Colour quality evaluation based on memory colours KaHo Sint-Lieven – K.U.Leuven Light & Lighting Laboratory – ESAT/ELECTA Gebroeders Desmetstraat 1, 9000 Gent (Belgium) Tel: TC1-69 meeting Princeton, june 17th 2010

2 Basic Idea: 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 Referencing is done to memory colours of familiar objects*, NOT to a reference illuminant! Kevin Smet & Peter Hanselaer – A colour rendering metric based on memory colours

Similarity distributions as special CR indicator functions CR&A paper: “Colour appearance rating of familiar real objects” Similarity of object chromaticity X i to memory colour (a i,3,a i,4 ): S i values: hue specific measures for colour rendering/quality Summarizing S a value: S a = geomean(S i ) 3 Kevin Smet & Peter Hanselaer – A colour rendering metric based on memory colours

Validation experiments at Light & Lighting Lab Six 2700K light sources: classic & modern –Fluo. F4, Fortimo with green filter, Nd Inc., LC (WW/G/R/B led cluster), Halogen, RGB 92 observers Familiar object set spans entire hue circle Scheffé paired comparison experiment Five quality descriptors rated on 7 point scale: –Preference, –Fidelity –Vivideness –Naturalness –Attractiveness 4 Kevin Smet & Peter Hanselaer – A colour rendering metric based on memory colours

Validation experiments at Light & Lighting Lab Using the method of Meng, Rosenthal and Rubin 3 for comparing correlated correlation coefficients significant differences were found between the MCRI and all other metrics at the p < 0.1 level. 5 Kevin Smet & Peter Hanselaer – A colour rendering metric based on memory colours Spearman ρpreferencefidelityvividnessnaturalnessattractiveness CIE CRI CQS Philips CRI MCRI

Validation: Jost-Boissard et al 1,2. - Recap of results presented at CIE conference in Vienna, march 2010 Using the method of Meng, Rosenthal and Rubin 3 for comparing correlated correlation coefficients significant differences were found between the MCRI and all other metrics at the p <0.05 level. 1.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; 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) Meng XL, Rosenthal R, Rubin DB. Comparing correlated correlation coefficients. Psychological Bulletin 1992;111: RYG region of hue circleCRICQSPhilips CRIMCRI 3000KPearson ρ Spearman ρ KPearson ρ Spearman ρ Special indices used in recalculation: MCRI (all but smurf & lavender were omitted); CIE CRI (1-4, 9-11 & 13-14); CQS (7-15); Philips CRI (-20°-150°). Kevin Smet & Peter Hanselaer – A colour rendering metric based on memory colours

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

Conclusion An evaluation of the quality of lighting using a metric based on memory colours correlated well with the visual results for preference, fidelity and attractiveness. It was also found to be significantly (p < 0.1) better at predicting the visual ranking of light sources for those quality descriptors. 8 Kevin Smet & Peter Hanselaer – A colour rendering index based on memory colours