminant

– Defined as spectral distribution

Page 5: J Schanda University Veszprém, Department of Image Processing and Neurocomputing, Hungary Characterizing illumination systems Colour rendering and beyond.

CIE Standard Illuminants

/ nm SA() SD65()

300 0,930 483 0,0341 000301 0,967 643 0,360 140302 1,005 97 0,686 180303 1,045 49 1,012 22304 1,086 23 1,338 26305 1,128 21 1,664 30306 1,171 47 1,990 34307 1,216 02 2,316 38308 1,261 88 2,642 42309 1,309 10 2,968 46310 1,357 69 3,294 50311 1,407 68 4,988 65312 1,459 10 6,682 80313 1,511 98 8,376 95314 1,566 33 10,071 1315 1,622 19 11,765 2316 1,679 59 13,459 4317 1,738 55 15,153 5318 1,799 10 16,847 7319 1,861 27 18,541 8320 1,925 08 20,236 0321 1,990 57 21,917 7322 2,057 76 23,599 5

Page 6: J Schanda University Veszprém, Department of Image Processing and Neurocomputing, Hungary Characterizing illumination systems Colour rendering and beyond.

Illuminant, source, simulator

• CIE Standard Illuminant

– Defined as spectral distribution

• CIE Standard Source

– Source with specified spectral distribution

• Simulator

– Source approximating the illuminant

Page 7: J Schanda University Veszprém, Department of Image Processing and Neurocomputing, Hungary Characterizing illumination systems Colour rendering and beyond.

CIE colorimetric illuminants

• CIE Standard Illuminant A

– New definition, unchanged values

Page 8: J Schanda University Veszprém, Department of Image Processing and Neurocomputing, Hungary Characterizing illumination systems Colour rendering and beyond.

CIE Standard Illuminant A

SAexp

1 435 000

159 488

exp14 350

2 848

( ),

100

0 56 1

1

5

Page 9: J Schanda University Veszprém, Department of Image Processing and Neurocomputing, Hungary Characterizing illumination systems Colour rendering and beyond.

CIE colorimetric illuminants

• CIE Standard Illuminant A

– New definition, unchanged values

• CIE Standard Illuminant D65

Page 10: J Schanda University Veszprém, Department of Image Processing and Neurocomputing, Hungary Characterizing illumination systems Colour rendering and beyond.

CIE Standard Illuminant D65

5. CIE standard illuminant D65

5.1 Definition

The relative spectral power distribution SD65

() of CIE standard illuminant D65 is defined bythe values given in table 1 which are presented at 1 nm intervals over the wavelength rangefrom 300 nm to 830 nm. If required, other intermediate values may be derived by linearinterpolation from the published values*.

* Information on the procedure used to derive D65 values is given in Publication CIE 15.2 [1].

Page 11: J Schanda University Veszprém, Department of Image Processing and Neurocomputing, Hungary Characterizing illumination systems Colour rendering and beyond.

CIE colorimetric illuminants

• CIE Standard Illuminant A

– New definition, unchanged values

• CIE Standard Illuminant D65

– Other daylight illuminants: D50

– Evaluation

Page 12: J Schanda University Veszprém, Department of Image Processing and Neurocomputing, Hungary Characterizing illumination systems Colour rendering and beyond.

CIE (Standard) Source(s)

• CIE Standard Source A

– Realization: incandescent lamp

• D65: no standard source

• Secondary sources

– fluorescent lamps

Page 13: J Schanda University Veszprém, Department of Image Processing and Neurocomputing, Hungary Characterizing illumination systems Colour rendering and beyond.

Source standards and imaging

• Original– Real life: daylight illumination

– paper copy: D50, fluorescent or tungsten illum.

– screen representation

• Reproduction– screen representation

– hard-copy

Page 14: J Schanda University Veszprém, Department of Image Processing and Neurocomputing, Hungary Characterizing illumination systems Colour rendering and beyond.

Source standards and imaging

• Original scene– Daylight: D50, D65 (Jackson - MacDonald - Freeman pictures)

Page 15: J Schanda University Veszprém, Department of Image Processing and Neurocomputing, Hungary Characterizing illumination systems Colour rendering and beyond.

Source standards and imaging

• Reproduction– screen representation

• CRT primaries

• chromatic adaptation

• colour appearance models

– hard-copy• CMYK primaries

• base material (paper reflection properties)

• gamut mapping

Page 16: J Schanda University Veszprém, Department of Image Processing and Neurocomputing, Hungary Characterizing illumination systems Colour rendering and beyond.

Source standards: original scene

• Light source colour description– chromaticity of source– colour temperature– correlated colour temperature– metamerism index

• Colour rendering – special indices: Ri

– general colour rendering index: Ra

Page 17: J Schanda University Veszprém, Department of Image Processing and Neurocomputing, Hungary Characterizing illumination systems Colour rendering and beyond.

Light source colour description

• Colour temperature, Tc– The temperature of a Planckian radiator

whose radiation has the same chromaticity as that of a given stimulus.

• Correlated colour temperature Tcp– The temperature of the Planckian radiator

whose perceived colour most closely resembles that of a given stimulus at the same brightness and under specified viewing conditions.

Page 18: J Schanda University Veszprém, Department of Image Processing and Neurocomputing, Hungary Characterizing illumination systems Colour rendering and beyond.

Light source colour description

Page 19: J Schanda University Veszprém, Department of Image Processing and Neurocomputing, Hungary Characterizing illumination systems Colour rendering and beyond.

Colour rendering

• Spectra of two sources of equal chromaticity

Spectral power distribution

0

20

40

60

80

100

120

140

160

180

350 400 450 500 550 600 650 700 750 800 850 900

wavelength, nm

rel.

po

we

r

Page 20: J Schanda University Veszprém, Department of Image Processing and Neurocomputing, Hungary Characterizing illumination systems Colour rendering and beyond.

Colour rendering

• Chromaticity of the two sources and of a sample illuminated by these sources

Page 21: J Schanda University Veszprém, Department of Image Processing and Neurocomputing, Hungary Characterizing illumination systems Colour rendering and beyond.

Colour rendering

• Effect of an illuminant on the colour

appearance of objects by conscious or

subconscious comparison with their colour

appearance under a reference illuminant

Page 22: J Schanda University Veszprém, Department of Image Processing and Neurocomputing, Hungary Characterizing illumination systems Colour rendering and beyond.

Colour rendering index

• Measure of the degree to which the

phsychophysical colour of an object

illuminated by the test illuminant conforms

to that of the same object illuminated by the

reference illuminant, suitable allowance

having been made for the state of chromatic

adaptation.

Page 23: J Schanda University Veszprém, Department of Image Processing and Neurocomputing, Hungary Characterizing illumination systems Colour rendering and beyond.

Colour rendering index

• Comparison of illuminants– test illuminant– reference illuminant:

• Planckian if CCT < 5000 K

• Phase of Daylight 5000 K

• Objects illuminated (test colour samples)

• Chromatic adaptation• Colour difference

Page 24: J Schanda University Veszprém, Department of Image Processing and Neurocomputing, Hungary Characterizing illumination systems Colour rendering and beyond.

Flow-chart of CRI calculation

Ref.illuminant

Test

source

Equal

CCT

test sourceU*V*W* transf.

Test smpls.

illum.

test smpl.

CIE

XYZ

Test smpls.

illum.

ref. illum.

XYZ

U*V*W*

Colour

diff.

Chrom.

adapt.

CRA

CRI

Page 25: J Schanda University Veszprém, Department of Image Processing and Neurocomputing, Hungary Characterizing illumination systems Colour rendering and beyond.

Test colour samples

Page 26: J Schanda University Veszprém, Department of Image Processing and Neurocomputing, Hungary Characterizing illumination systems Colour rendering and beyond.

CRI calculation - 1

• Selecting reference illuminant

• Selecting test colour samples

• Chromatic adaptation (von Kries)

• Colour difference calculation

– U*, V*, W* colour space

Page 27: J Schanda University Veszprém, Department of Image Processing and Neurocomputing, Hungary Characterizing illumination systems Colour rendering and beyond.

Chromatic adaptation

Page 28: J Schanda University Veszprém, Department of Image Processing and Neurocomputing, Hungary Characterizing illumination systems Colour rendering and beyond.

CRI calculation - 2

• Special colour rendering indices: Rk,t = 100 – 4,6 Ei,k,r-t.

• General colour rendering index:

8

18

1

iia RR

Page 29: J Schanda University Veszprém, Department of Image Processing and Neurocomputing, Hungary Characterizing illumination systems Colour rendering and beyond.

Assessing daylight simulators - 1

• For colorimetric practice the evaluation of

the UV content also important

• Assessment based on metamerism indices

– 5 metameric pairs

• 3 sets: D55, D65, D75,

• Set for D50 under development

Page 30: J Schanda University Veszprém, Department of Image Processing and Neurocomputing, Hungary Characterizing illumination systems Colour rendering and beyond.

Assessing daylight simulators - 2

• Visible range metamerism index– average colour difference for the five

metameric pairs

5

1 5i

iEMIvis

Page 31: J Schanda University Veszprém, Department of Image Processing and Neurocomputing, Hungary Characterizing illumination systems Colour rendering and beyond.

Assessing daylight simulators - 3

• UV range assessment– reflected part of radiation +– emitted part of radiation

• Final assessment: MI for UV and visible

• Assessment based on CIELAB or CIELUV colour differences– Five categories established

Page 32: J Schanda University Veszprém, Department of Image Processing and Neurocomputing, Hungary Characterizing illumination systems Colour rendering and beyond.

Assessing daylight simulators - 4

Page 33: J Schanda University Veszprém, Department of Image Processing and Neurocomputing, Hungary Characterizing illumination systems Colour rendering and beyond.

CIE TCs working on colorimetry

• CIECAM colour appearance models

• VDU - Reflective media comparison

• Chromaticity diagram with physiologically significant axes

• Geometric tolerances in colorimetry

• Updating the colorimetry and colour rendering documents

Page 34: J Schanda University Veszprém, Department of Image Processing and Neurocomputing, Hungary Characterizing illumination systems Colour rendering and beyond.

Summary

• Light source colorimetry– lamp light colour

– brightness - task-performance relationship

– colour rendering

• Image reproduction colorimetry– colour appearance

– colour management