1 / 27

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 .

rhea
Télécharger la présentation

An alternative colour rendering index based on memory colours

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  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

More Related