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An alternative colour rendering index based on memory colours

An alternative colour rendering index based on memory colours. Kevin SMET KaHo Sint-Lieven – K.U.Leuven Light & Lighting Laboratory – ESAT/ELECTA Gebroeders Desmetstraat 1, 9000 Gent ( Belgium ) Tel: +32 92 65 87 13 kevin.smet@ kahosl.be. All data is for personal or TC1-69 use .

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An alternative colour rendering index based on memory colours

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  1. Analternative colour rendering index basedonmemorycolours Kevin SMET KaHo Sint-Lieven – K.U.Leuven Light & Lighting Laboratory – ESAT/ELECTA Gebroeders Desmetstraat 1, 9000 Gent (Belgium) Tel: +32 92 65 87 13 kevin.smet@kahosl.be Kevin Smet – Analternative colour rendering index

  2. All data is forpersonalor TC1-69 use. The basicidea, methodsused, visualresults & modeling have been written in a paper that is underreview forpublication in “Journal of Vision”. Resultscomparing the Memory Colour based index with CIE CRI, CQS and visualresultslike the Thurstonescalings, kindlyprovidedby Sophie Jost-Boissard, as well as withvisualscalingexperimentsthatwillbeperformed in the nearfuturewillbepublished in a next paper. Kevin Smet – Analternative colour rendering index

  3. BasicIdea & TheoreticalMethod Kevin Smet – Analternative colour rendering index

  4. BasicIdea: • Absolute assessment • No need of referenceilluminants! • No dependenceoncorrelatedcolour temperature: test sourceswith different CCT canbecompared. • More realisticway of evaluating colour rendering. • (*) Memory colours define the colours that are recalled in association with familiar objects in long-term memory (Bartleson, 1960).. Referencing is done to memorycolours* of familiarobjects, NOT to a referenceilluminant! Kevin Smet – Analternative colour rendering index

  5. Method • YES / NO • Only a qualitativemeasurefor colour renderingbasedonacceptability of apparent object colour. Investigatecolour acceptanceboundaries of familiarobjects • Test subjectsrateacceptability(YES/NO) of a set of apparent object colours: Kevin Smet – Analternative colour rendering index Kevin.Smet@kahosl.be 5

  6. Method • Similarity ratings on a 5 point scale as a function of chromatic distance to memory colour. • Quantitativemeasurefor colour rendering. • Test subjectsratesimilarity (on a 5 point scale) of a set of apparent object colours to theirmemory colour of the object: Kevin Smet – Analternative colour rendering index Kevin.Smet@kahosl.be 6

  7. Fromsimilarity ratings to analternative colour rendering index • Model pooledsimilarity ratings by a bivariateGaussiansurface R(x,y): • Chromaticity of apparent object colour: X • Centre Xc = chromaticity of memory colour • Mahalanobisdistance d(x,y) ~ degree of similarity S(x,y) • aiare fitting parameters: • a1 & a2 are used to account forinterobservervariability • a3 to a4 describe the similarityfunction S(x,y). Kevin Smet – Analternative colour rendering index Kevin.Smet@kahosl.be 7

  8. Fromsimilarity ratings to analternative colour rendering index • Alternative colour rendering index Sa: • Calculateforeach object i: • chromaticity of object renderedby the test source • byusing the spectralreflectance factors of the object. • Mahalanobisdistancedi to chromaticity of memory colour • Special colour rendering index:S’i = exp(-0.5* di) • General colour rendering index:S’a= mean(Si). 5. (Rescale indices to CRI levels: Ra(F1-F12)= a*Sa(F1-F12)+b) Kevin Smet – Analternative colour rendering index Kevin.Smet@kahosl.be 8

  9. Practical Kevin Smet – An alternative colour rendering index Kevin Smet – Analternative colour rendering index

  10. Real versus simulatedobjects? • Naturalness has influenceonsimilarity ratings (Yendrikhovskii, Blommaert & De Ridder, 1999) • Colour constancy is greaterforsurfacecolours and lights in realscenesthan in simulatedscenes. (Berns & Gorzynski, 1991; Brainard, 1998) Experimentswithrealobjects ! Kevin Smet – Analternative colour rendering index Kevin.Smet@kahosl.be 10

  11. Illumination box to changeapparent object colours Create the illusion of the object changing colour! • Special design to maskanyilluminantclues! a. RGBA LEDs • changeapparent object colour b. Diffusing tunnel: • uniform illumination of objects • avoidspecularreflectionon object c. Transparent support forobjects: • hidesurfacereflections revealingillumination colour d. Back panel lighting: • constant adaptation white with CCT = 6000K. Kevin Smet – Analternative colour rendering index Kevin.Smet@kahosl.be 11

  12. SpectralMeasurements • Tele-spectroradiometrically: • radiometric measuring head • 74055 MS260i spectrograph • iDUS DV420A-BU2 CCD camera • Setupidentical to viewingconditions Kevin Smet – Analternative colour rendering index Kevin.Smet@kahosl.be 12

  13. Chromaticities / colour spaces • CIE 10 degreeobserver • Measuredchromaticities are transformed to correspondingcolours: • Chromatic AdaptationTransform: CAT02 • Equal Energy Illuminant • Colour spaces: • SVF (Seim & Valberg, 1986): ~perceptually uniform colour space • CIECAM02 is unfortunatelynotapplicable: • Yb of background cannotbedefined, becauseit is more luminous (=selfluminous) than the reflected white of the front panel (Yb wouldbe > 100). Personalcommunicationwith Mark Fairchild. Kevin Smet – Analternative colour rendering index Kevin.Smet@kahosl.be 13

  14. Test Object Selection • High degree of familiarity: NATURAL OBJECTS (e.g. food) • Object chromaticitydistributions are preferablyunimodalor a single mode shouldbeunambiguouslyspecifiable; i.e. the natural colour varianceshouldnotbetoo high: e.g.: • green apple, ripebanana, … • but NOT: blue grape, because the chromaticity of blue grapesvariesfrom a black/dark blue to wine red. Kevin Smet – Analternative colour rendering index Kevin.Smet@kahosl.be 14

  15. Test Object Selection • Object chromaticities spread uniformlyaround the huecircle: • Primaryregions of choice: green, yellow, red, purple & blue. BUT somedifficulties: • Illumination box cannotchange the apparent colour of REDnaturalobjectssufficientlydue to theirhighly chromatic nature. - ORANGE is taken as a compromise. • Number of bluewell-knownunambiguouslyspecifiableobjects is extremelylimited. - a SMURF figurine was selected, becausewhenquestioned most people report having a goodideasmurf blue. • Extra experiments are plannedwithsomeless chromatic objects as well: strawberry yoghurt (red), cheese , caucascian skin, … Kevin Smet – Analternative colour rendering index Kevin.Smet@kahosl.be 15

  16. Experiment setup: • Calibrateillumination box: map XYZ to RGBA DAC input values. • Calculate object colour solid. • Select luminanceplanewith optimum chromaticitygamut. • Calculate RGBA DAC input valuesresulting in a uniform gridin the colour spaceselected. • Add double gridpoints to illuminationsequence. • Randomizesequence. • Add a set of 20 training pointsto familiarizeobserverswith the scale. • Measure the object spectralradiance. • Calculatechromaticities of sequence of apparent object colours • Visual assessmentof sequenceby test subjects: • Similarity ratings on a 5 point scale • 1: very bad; 2: bad; 3: neutral; 4: good; 5: verygood Kevin Smet – Analternative colour rendering index Kevin.Smet@kahosl.be 16

  17. Experimentalresults Kevin Smet – Analternative colour rendering index

  18. Visual assessmentresults • Intra & Interobservervariabilitywith PF/3 performance factor: • Results are good, consideringthat a PF/3 of 30 is common in colour discrimination studies. (Guan & Luo, 1999a,b; Xu, Yaguchi & Shiori, 2001) • Data can be pooled and average observer can be postulated. Kevin Smet – Analternative colour rendering index Kevin.Smet@kahosl.be 18

  19. Visual assessmentresults • Average observer reliability (real world validity) analysed with ICC(2,n) according to method described by Shrout & Fleiss (1979). • Good results: • validate the use of pooled rating data as basis for colour rendering evaluation. • ICC(2,n) shows a high inverse correlation (ρ = -0.94) with the PF/3. • Observers agreed best on what a ripe banana looks like and least on what dried lavender should look like. Kevin Smet – Analternative colour rendering index Kevin.Smet@kahosl.be 19

  20. Model results • Pooled rating distribution was fitted using MATLAB lsqcurvefitfunction. • Goodness-of-fit to mean ratings of pooled data analysedwithPearsonρ and RMSE: • Confirmation of Yendrikhovskij et al. (1999): • Similarityjudgementscanbedescribed by a bivariateGaussian distribution in a perceptually uniform colour space. Kevin Smet – Analternative colour rendering index Kevin.Smet@kahosl.be 20

  21. Colour renderingevaluationbasedonmemorycolours. - Results - Kevin Smet – Analternative colour rendering index

  22. Rescaling the similarityfunctions Fluorescent sources F1-F12 • Similarityfunctions are rescaled to the CIE CRI level by a lineartransformationcalculatedusing a least squares approach: • Advantage: Colour rendering scores foroldsources are keptnearly the same. Kevin Smet – Analternative colour rendering index Kevin.Smet@kahosl.be 22

  23. Alternative CRI for 90 lamps • Lamp spectralradiances: seeexcel file. Kevin Smet – Analternative colour rendering index Kevin.Smet@kahosl.be 23

  24. Correlationwithvisualassessments • All visualscaling data was kindlyprovidedby Sophie Jots-Boissard • The Pearsoncorrelationcoefficientbetween the Thurstonescalingsforattractiveness, of nine3000K (Boissard, 2009) & eight 4000K lampsobtained in a series of visualexperimentsperformedby Sophie Jost-Boissard, and the Memory Colour based index is high: ρ3000K = 0.95 (p<0.05) & ρ4000K = 0.87 (p<0.05). As to not obscure anypossiblecorrelationbetween the visualassessments and the Memory Colour based index, only the special colour rendering indices (apple, banana and orange) have been used in thiscalculation, since a lightsourcehaving terrible colour renderingcapabilities in the blue to purpleregionmightobscurthiscorrelation. • The Pearsoncorrelation has also been calculatedbetween the Thurstonescalingsforattractiveness and the CRI and CQS. The Pearsoncorrelationcoefficientswere: ρCRI,3000K = 0.26 (p=0.50) & ρCRI,4000K = 0.07 (p=0.86) ρCQS,3000K = 0.48 (p=0.20) & ρCQS,4000K = 0.44 (p=0.28) For the samereasondescibedabove, special colour rendering indices 2,3,4,10,11,13 & 14 have been usedfor the CRI, whilefor the CQS special indices 7-13 wereselected. Kevin Smet – Analternative colour rendering index Kevin.Smet@kahosl.be 24

  25. Plannedexperiments • Extend special indices into the red region: strawberry yoghurt, ham, bacon,… • Addsomelesssaturatedobjects. • Try and get a similarityfunctionforCaucasian skin. • Extendnumber of observersoneach object. • Performvalidationexperimentswith a set of test lampshaving low CRI but high visualappreciation and withan object set that is notlimited to the green-redregion! • Change to an even more perceptually uniform colour space: eg. IPT? Kevin Smet – Analternative colour rendering index Kevin.Smet@kahosl.be 25

  26. References • Bartleson, C. J. (1960). Memory colors of familiar objects. J. Opt. Soc. Am., 50, 73–77. • Berns, R.S. & Gorzynski, M.E. (1991). Simulating surface colors on CRT displays: the importance of cognitive clues. Proc. AIC Colour and Light, 91, 21-24. • Brainard D.H., (1998). Color constancy in the nearly natural image. J. Opt. Soc. Am. A, 15, 307-325. • Guan, S. & Luo, M.R. (1999a). Investigation of parametric effects using small colour differences pairs. Col. Res. Appl., 24, 331–343. • Guan, S. & Luo, M.R. (1999b). A colour-difference formula for assessing large colour-differences. Col. Res. Appl., 24, 344-355. • Jost-Boissard, S., Fontoynont, M., & Blanc-Gonnet, M., (2009). COLOUR RENDERING OF LED SOURCES: VISUAL EXPERIMENT ON DIFFERENCE, FIDELITY AND PREFERENCE. Proc. CIE Light and Lighting conference. Budapest. Hungary. 27-29 may 2009. • Seim, T. & Valberg, A. (1986). Towards a uniform color space. A better formula to describe the Munsell and OSA color scales. Col Res. Appl.,11, 11–24. • Xu, H., Yaguchi, H. & Shioiri S. (2001). Estimation of Color-Difference Formulae at Color Discrimination Threshold Using CRT-Generated Stimuli. Optical Review, 8 (2), 142-147. • Yendrikhovskij, S. N., Blommaert, F. J. J., De Ridder, H. (1999). Representation of memory prototype for an object colour. Col. Res. Appl., 24 (6), 393–410. Kevin Smet – Analternative colour rendering index Kevin.Smet@kahosl.be 26

  27. Kevin Smet – An alternative colour rendering index

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