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Colour quality evaluation based on memory colours

Colour quality evaluation based on memory colours. TC1-69 meeting Princeton, june 17th 2010. 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 ; peter.hanselaer@kahosl.be.

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Colour quality evaluation based on memory colours

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  1. Colour quality evaluation based on memory colours TC1-69 meeting Princeton, june 17th 2010 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; peter.hanselaer@kahosl.be

  2. Basic Idea: Referencing is done to memory colours of familiar objects*, NOT to a reference illuminant! • The more similar a light source renders the object colours to their memory colours, the better the colour rendering (perceived colour quality). • (*) Smet K, Ryckaert WR, Pointer MR, Deconinck G, Hanselaer P. Colour Appearance Rating of Familiar Real Objects. Colour Research and Application. Accepted for publication 2010. Kevin Smet & Peter Hanselaer – A colour rendering metric based on memory colours

  3. Similarity distributions as special CR indicator functions • CR&A paper: “Colour appearance rating of familiar real objects” • Similarity of object chromaticity Xi to memory colour (ai,3,ai,4): • Si values: hue specific measures for colour rendering/quality • Summarizing Sa value: Sa = geomean(Si) Kevin Smet & Peter Hanselaer – A colour rendering metric based on memory colours Kevin.Smet@kahosl.be 3

  4. Validation experiments at Light & Lighting Lab • Six 2700K lightsources: classic & modern • Fluo. F4, Fortimowith green filter, Nd Inc., LC (WW/G/R/B led cluster), Halogen, RGB • 92 observers • Familiar object set spansentirehuecircle • Scheffépairedcomparison experiment • Fivequalitydescriptorsratedon 7 point scale: • Preference, • Fidelity • Vivideness • Naturalness • Attractiveness Kevin Smet & Peter Hanselaer – A colour rendering metric based on memory colours Kevin.Smet@kahosl.be 4

  5. Validation experiments at Light & Lighting Lab • Using the method of Meng, Rosenthal and Rubin3forcomparingcorrelatedcorrelationcoefficients significant differenceswerefoundbetween the MCRI and all othermetrics at the p < 0.1 level. Kevin Smet & Peter Hanselaer – A colour rendering metric based on memory colours Kevin.Smet@kahosl.be 5

  6. Validation: Jost-Boissard et al1,2. -Recap of results presented at CIE conference in Vienna, march 2010 • Using the method of Meng, Rosenthal and Rubin3for comparing correlated correlation coefficients significant differences were found between the MCRI and all other metrics at the p <0.05 level. • Jost-Boissard S, Fontoynont M, Blanc-Gonnet J. Colour Rendering of LED Sources: Visual Experiment on Difference, Fidelity and Preference. CIE Light and Lighting Conference with Special Emphasis on LEDs and Solid State Lighting Budapest; 2009. • Jost-Boissard S, Fontoynont M, Blanc-Gonnet J. Thurstone scalings for attractiveness of fruit and vegetables under nine 3000K and eight 4000K light sources. (personal communication). 2009. • Meng XL, Rosenthal R, Rubin DB. Comparing correlated correlation coefficients. Psychological Bulletin 1992;111:172-175. Kevin Smet & Peter Hanselaer – A colour rendering metric based on memory colours Kevin.Smet@kahosl.be 6

  7. Validation: Jost-Boissard et al. 3000K lightsources: 4000K lightsources: Kevin Smet & Peter Hanselaer – A colour rendering metric based on memory colours Kevin.Smet@kahosl.be 7

  8. Conclusion Anevaluation of the quality of lightingusing a metricbasedonmemorycolourscorrelatedwellwith the visualresultsforpreference, fidelity and attractiveness. It was alsofound to besignificantly (p < 0.1) better at predicting the visualranking of lightsourcesforthosequalitydescriptors. Kevin Smet & Peter Hanselaer – A colour rendering index based on memory colours Kevin.Smet@kahosl.be 8

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