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Best lighting for naturalness and preference

Osamu Masuda # $Centro de Fısica, Universidade do Minho, Braga, Portugal

Sergio M. C. Nascimento # $Centro de Fısica, Universidade do Minho, Braga, Portugal

Spectral optimization for naturalness and preference wascarried out empirically in a set of psychophysicalexperiments in which observers adjusted the spectralcomposition of the illumination to render commercialfood counters containing a variety of fruits andvegetables as well as meat and fish. The scenes weresimulated with high chromatic precision on a calibratedcomputer monitor from data obtained by hyperspectralimaging. The illuminants were daylight-like and theirmetamers, representing a set of nearly arbitrary spectra.For daylights, the most natural colors were producedwith illuminants with an average correlated colortemperature (CCT) of 6040 K and the most preferredcolors with an average CCT of 4410 K. For metamers, theCCT for the two conditions were a little higher than fordaylights, and the corresponding spectra wereconsiderably different from daylight with characteristicpeaks at both ends of the visible band and at about 490nm and 560 nm. When compared directly with daylights,these metamers were preferred for most of the scenes.It was hypothesized that observers’ choices may bedetermined by the chromatic volume and the symmetryof the color distributions: The best illuminants forpreference produced larger gamuts, and the bestilluminants for naturalness produced gamuts with aspectratios closer to unity, i.e., more symmetricallydistributed.

Introduction

Most of the visual stimuli for humans are illumi-nated objects reflecting to our eyes a fraction of thelight impinging on them. Consequently, the colorperception of complex scenes is influenced, amongother factors, by the spectrum of the illumination(Shevell & Kingdom, 2008). Natural daylight isvariable both spectrally and in intensity, e.g., during theday or at different locations (Hernandez-Andres,Romero, & Lee, 2001; Hernandez-Andres, Romero,Nieves, & Lee, 2001; Judd et al., 1964); artificialillumination may vary even more dramatically, e.g.,

from incandescent to discharge lamps (CIE, 2004;Thornton, 1973). Nevertheless, the visual system hasthe ability to compensate to some extent for thesevariations and to recover object colors reliably undernatural illumination (Granzier, Brenner, & Smeets,2009) and under artificial ones (Olkkonen, Hansen, &Gegenfurtner, 2009) almost with constant colors. Colorconstancy is, however, not perfect (Foster, 2003, 2011),and the effects of different lighting on the color andconspicuity of objects can be quite large and aretypically addressed in color rendering (Schanda, 2007).

The main aspects to be considered in color renderingare fidelity, appeal or preference, and color discrimi-nation. Each is typically equated in terms of indicesbased on perceptual assumptions and on psychophys-ical data (for a review of color rendering indices seeGuo & Houser, 2004). The general color renderingindex (CRI) standardized by the CIE (1995) measuresfidelity or degree of naturalness of the colors renderedby an illuminant. In its definition, the main assumptionis that the most natural colors are produced by daylightor incandescence. The impression of appeal or prefer-ence was first quantified by Judd (Judd, 1967;Thornton, 1974) based on empirical work on colormemory (Bartleson, 1960; Newhall, Burnham, & Clark,1957) and color preference (Sanders, 1959). Thepotential for color discrimination of an illuminant isquantified by indices related to the color gamutspanned by a set of colored samples or scenes (Linhares& Nascimento, 2012; Rea & Freyssinier-Nova, 2008;Thornton, 1972; Xu, 1993, 2012) that have been used indeveloping illuminants with high discriminability(Masuda & Nascimento, 2012; Thornton, 1973). Morecomplex indices representing combinations of theseperceptual aspects have also been synthesized andevaluated (Davis & Ohno, 2010; Smet, Ryckaert,Pointer, Deconinck, & Hanselaer, 2011a).

The empirical basis for the assumptions underlyingcolor rendering and the testing of the rendering indiceshas, however, been constrained to physical existinglight sources. Most of the psychophysical testing has

Citation: Masuda, O., & Nascimento, S. M. C. (2013). Best lighting for naturalness and preference. Journal of Vision, 13(7):4, 1–14, http://www.journalofvision.org/content/13/7/4, doi:10.1167/13.7.4.

//Xinet/Production/j/jovi/live_jobs/jovi-13-07/jovi-13-07-01/layouts/jovi-13-07-01.3d � 4 June 2013 � 2:24 pm � Allen Press, Inc. � MS#: JOV-03627-2013

Journal of Vision (2013) 13(7):4, 1–14 1http://www.journalofvision.org/content/13/7/4

doi: 10 .1167 /13 .7 .4 ISSN 1534-7362 � 2013 ARVOReceived March 4, 2013; published June 7, 2013

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been based on rating with LED or standard illuminants(e.g., Schanda &Madar, 2007; Smet, Ryckaert, Pointer,Deconinck, & Hanselaer, 2010, 2011b). The popular-ization of solid-state lighting has shown the potentialfor lighting spectra without constraints and challengedthe existing knowledge based on a limited set ofilluminants.

Computational spectral design and optimization hasbeen carried out mainly assuming LEDs (Berns, 2011;Zukauskas, Vaicekauskas, Ivanauskas, Vaitkevicius, &Shur, 2008). These studies have produced usefulinformation but not direct experimental data from aperceptual point of view. Empirical optimization hasbeen carried out with lights metameric of D65 and haveshown that observers require spectra more structuredthan daylight to produce the best impression ofnaturalness and preference (Nascimento & Masuda,2012).

The goal of the present study is to determinepsychophysically the best spectral power distributionsto render natural scenes the most natural and the mostpleasant. The experiments were based on imagesrepresenting simulations of real food counters obtainedby spectral imaging carried out in a local supermarket,and the illuminants tested had a wide range ofchromaticities and almost arbitrary spectral distribu-tion. Human color vision is thought to have evolved todetect or discriminate ripe food from background orunripe food (Mollon, 1989; Surridge, Osorio, &Mundy, 2003). Finding optimal lighting for food can beof practical benefit and contribute to the understandingof the mechanisms of human color vision. This studywas conducted regardless of energy-efficiency aspectsor the present availability of light-emitting materialswith the specific spectral compositions tested (Protz-man & Houser, 2006).

General methods

Hyperspectral images of commercial foodcounters

Hyperspectral images of commercial food counterswere acquired in a local supermarket. The countersdisplayed vegetables, fruits, meat, and fish (see Figure 1for pictures of the counters imaged). These types ofobjects are appropriate for testing visual aspects ofillumination and have been used in classical worksalthough with much more spectrally constrained lightsources (Thornton, 1974). The existing illumination ofthe counters was turned off and replaced by two metal-halide discharge lamps of 1000 W (GW 84 662; Gewiss,Cenate Sotto, Italy), each positioned approximately at458 relative to the areas imaged. The correlated colortemperature (CCT) of the light sources was 7600 K,and their spectral profiles were stable over the scenes.

Spectral data were acquired over the range of 400–720 nm at 10 nm intervals using a fast-tunable liquid-crystal filter (VariSpec VIS-10; Cambridge Research &Instrumentation, Hopkinton, MA) and a low-noisePeltier-cooled digital camera with a spatial resolutionof 1344 · 1024 pixels and 12-bit output (ORCA-AGCA4742-80-12AG; Hamamatsu Photonics, Hamamat-su, Japan) in a configuration similar to the onedescribed in detail elsewhere (Foster, Amano, Nasci-mento, & Foster, 2006; Foster, Nascimento, & Amano,2004).

The spectral reflectance of each pixel was estimatedfrom the hyperspectral data by dividing the image datafor each wavelength by the spectrum of the lightreflected from a gray reference surface with a known

Figure 1. Scenes tested in the psychophysical experiments. The scenes were digitalized by hyperspectral imaging in a local

supermarket. The number on each image is for labeling and was not displayed in the experiments. Images 1–3 represent fruits,

images 4–6 vegetables, images 7–9 meat, and images 10–12 fish.


Journal of Vision (2013) 13(7):4, 1–14 Masuda & Nascimento 2

spectral reflectance placed in the scene. The grayreference surface was always a flat surface painted withMunsell N7 matt emulsion paint (VeriVide Ltd.,Leicester, UK). Images were corrected for noise, straylight, and for the effects of transmission through theoptical system, but no compensation was introducedfor the spatial variations in intensity of the lightsources. Thus, the spectral reflectance functions esti-mated were spatially modulated by these spatialvariations in intensity, and everything is as if theilluminants synthesized for the experiments reproducedthe intensity profiles of the light sources at the time ofdata acquisition. The spatial resolution of the hyper-spectral system was at least as good as that of thehuman eye at the same viewing distance (Foster et al.,2006). The accuracy of the system in recovering spectralreflectance functions is acceptable for visual experi-ments as the spectral error is about 2% and thecolorimetric error is about 2.2 in CIELAB color space(Carvalhal, 2004; Foster et al., 2006; Nascimento,Ferreira, & Foster, 2002).

Illuminants

Two types of illuminant were used in this study:daylight-like illuminants and the metamers of thedaylight-like illuminants.

Daylight illuminants

Daylight-like illuminants were synthetized fromJudd’s daylight spectral basis functions (Judd et al.,1964) with variable coefficients such that their colordefined a chromaticity grid over and around thePlanckian locus. Figure 2 represents this grid expressedin the CIE 1960 uniform chromaticity scale (UCS)diagram. The grid points had the CCT in the range2222–20000 K. The color temperature (CT) of theidealized Planckian radiator is the absolute tempera-ture of the radiator, and it is related with the spectralpower distribution it irradiates. For a real radiator,like a light source, the concept of CCT applies instead.It is the temperature of the Planckian radiator whosechromaticity is closest to that of the light source on theCIE 1960 UCS diagram. We introduced here thechromaticity difference (DC) as the distance betweenthe chromaticities of the light source and of thePlanckian radiator of the same CT on the CIE 1960UCS diagram (CIE, 1995). A positive DC means thatthe chromaticity is above the Planckian locus, and anegative DC is below the locus. To guarantee morevisual uniformity, the CT were equally spaced inreciprocal color temperature (RCT) (Wyszecki &Stiles, 1982) by 25 MK�1. The points on the linesorthogonal to the Planckian locus were in the range�0.01 toþ0.01 from the locus at an interval of 0.002 inDC.

Metamers of daylight

At each point on the grid represented in Figure 2,1000 metamers were generated using Schmitt’s simpleelements method (Schmitt, 1976). These metamericilluminants had almost arbitrary spectra. The spectralrange was 400–720 nm, and the spectral resolution was10 nm. The simple elements at each chromaticity are allthe spectra with three spectral bands producing thatchromaticity. Thus, for each grid point, all corre-sponding simple elements were computed, and the 1000metamers were obtained by linear combinations of thesimple elements. To obtain a reasonable range ofspectral profiles, the metamers were generated to beuniformly distributed with regard to the spectraldifference against the corresponding daylight spectrum.This difference was quantified by an index defined bythe following equation:

d ¼XN

k¼1

jfk �Dkj ð1Þ

where N is the number of spectral bands (33), fk is theintensity of the metamer f at the kth spectral band, andDk is the intensity of the daylight at the kth spectralband. d is related to the spectral similarity of themetamer to the daylight with the same chromaticity. Italso measures, indirectly, the degree of spectralsmoothness. Metamers with low values of d are

Figure 2. Illuminant chromaticities tested expressed in the CIE

1960 UCS diagram. The illuminants were synthetized from

Judd’s daylight spectral basis functions. The grid points had

correlated color temperatures in the range 2222–20,000 K

equally spaced in reciprocal color temperature at an interval of

25 MK�1. The points on the lines orthogonal to the Planckian

locus were in the range �0.01–þ0.01 from the locus at an

interval of 0.002 in UCS units.



spectrally close to natural daylight and smooth. On thecontrary, those with large d are less natural and moreirregular and spiky (Nascimento & Masuda, 2012).Figure 3 shows the average spectrum of the simpleelements at the grid point (CCT, DC) ¼ (6667 K, 0).The energy of each simple element was normalized suchthat

PNk¼1 fk ¼ 1. The average spectrum has four peaks

at both ends of the visible band and at 490 nm and 570nm. The wavelengths of the central two peaks variedwith each grid point, but this characteristic four-peakpattern in the spectrum appeared at all grid points. Thisspectral structure reflects natural constraints associatedto the chromaticity region considered.

Stimuli

Stimuli for the experiments were synthetized bymultiplying the spectral reflectance functions estimatedfor each pixel from the hyperspectral data by thespectral distributions of the illuminants. In this way, aspectral radiance and a color were obtained for eachpixel. The images were displayed on an LCD monitor(CA750; Samsung, Seoul, South Korea) controlled by avideo board (ViSaGe Visual Stimulus Generator;Cambridge Research Systems, Rochester, Kent, UK) in24-bits-per-pixel true-color mode driven by a PC. Themonitor was calibrated in color and luminance with atelespectroradiometer (PR-650 SpectraScan Colorime-ter; Photo Research, Chatsworth, CA). The imagessubtended a 408 · 308 visual angle and were observedat 60 cm distance. Images were subsampled every otherpixel from the original resolution of 1344 · 1024 pixels,then trimmed about 20–30 pixels from an edge to deletethe reflectance standard from the scene. The averageluminance of each displayed image across pixels was 15cd/m2.

Figure 1 shows the 12 scenes tested. Three representfruits, three vegetables, three various types of meat, andthree several sorts of fish.

Colorimetric accuracy

The colorimetric performance of the monitor wasbetter for food than that of a good CRT because it hada wide gamut in the red-yellow area. The maximumluminance of the LCD was lowered from its originalmaximum (280 cd/m2) to 130 cd/m2 to achieve a goodtone reproduction. Figure 4 shows the error of thedisplay calibration. Small black dots are the grid pointsshown in Figure 2. Red circles are the actuallymeasured chromaticities of the grid points with PR-650. Red circles were measured only along the DC of�0.01, 0.00, andþ0.01. The mean error between the redcircles and the corresponding grid points was 0.003,which is less than a half of the just noticeable difference(JND) around this chromaticity area (0.007) estimatedas thrice the mean radius of the MacAdam ellipse(MacAdam, 1942). The intended luminance was 15 cd/m2, and the actually reproduced mean luminance was15.11 6 .02 (standard deviation). The three red pointsat the upper right of the grid (DC¼þ0.01, CCT � 2500K) were out of the display gamut, but these points wereactually not selected by the observers.

Table 1 shows the mean reproduction errors of 15color samples defined in the Japanese IndustrialStandard (1990) Z8726 simulated on the monitor andmeasured with PR-650. Fourteen of them are the sameas the color samples defined in CIE 13.3 (CIE, 1995).The color difference for each pixel was defined as

DE*ab ¼

ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiðL*

2 � L*1Þ

2 þ ða*2 � a*

1Þ2 þ ðb*

2 � b*1Þ

2q

where (L*1, a

*1, b

*1) and (L*

2, a*2, b

*2) are the CIELAB

coordinates of the intended and measured colors,respectively. Most of the errors within the gamut wereclose to 2.2, the JND for complex images in CIELAB

Figure 3. Average spectrum of the simple elements at (CCT, DC)

¼ (6667 K, 0). Error bars show the standard errors at each band.

Figure 4. Calibration of the monitor. Black dots are the intended

chromaticities of the grid. Red circles are the actually measured

chromaticities. Red circles were measured only along the DC of

�0.01, 0.00, andþ0.01. The mean error between the red circles

and the corresponding grid points was 0.003, which is smaller

than the just noticeable difference (JND) around this chroma-

ticity area (0.007) estimated as the thrice of the mean radius of

the MacAdam ellipse (MacAdam, 1942).



(Aldaba et al., 2006; Song & Luo, 2000). The grid pointat (CCT, DC)¼ (2222 K, 0.01) was out of the monitorgamut.

When the color of a pixel was outside the gamut, thecolor was clipped to the closest RGB value. Figure 5shows the histograms of the mean color errors due tothe gamut limit of the display expressed as the meancolor difference across pixels in DE*

ab between thecolorimetrically intended and actually achievable im-ages chosen by the observer in each trial. In Experiment1, the mean error for 96.4% of the trials was less thanthe JND (2.2). The trials with errors more than twicethe JND (4.4) were 0.4%. In Experiment 2, 90.9% of thetrials had mean errors less than the JND, and 4% of thetrials had mean errors more than twice the JND.

Observers

There were six observers. All but one of the authors(OM) were naıve to the purpose of the experiment.Each observer had normal or corrected-to-normalacuity and normal color vision accessed by theRayleigh anomaloscope and Ishihara plates. Five ofthem are 20- to 21-year-old females, and the other was

a 42-year-old male. The experiments were performed inaccordance with the tenets of the Declaration ofHelsinki, and informed consent was obtained from allobservers.

Experiment 1: Daylights

In Experiment 1, the goal was to determine thedaylight-like illuminants producing the most naturaland the most preferable appearance. The illuminantstested were synthetized from the daylight basisfunctions as described above, and the task of theobservers in each trial was to select one of theilluminants from the chromaticity grid represented inFigure 2. Two conditions were tested. In one, thenaturalness condition, the observers were instructed toselect the illuminant on the scene such that the colors ofthe objects appear the most natural. In the other, thepreference condition, observers were instructed to selectthe illuminant such that the appearance of the scenewas the most pleasant or preferable for them. Theinstructions to the observers were written and shown tothe observers at the beginning of each experimentalsession. None of the observers found the instructionsambiguous or unclear.

Procedure

In each trial, the chromaticity of the initial illumi-nant was selected randomly from the grid. The observerthen adjusted the chromaticity of the illuminant withfour buttons on a joypad. Each of the four buttonscorresponded to one incremental or decremental stepon the grid in CCT or in DC. The switching betweendifferent illuminants on the grid was fast, less than 0.5s. When the observer was satisfied with the setting, s/hepressed two dedicated buttons in a specific order torecord the result. Each scene was repeated three timesper session, condition, and observer. There was noadaptation period before each trial or session. Eachobserver did two sessions for each condition. Condi-tions and scenes were tested in random order.

Results

Figure 6 shows the results obtained in the twoconditions averaged across all scenes and observers.The average CCT and DC were computed from thechromaticity of the average spectra. Averaging directlyin RCT and DC axes is less meaningful as these are notaxes of a chromaticity diagram. The diagram expressesthe data vertically in DC. For readability, thehorizontal axis is labeled in CCT, but it is spaceduniformly in RCT (25 MK�1/tick). The error bars show

CCT (K)

20,000 6667 4000 2857 2222

DC

0.01 2.89 2.14 2.73 3.09 N/A

0.00 2.99 2.80 2.18 3.12 3.22

�0.01 2.69 2.25 2.23 2.28 3.63

Table 1. Mean errors of 15 reproduced color samples in DE*ab.

Figure 5. Histograms of the colorimetric errors due to the gamut

limit in Experiment 1 (red striped bars) and Experiment 2 (gray

bars). The errors were expressed as the mean color difference in

CIELAB across the pixels between the intended and actually

achievable images selected by the observer in each trial. In

Experiment 1, the mean errors for 96.4% of the trials were less

than the JND. In Experiment 2, 90.9% of the trials had errors

less than the JND.



the standard errors of the means, but these are nowcomputed directly from the DC and RCT obtained ineach trial.

The CCT of the most natural daylight was 6040 K,and the CCT of the most preferred one was 4410 K.The DC of the most natural daylight was�0.0035, andthe DC of the most preferred was �0.0036, both ofwhich were considerably different from the Planckianlocus (DC ¼ 0) and from the daylight locus (DC ¼0.003). Both daylights are shifted to a purplishdirection below the locus.

Figure 7 shows the average CCT obtained across allobservers for each scene. The preferred CCTs wereconsistently lower than the natural ones regardless ofthe scene contents.

Experiment 2: Metameric lights

In Experiment 1, the illuminants were constrained todaylight-like spectra. In Experiment 2, this constraintwas relaxed, and observers were able to selectilluminants with almost arbitrary distributions. Theilluminants tested had chromaticities at and around theaverage chromaticity obtained for daylights in Exper-iment 1 for each scene, observer, and condition andwere metamers of the daylight synthesized as describedin the General methods section. The conditions of theexperiments were the same as in Experiment 1, i.e.,naturalness and preference.

Procedure

Experiment 2.1

The experiment was carried out in two parts. In thefirst part (Experiment 2.1), a first set of five bestmetamers was obtained by testing at five chromaticities

at and around the chromaticity obtained in Experiment1 for each scene and observer. Then, in the second part(Experiment 2.2), the best metamer was obtained bytesting the five candidates obtained in Experiment 2.1.

To select the testing points for Experiment 2.1, thechromaticities obtained in Experiment 1 were averagedfor each scene, each observer, and each condition, andthe chromaticity in the grid nearest to the average wasselected as the central (C) point. Then, four grid pointssurrounding C were computed: The upward (U) pointwas 1 standard deviation (SD) in DC away from C inthe incremental DC direction; the SDs were calculatedfrom the results in Experiment 1 for each scene,observer, and condition. In the same way, thedownward (D) point was 1 SD away from C but in theopposite direction. The leftward (L) point was 1 SD inRCT away from C in the decremental RCT direction,and the rightward (R) point was 1 SD away in theopposite direction. If any chromaticity was out of thegrid, the nearest point in the grid was selected instead.Figure 8 shows an example of the method of selectingthe testing chromaticities.

Observers were instructed to select the most appro-priate metamer from the metamer set for each of thefive chromaticity points, scenes, and conditions.

The metamer set at each chromaticity was ordereddifferently for the two conditions. For naturalness, themetamers were ordered linearly according to their CIEgeneral CRI. For the preference condition, they wereordered linearly according to the product of their CRIand their chromatic diversity indices (CDI) (Linhares &Nascimento, 2012). This ordering was adopted to makethe changes in appearance more directly related to eachcondition tested and to facilitate adjustment for theobservers, but it is not expected that the ordering itselfinfluenced the outcome of the experiments (Nascimento& Masuda, 2012).

Figure 6. Results obtained in the two conditions of Experiment 1

averaged across all images and observer. Error bars show the

standard errors of the means. For readability the horizontal axis

is labeled in CCT but is spaced uniformly in RCT.

Figure 7. Average CCT across all observers for each scene. Filled

symbols connected by solid lines represent the naturalness

condition and open symbols connected by dotted lines

represent the preference condition. Error bars show the

standard errors of the means. For readability the vertical axis is

labeled in CCT, but is spaced uniformly in RCT.



The observers changed the metamer by scrolling theordered set in either direction with two buttons or ananalog stick on the joypad. The step by the two buttonswas 1% of the full scale in CRI or the product of CRIand CDI. The observers were also able to adjust themetamer by the analog stick. The step by the analogstick was proportional to the tilt angle of the stick, andthe maximum step was 5% of the full scale. The startingpoint was randomly selected from among the 1000metamers at each chromaticity. The adjustment of theorder was in a circular fashion, that is, when the nextmetamer was calculated to be out of the scale, theactual next metamer was bounced back in the oppositedirection by the amount of excess. In this way, theobserver was not able to know the ends of the scaleexplicitly.

When the observer was satisfied with the setting, s/hepressed two dedicated buttons in a specific order torecord the result. Each scene was repeated three timesin one session for each of the five chromaticities. Theorder of the trials was randomized for each chroma-ticity, observer, and condition; the order of the fivechromaticities was also randomized. One sessionconsisted of 36 trials (3 repetitions · 12 scenes).Sessions were repeated twice, and the total number oftrials for each chromaticity, observer, and conditionwas 72.

Experiment 2.2

The spectra of the six metamers obtained inExperiment 1 for each scene, chromaticity, condition,and observer were averaged and constituted the testingset in Experiment 2.2. The observer selected the bestmetamer from this set of five average spectra (one ineach chromaticity tested). The testing methodology was

the same as in Experiment 2.1 except that the set oftesting metamers was now of only five. Each scene wasrepeated six times for each condition and eachobserver. The order of the trials was randomized foreach observer and criterion.

Results

Correlated color temperature and chromaticity difference

Figure 9 shows the results obtained in Experiment2.2 in the two conditions averaged across all scenes andobservers. The average CCT and DC were computedfrom the average spectra, but the standard errors werecalculated directly from the CCT and DC obtained ineach trial. The diagram expresses the data vertically inDC and horizontally in CCT.

Both metamers are located below the Planckianlocus. The most natural CCT was 6200 K, and the mostpreferred one was 4550 K. These values were a littlehigher than those obtained with daylights in Experi-ment 1. The preferred CCT was considerably differentfrom that of D65, but the natural one was close to thatof D65.

Figure 10 shows the average CCT across observersfor each scene. The CCTs selected in Experiment 2.2were slightly, but almost consistently, higher than thosewith daylights obtained in Experiment 1 for bothconditions.

Spectra

Figure 11 shows the averaged best spectra selectedby observers in the naturalness condition: Figure 11a isthe average across all the observers and scenes, andFigure 11b is the averages across all the observers foreach food category. The error bars in Figure 11a

Figure 8. Example of the selection of the chromaticities for

Experiment 2.1. U is 1 SD (0.04 in DC) shifted upward from C,

and D is shifted downward by the same amount in the opposite

direction. L is shifted 1 SD (100 MK�1 in RCT) leftward from C,

and R is shifted 1 SD by the same amount in the opposite

direction. The chromaticity of C and SDs were obtained from the

corresponding results in Experiment 1.

Figure 9. The filled symbols show CCT and DC obtained in the

two conditions of Experiment 2.2 averaged across all scenes

and observer. The error bars show the standard errors of the

means. For readability the horizontal axis is labeled in CCT but is

spaced uniformly in RCT. The faded open symbols are the replot

of Figure 6.



represent the standard errors at each spectral band. Inthe spectra shown in Figure 11, characteristic peakswere found at both ends of the visible band and atabout 490 nm and 560 nm. The spectral differenceindex d of Figure 11a was 0.49.

Figure 12 shows the averaged best spectra selectedby observers in the preference condition: Figure 12a isthe average across all the observers and scenes, andFigure 12b is the averages across all the observers foreach food category. The error bars in Figure 12arepresent the standard errors at each spectral band.Characteristic peaks similar to those obtained in thenaturalness condition were found although the peak at560 nm is less prominent and less sharp. The spectraldifference index d of (Figure 12a) was the same as thatof the naturalness condition.

Experiment 3: Control

The results obtained in Experiment 2 were surprisingbecause they mean that the observers preferred artificialspectra to daylight to produce the impression ofnaturalness. The intention of Experiment 3 was toconfirm that the spectra obtained in Experiment 2 were,in fact, preferred to daylight by direct comparison.

Procedure

In a two-interval forced-choice procedure, theobservers compared two images. One was always thesimulation of a scene rendered under the best metamerobtained in Experiment 2.2 for each scene, observer,and condition; the other represented the same scenerendered under daylight with a chromaticity aroundthat of the best metamer. The chromaticity of thisdaylight followed a normal distribution with the meanof that of the metamer and the standard deviationobtained in Experiment 1 for each observer, scene, andcondition. The task of the observers was to select themore natural or the more preferred image according tothe condition tested.

Each trial was started with a button pressed by theobserver. One of the two images, chosen randomly, wasdisplayed for 500 ms followed by a dark screen for 500ms. Then, the other image was displayed for 500 ms.The observer selected one of the two for each conditionby pressing one of two buttons. Only one scene wasselected for this experiment for each food category(scene 2 for fruits, scene 6 for vegetables, scene 10 formeat, and scene 13 for fish). Each scene was repeated 12times for each observer and condition.

Figure 10. Average CCT obtained with the metamers (M; solid

symbols) for each scene across all the observers in the

naturalness (a) and preference (b) conditions. The error bars

show the standard errors of the means. The CCT obtained with

daylights (D; dashed lines) in Experiment 1 are also shown for

comparison.

Figure 11. Average spectra selected by observers in the

naturalness condition. (a) The average across all the observers

and categories. The error bars show the standard errors at each

band. The gray dotted line is the average natural daylight

obtained in Experiment 1 for comparison. (b) The averages

across all the observers for each category.



Results

Table 2 shows the percentages and p values(binomial test) of the choices of metamers againstdaylights. The best metamers were selected morefrequently for each condition than the daylights withthe same chromaticities within the range of color-matching error. The difference in the percentage fromthe chance level was statistically significant in all thefood categories with the exception of fish in thepreference condition.

Discussion

Daylights

In Experiment 1, the daylights selected for natural-ness and preference had a CCT, on average, of 6040 Kand 4410 K, respectively. The natural CCT was close to6500 K, the CCT recommended for the assessment ofthe color of foods by the International Organization forStandardization (ISO, 1999), but was very differentfrom 3000 K, the common practice in most supermar-kets (MacDougall, 2002). On the other hand, thepreferred CCT was different from both 6500 K and3000 K. Although the CCT varied across scenes and

observers, they were systematically lower for preferencethan for naturalness. The value of 4410 K¼ 227 MK�1

obtained in Experiment 1 was relatively close to theresults of experiments in which observers adjusted theCCT of daylights such that they produced the bestvisual impression of artistic paintings and in which thedistribution of observers’ preferences had a maximumat a CCT of about 5100 K ¼ 196 MK�1 (Pinto,Linhares, & Nascimento, 2008).

The daylights obtained for naturalness and prefer-ence had chromaticities below the daylight (DC ¼0.003) and Planckian (DC ¼ 0) loci, i.e., they wereshifted to a more purplish direction. This curious effectis not predicted by the CRI. Figure 13 shows apseudocolor map representing CRI for the daylightstested. If this index was a good predictor of naturalnessor preference, the illuminants selected by observersshould be close to the areas of larger values, that is,close to the daylight locus.

Why does the preferred CCT have a lower value thannatural CCT? A possible reason for this effect is thatobservers prefer scenes that are more colorful, corre-sponding to a larger color gamut. This would beconsistent with experiments in which the image quality ismaximum when average chroma is higher than thatobtained with natural illuminants (Fedorovskaya, DeRidder, & Blommaert, 1997). Figure 14a shows thepseudocolor map of the convex hull volume expressed inCIELAB space of the Munsell set rendered by thedaylights tested. The volume has a maximum close tothe average chromaticity for preference (open circlesymbol). It also increases in the direction of negativeDC, suggesting that scenes can look more colorful orvivid with these purplish daylights. This result obtainedwith the Munsell set also holds for the group of scenestested. The color volume map of each scene wasnormalized, and the result was averaged across all scenestested. The CCT producing the maximum chromaticvolume of this average map was 4444 K whereas theaverage experimental data for preference across thesame scenes was 4410 K. Figure 15 compares thevolumes for the preference and naturalness conditionsfor the 12 scenes tested. The illuminant for each sceneand condition was averaged across all observers. Thetrend line fitted to the data is steeper than the diagonal

Figure 12. Average spectra chosen by observers in the

preference condition. (a) The average across all the observers

and categories. The error bars show the standard errors at each

band. The gray dotted line is the average preferred daylight

obtained in Experiment 1 for comparison. (b) The averages

across all the observers for each category.

Fruit Veg Meat Fish All

Naturalness

% 65.3 72.2 59.7 70.8 67.0

p ,0.01 �0.01 0.04 �0.01 �0.01

Preference

% 63.9 76.4 73.6 56.9 67.7

p ,0.01 �0.01 �0.01 0.10 �0.01

Table 2. The percentages and p values of the direct choices ofmetamers against daylights.



line, which means preferred images were more colorfulthan the corresponding natural images.

The spectra of conventional natural lighting havebeen assumed with chromaticities on the Planckian ordaylight loci, but the data obtained here suggests thatthis constraint might be unnecessary as larger colorvolume is obtained for lower or more purplishchromaticities.

What determines CCT for naturalness? A possiblefactor is the distribution of chromaticities rather thanglobal volume. To investigate this possibility, the colorsof the Munsell set under the daylights found inExperiment 1 were computed and expressed in CIE-LAB space. Figure 16b and Figure 16d show thecorresponding projections in the (a*, b*) plane. Ellipsescovering 95% of the points were fitted to each data set,and their ratios of the lengths of the shorter axis tothose of the longer ones were calculated. The aspectratio of the ellipse for the natural daylight (b; 0.859) iscloser to the unity than that for the preferred daylight(d; 0.819), meaning a more symmetrical distribution ofcolors.

Figure 17 shows the map of the aspect ratios of theellipses fitted to the Munsell set for all daylights tested.The data obtained for naturalness is close to themaximum of the map, supporting the hypothesis thatthis ratio influences naturalness.

These results obtained with the Munsell set also holdfor the food scenes tested. Figure 18 compares theaspect ratios of the ellipses fitted to the image colorgamuts between the preference and naturalness condi-tions for the 12 scenes tested. The illuminant for eachscene and condition was averaged across all observers.Most points are below the diagonal line, which meansimages in the naturalness condition have more sym-metrical color distribution than those in the preferencecondition. Means of the ratios across the images were0.498 for naturalness and 0.472 for preference.

Metamers

In Experiment 2, the CCTs obtained with metamerswere 6200 K for naturalness and 4550 K for preference.They were a little higher than those obtained withdaylights. The DC obtained for the natural metamerwas close to that for natural daylight. However, the DC

Figure 13. The pseudocolor map of CRI corresponding to the

daylights tested. The symbols show the average psychophysical

data obtained in Experiment 1. Standard errors are smaller than

the symbol size.

Figure 14. Pseudocolor map of the convex hull volume

expressed in CIELAB space of the Munsell set rendered by the

daylights tested (a) and by the metamers that maximize the

volume at each grid point (b). Open square and circle show the

natural and preferred daylights in Experiment 1, and filled

square and circle show the natural and preferred metamers in

Experiment 2.2, respectively. Standard errors are smaller than

the symbol size.

Figure 15. Comparison of volumes by the food images in CIELAB

space between the natural and preferred daylights. The trend

line fitted to the data (solid line) is steeper than the diagonal

(dotted line).



for the preferred metamer was shifted in an even morepurplish direction in relation to the preferred daylight.Figure 14b shows the pseudocolor map of the averageof the convex hull volume expressed in CIELAB spaceof the Munsell set rendered by the metamer producingthe maximum volume at each grid point. The maximumvolume is shifted to a higher CCT in relation to themap for daylights in Figure 14a, suggesting that theshift of CCT in the experimental data is explained bythis shift. Actually, as shown in Figure 16, the preferredmetamer (Figure 16c) had a larger color volume thanthe preferred daylight (Figure 16d). This resultobtained for the Munsell set generalizes for the foodscenes tested as shown in Figure 19.

A similar shift can be observed for the aspect ratio.Figure 17b shows the pseudocolor map of the averageaspect ratios of the ellipses fitted to the Munsell setrendered by the metamers producing the top 5% aspectratios at each grid point. The maximum aspect ratio isshifted to a higher CCT in relation to the map fordaylights (Figure 17a), suggesting that the shift in theexperimental data is explained by this shift. Actually asshown in Figure 16, the natural metamer (Figure 16a;0.863) has a higher aspect ratio than the naturaldaylight (Figure 16b; 0.859). This result obtained forthe Munsell set generalizes for the food scenes tested.The means of the ratios across the images were 0.502for the metamers and 0.498 for the daylights.

The relationship found in Figure 18 for daylightsalso holds for metamers. The average aspect ratio ofnatural metamers across images (0.502) was higherthan that of the preferred metamers (0.446).

Thus, symmetry in color distribution seems to becritical to naturalness, and colorfulness seems to becritical to preference. Allowing spectral freedom in theselection of the lighting spectra promotes the expres-sion of these trends, and the spectra producing more

symmetrical color distributions are seen as more

natural even if their spectra themselves are unnatural or

artificial. On the other hand, the spectra producing

higher colorfulness create more preferable chromatic

impressions, also regardless of their origin, natural or

artificial.

Figure 16. Gamuts of Munsell chips projected onto the a*b* plane rendered by (a) the most natural metamer in Experiment 2.2 (b)

the most natural daylight in Experiment 1, (c) the most preferable metamer in Experiment 2.2, and (d) the most preferable daylight in

Experiment 1. The center of an ellipse is the mean of the data points, and the radii correspond to two standard deviations along the

most and least variable direction. An ellipse covers 95% of the data points. The convex hull volumes of the chips in the CIELAB space

are (a) 2.91x105, (b) 2.97x105, (c) 3.24x105, and (d) 3.03x105, respectively. The ratios of lengths of the shorter axes to longer ones are

(a) 0.863, (b) 0.859, (c) 0.837, and (d) 0.817, respectively.

Figure 17. The background pseudocolor plot in (a) shows the

aspect ratios of the ellipses fitted to the gamuts of Munsell

chips rendered by the daylights on the grid. The pseudocolor

plot in (b) shows the average aspect ratios of the ellipses fitted

to the gamut of Munsell chips rendered by the metamers with

the top 5% aspect ratios.



The study described here did not include commonlyused illuminants, like halogen and fluorescent lights,for example. To investigate how the chromatic effectsof these compare with those obtained here experimen-tally, the color volumes and aspect ratios with theMunsell chips were computed for a representativegroup of practical, commonly used illuminants. Theywere three CIE illuminants (A: incandescent lamp; B:direct sunlight; C: average daylight), 27 typicalfluorescent lamps (FL1–6: standard; FL7–9: broad-band; FL10–12: narrow band; FL3.1–3.3: standardhalophosphate; FL3.4–6: deluxe; FL3.7–11: three-band; FL3.12–14: multiband; FL3.15: D65 simulator),five high pressure discharge lamps (HP1: standardsodium; HP2: color enhanced; HP3–5: metal halide),and five white LEDs (LXHL-BW02, LXHL-BW03,LXMLPWC1-0100, LXML-PWN1-0100, and LXML-PWW1-0060 from Luxeon, Philips Lumileds LightingCompany, USA) (CIE, 2004; Linhares & Nascimento,2012). The largest color volume obtained was 3.05 ·105 with FL11, and the highest aspect ratio was 0.862with FL3.15; both were smaller than those obtainedexperimentally in Experiment 2 (3.24 · 105 and 0.863,respectively). Thus, although a direct psychophysicaltest was not carried out, these data suggest that theexperimental metamers we obtained would be preferredto those commonly used illuminants.

This study has shown that in what concernsillumination observers prefer yellowish illuminants,which seems to contradict the fact that people prefermore bluish color for objects. It has been long knownthat people like blue and red more than yellow andorange (Eysenck, 1941), a fact that has been confirmedand explained by quantitative studies (Ling & Hurlbert,2007; Palmer & Schloss, 2010). These studies, however,have focused on abstract uniform patches whereas thepresent study concerns full complex scenes. Still, thisapparent contradiction is puzzling.

Conclusions

The spectra for best lighting for naturalness andpreference were determined psychophysically withstimuli derived from hyperspectral images, simulatingthe illumination by daylights and the metamers ofdaylights. For naturalness, the empirical illuminant hada CCT around 6200 K off the Planckian locus in amore purplish direction. For preference, the illuminanthad a CCT around 4550 K off the Planckian locus toan even more purplish direction. Both spectra differedfrom daylight-like illuminants and had the same fourcharacteristic peaks at both ends of the visible bandsand at 490 and 560 nm. It was hypothesized that theobservers’ choices may be determined by the aspectratio of the color distributions and the colorfulness ofthe scene: The best illuminants for naturalness pro-duced more symmetrical gamuts with more even aspectratios than those for preference, and the best illumi-nants for preference produced more colorful gamuts.

Keywords: color rendering, lighting, color memory,color constancy, naturalness, preference

Acknowledgments

This work was supported by the European RegionalDevelopment Fund through Program COMPETE(FCOMP-01-0124-FEDER-009858) and by NationalPortuguese funds through Fundacao para a Ciencia e aTecnologia (grant PTDC/EEA-EEL/098572/2008). Weare grateful to the supermarket Pingo Doce do BragaParque, Grupo Jeronimo Martins, for the permission toacquire spectral data from their food counters. Wethank Helder Tiago Correia for his cooperation in thehyperspectral imaging and Joao Manuel Maciel Lin-

Figure 18. Comparison of aspect ratios of the color gamuts by

the food images between the natural and preferred daylights.

The daylight for each image and condition were averaged across

the observers.

Figure 19. Comparison of the volumes of the food images in the

CIELAB space between the preferred metamer found in

Experiment 2 and the preferred daylight found in Experiment 1.

The metamer and daylight for each image were averaged across

the observers.



hares for his contribution to the development ofhyperspectral data processing software.

Commercial relationships: none.Corresponding author: Sergio M. C. Nascimento.Email: [email protected]: Centro de Fısica, Universidade do Minho,Braga, Portugal.

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