258—Recent Progress in Color Processing

Abstract

Color-appearance models are used to relate chromatic stimuliviewed under one set of viewing and illuminating condi-tions to a differing set such that when each stimulus isviewed in its respective conditions, the stimuli match incolor appearance. These models assume the observer has asteady-state adaptation to each condition. In practice, ob-servers often view stimuli under mixed adaptation; thiscould occur when viewing CRT and reflection-print stimulisimultaneously. A visual experiment was performed todetermine whether the RLAB color-appearance model couldbe used successfully to generate reflection prints that matchthe appearance of the CRT when viewed under mixed statesof adaptation and in turn as stand-alone images viewedunder a single state of adaptation. Sixteen observers viewedfour pictorial images displayed on a D65 balanced CRTdisplay in a room lit with cool-white fluorescent luminaries.The RLAB color-appearance model was used to calculatecorresponding images where the observer’s state of chro-matic adaptation was assumed to be one of the following:adaptation to each device condition, a single adaptation atthe midpoint of the two device conditions, adaptation to theCRT condition and a print adaptation shifted 25% towardthe CRT condition, adaptation to the print condition and aCRT adaptation shifted 25% toward the print condition, anda CRT condition shifted 25% toward the print condition anda print condition shifted 25% toward the CRT condition.Each condition was compared pairwise and Thurstone’slaw of comparative judgments was used to calculate inter-val scales of quality. Observers first judged the reflectionprints adjacent to the CRT display selecting the imageclosest in color appearance to the CRT image; they alsocategorized the closest image as “acceptable, “ “marginallyacceptable,” or “not acceptable.” The images were againscaled except the display was turned off; this determined thebest stand-alone color reproduction. The observers deter-mined that images generated where it was assumed that theCRT adaptation was shifted 25% toward the print conditionand a print adaptation was shifted 25% toward the CRTcondition produced both the closest match to the CRT displayand the best stand-alone image. The mixed-adaptation matches

were acceptable or marginally acceptable on average 84%of the time. This adaptational condition produced the mostpreferred stand-alone images due to shifts toward regions ofknown preferred color reproduction.

1 Introduction

A number of issues need to be addressed to achieve accuratecolor reproductions between imaging devices with dispar-ate color gamuts, white points, luminances, cognitive fac-tors, and illuminating environments.1 Many of these factorsare taken into suitable account through the use of color-appearance models. Consider the example where a CRTimage will be reproduced in hard copy with the goal ofachieving as accurate a color rendition as possible. TheCRT when viewed in the dark may have a white pointchromaticity near CIE illuminant D65 with a peak whiteluminance of around 60 cd/m2. The print may be viewedunder office lighting similar to CIE illuminant F2 where thepaper white has a luminance around 150 cd/m2. Acolor-appearance model will account for these differencesunder the assumption that each device is viewed separately.In other words, the observer has a single steady-state adap-tation to each display. In the CIE guidelines for coordinatedresearch to test color-appearance models for cross-mediacolor reproduction, single steady-state adaptation is re-quired.2 For this to occur with normal binocular vision,observers would first adapt to the CRT environment andthen memorize the displayed CRT image. They would thenadapt to the print-viewing environment and, followingadaptation, view the print. Adaptation to each environmentwould take between 1 and 2 min to occur in this example.3

Braun and Fairchild4 evaluated this and other methods ofviewing to achieve single-state adaptation. They also evalu-ated mixed adaptation where observers could view bothdevices simultaneously. They found that models predictingcolor appearance matches for steady-state adaptation toeach device were very unacceptable when applied undermixed adaptation. However, this is how users of colorimaging systems often judge color reproduction accuracy.Once the print is produced, it is held next to the CRTdisplay. In the above example, this would redefine the

Cathode-Ray-Tube to Reflection-Print Matchingunder Mixed Chromatic Adaptation using RLAB

Roy S. Berns and Heui-Keun Choh*Rochester Institute of Technology, Center for Imaging Science

Munsell Color Science Laboratory54 Lomb Memorial Drive, Rochester, New York 14623-5604

E-mail: rsbpph@rit.edu*Samsung Advanced Institute of Technology, Suwon, P.O. Box 111

Kyung Ki-Do, Korea

Chapter I—Color Appearance—259

appearance of the CRT display because of a change in theobserver’s state of chromatic adaptation, surround relativeluminance, and the addition of ambient flare (unless the printwas viewed in a light booth adjacent to the monitor). The colorappearance of the print would similarly be affected.

Presumably, if the influence of the alternate device andits viewing environment is known, this can be taken intoaccount when defining the color appearance of each image.Suppose one is viewing the CRT in a fully lit room asdescribed above. Further suppose that the room environ-ment determines the state of adaptation for both images; inthis case, the appearance of the CRT is defined as a verybluish image. One would then generate a bluish balancedprint. Because the observer is looking back and forth be-tween the CRT and print, one could instead suppose that theobserver is adapted to the midpoint of the two images. Theappearance of the CRT would be bluish, though less so thanwith the first supposition.

Katoh5 addressed this question where he used a modi-fication of the RLAB6 color-appearance model. Corre-sponding images were generated using an inkjet printerwhere the adaptational state when viewing the CRT waseither completely dependent upon the CRT environment,completely dependent upon the print environment, or vari-ous ratios between the two. It was assumed that the observerwould always be completely adapted to the ambient envi-ronment when viewing prints. Observers performed a pairedcomparison experiment to determine which CRT adapta-tion state corresponded to the closest color reproductionbetween the CRT and printed images. Fifteen observersjudged one image at six different adaptation ratios (0, 20,40, 60, 80, 100%). The experiment was repeated with twodifferent CRT correlated color temperatures, 6500 K and9000 K. The 60% and 40% adaptations to the CRT environ-ment yielded the closest matches, statistically. Images wheresingle-state adaptation was assumed had the poorest qual-ity, statistically. Katoh concluded that, for practical appli-cations, assuming the CRT adaptation to be around a 50%ratio of the CRT and print viewing environments wouldlead to improved hard-copy output when the quality crite-rion is based on viewing prints under mixed adaptation.

Several questions remained following the Katoh studythat were addressed in the present research. The first questionwas whether images that matched under this mixed viewingwould look acceptable when viewed on their own. Althoughimages tend to be judged initially adjacent to the CRT, theirfinal usage is often as standalone images. If a bluish balancedprint had the closest appearance to the CRT, would it remainacceptable when viewed at a later time? The second ques-tion was whether adaptation to the print environment re-mains unaffected when viewing the CRT display.

2 Experimental

2.1 CRT ColorimetryA Macintosh Quadra 900 with a 16-in. Sony Trinitron

monitor was used to display pictorial images. The colori-metry was first determined for this display in a darkenedroom using a Minolta CRT Color Analyzer CA-100 usingthe methodology recommended by Berns et al.7,8 The peakwhite had chromaticities of x = 0.3045 and y = 0.3126, closeto D65, and a luminance of 56.8 cd/m2. Independent data (3

× 3 × 3 digital factorial design) were used to determinemodel accuracy; the average ∆E*ab was 1.2 with a maxi-mum error of 1.7 and a standard deviation of 0.3.

The room lights were turned on according to the ex-perimental design to be described and the light reflectingoff of the CRT faceplate was measured using an LMTmodel L 1009 photometer (4.6 cd/m2). From a knowl-edge of the ambient chromaticities (assumed to equal F2)and the photometric measurement, the tristimulus values ofthe ambient flare were calculated. This was added to thetristimulus estimates based on the characterization per-formed in darkness.

2.2 Printer ColorimetryContinuous tone prints at 200 dots per inch were

generated using a Fujix Pictrography 3000 printer. Theprinter was colorimetrically characterized using similarmethodology to Berns.9 The modeling data consisted ofcyan, magenta, yellow, and gray step wedges modulatedbetween each primary and white in steps of 32 digital countsfrom 0 to 255 and red, green, and blue step wedges modu-lating between each primary and black in steps of 32 digitalcounts. Each sample was measured using a Macbeth 7000spectrophotometer with total hemispherical geometry. Thespectral reflectance factor was transformed to spectral ab-sorption using Kubelka-Munk theory. Principal componentanalyses were performed10 on the spectral absorption ofeach cyan, magenta, and yellow ramp. The first eigenvectorwas used to characterize the spectral absorptivity of eachdye. A tristimulus matching algorithm for the 1931 ob-server and illuminant F2 was used to determine the dyeconcentrations of each sample.

Figure 1. Concentration of magenta dye contained within neutraland magenta step wedges.

Plots of concentration versus digital counts for eachprimary and gray ramp revealed a small amount of interac-tion at high concentrations as shown in Fig. 1. For colorsnear the bottom of the printer’s color gamut, less dye wastransferred than in the top portion of the color gamut. Thisphenomenon is common in dye-diffusion printers, althoughfor the Fuji printer this effect was much smaller than usualbecause of its particular technology where a silver-halide

260—Recent Progress in Color Processing

intermediary is exposed with lasers, the color developed,and the entire colored image transferred to the receiversheet.11 Two different models were tested to relate digitalcounts to concentration.

Because of the importance of gray balance, a simplemodel was first implemented where three one-dimensionallook-up tables (LUTs) were generated to relate digitalcounts to concentration for the gray ramp samples. Cubicspline interpolation was used to build the three LUTs fromthe nine samples. These LUTs model the tone reproductioncharacteristics of the printer. Ordinarily, a color-correctionmatrix to model the interaction would follow the threeLUTs. The matrix coefficients are estimated from multiplelinear regression where the linearized digital counts are theindependent variables and concentrations are the dependentvariable. When the matrix is a three-by-three linear trans-formation, it is often constrained such that its row elementssum to unity. However, unless the units of concentration aredefined on a visual density basis such as equivalent-neutraldensities, the constrained matrix will not maintain graybalance. This is remedied by placing the constrained inter-action matrix before the three LUTs. This ensures accurateestimates of gray-ramp concentrations.

Once concentration was estimated, the appropriateKubelka-Munk equations were used to estimate the spectralreflectance factor and, in turn, calculate colorimetric val-ues. A database consisting of the 63 samples to build themodel and 88 colors sampling the color gamut were used asverification data. The average ∆E*ab (1931 observer,illuminant F2) between the measured colors and their esti-mated values was 2.3 with a maximum of 9.4. The maximumerrors were near the edges of the color gamut where concentra-tion was underestimated. The three-by-three matrix was un-able to account for the discrepancy depicted in Fig. 1.Higher order row-constrained matrices where the linear termssummed to unity and higher order and covariance termssummed to zero resulted in only marginal improvement.

Because of the need for gamut mapping between theCRT display and the printer, we were concerned that thischaracterization would result in an underutilization of theprinter gamut although giving perfect gray balance withinthe printer’s repeatability and spatial uniformity (meancolor difference from the mean for a midgray of up to 1.5∆E*ab). Accordingly, a second model was developed wherethe three one-dimensional LUTs were based on the cyan,magenta, and yellow primary ramps followed by an uncon-strained matrix. Stepwise multiple linear regression (for-ward selection, (x = 0.05) was performed where the linearizeddigital counts were the independent data and concentrationswere the dependent data. Linear, squared, and linear cova-riance terms were hypothesized as candidate model coeffi-cients. The concentration estimates were used as describedabove. This unconstrained model resulted in an average∆E*ab for the test colors of 1.6 with a maximum of 5.6. Thegray scale had color differences ranging between 0.1 and1.8. Since the average color difference and the gray-scaleerrors were near the printer’s repeatability, and the largererrors were randomly distributed within the printer’s colorgamut, this second model was used.

2.3 Colorimetric Unit ConversionThe CRT was characterized in units of luminance while

the printer was characterized using total hemispherical geom-etry relative to the perfect reflecting diffuser. Since the colorappearance model to be implemented would output lumi-nance units, the printer units required conversion.

A print with solid black and white image areas wasplaced adjacent to the CRT according to the experimentaldesign. Using the LMT photometer, measurements were madeof the two areas with the photometer placed in a similarlocation to the observer (0.97 and 75.7 cd/m2). Assumingthe ambient chromaticities were equal to illuminant F2,tristimulus values were calculated from the photometricmeasurements. Three linear equations were derived to con-vert from photometer to spectrophotometer values.

2.4 Gamut Mapping and ImplementationImages presented on the CRT are defined by their

tristimulus values. These tristimulus values are input to acolor appearance model where corresponding colors arecalculated according to defined appearance model param-eters. The tristimulus values of these corresponding colorsneed to be reproduced as prints, which was accomplished bythe following steps. First, the photometer tristimulus values(defining the corresponding colors) were converted to spec-trophotometer values. These tristimulus values were inputto a tristimulus matching algorithm (CIE illuminant F2,1931 2° observer). The algorithm iteratively determinedconcentrations corresponding to the input tristimulus val-ues based on the Kubelka-Munk spectral model. The con-centrations were input to the three LUTs in inverse wherepiecewise linear interpolation was used to estimate digitalcounts between the 256 LUT values. Finally, these digitalcounts were input to an unconstrained interaction matrix.(Since the forward model matrix is noninvertible, a newmatrix was derived where the estimated digital counts werethe independent data and the actual digital counts were thedependent data. The matrix had a similar form to theforward model.)

Portions of the CRT color gamut could not be repro-duced corresponding to negative dye concentrations. Forthose cases, the tristimulus matching algorithm determinedpositive concentrations minimizing the sum of square errorin tristimulus space. This is similar conceptually to mini-mum ∆E*ab clipping as a method of gamut mapping. Thisresulted in a three-dimensional LUT where the printer digitalvalues were extrapolated smoothly. The data extrapolationis necessary for three-dimensional interpolation.12

The three sections, forward CRT model, appearancemodel, and inverse printer model, were concatenated withfloating point calculations and used to build a 17 × 17 × 17three-dimensional LUT. Because the two device colorimet-ric characterizations were model based, the 3-D LUT waswithout numerical discontinuities. This minimized artifactsresulting from linear interpolation of inherently nonlineardata. These discontinuities can occur when direct measure-ments are used in place of models unless the sampling of thenecessary spaces (device and colorimetric) is uniform or theamount of nonlinearity is very small in undersampledregions. Cubic interpolation software13 operating as anAdobe Photoshop™ plug-in filter was used to processimages.

As a visual check, prints were made using the 3-DLUTs except optimized for illuminant F7 and viewed with

Chapter I—Color Appearance—261

fluorescent simulated daylight rather than cool-white fluo-rescent. The ambient luminance was adjusted so the paperand CRT peak whites had similar values. When viewing theexperimental images, the color match between the twodevices was very acceptable.

2.5 Viewing EnvironmentThe Macintosh system was placed in a small laboratory

painted a midgray with variable ceiling lighting. Eight 4-ftfluorescent tubes could be individually turned on and off.They were adjusted to give reasonable illuminance whileminimizing ambient flare from the CRT. The tubes werestandard cool-white fluorescent with spectral power distri-butions similar to CIE illuminant F2.

An easel was used to position prints adjacent to theCRT. Images were about 4 × 6 in. The remaining imageareas were set to a medium gray. Observers sat about 2 ftfrom the image plane.

2.6 Test ImagesFour pictorial images were used in the visual experi-

ment: “Motorcycles,” “Picnic,” “Balloon Girl,” and “FujiGirl” shown in Fig. 2. The first three images are EastmanKodak images. “Motorcycle” was selected for itshigh-chroma primary colors (yellow, red, green, and blue)and ground cover. “Picnic” is notable for its range ofhigh-chroma primary colors, flesh tones, blue sky, andgreen grass. “Balloon Girl” is notable for its range of pastelcolors, Caucasian flesh tone, and white (child’s dress).“Fuji Girl” is a portion of the continuous-tone test targetdeveloped by Fuji Photo Film Ltd. for the Japan Electrophoto-graphic Society. This target was scanned with a Sharp JX610at 200 dots per inch. A color correction matrix optimized forphotographic paper was used to improve the color accuracyof this image when displayed on the CRT display. We feltthese four images sampled typical pictorial images andcontained colors that were important to reproduce well: skintones, high chroma colors, green grass, blue sky, and white.Several of these images had portions of their color gamutwell outside of the printer’s color gamut. Because gamutmapping was not an experimental parameter, these imageswere adjusted in Photoshop, reducing their chroma slightly.Although this resulted in a closer gamut match, mappingwas still required. (We were concerned that if we eliminatedall gamut mismatching, the prints would appear unnaturalas stand-alone images due to an excessive reduction inchroma in some regions of color space.)

Prints were made where each experimental parameter(to be described below) was compared pairwise. This cor-responded to 10 prints per image. Prints were randomizedspatially (left to right or vertical to horizontal) and tempo-rally (presentation order).

2.7 Color-Appearance ModelThe RLAB color-appearance model6 was used in this

research. It has the advantages of computational simplicity,mathematical inversion, ease of understanding, good pastperformance for pictorial images,4,14,15 and infrequentlypredicting corresponding colors outside of the printer colorgamut. Because the viewing conditions were the same forboth the CRT and printed images, the RLAB model reducedto the following equations:

XYZ

Print

= M−1A p−1C p

−1CCACMXYZ

CRT

,

where

M =0.4002 0.7076 −0.0808

−0.2263 1.1653 0.04570.0 0.0 0.9182

A c =pL / Ln,CRT 0.0 0.0

0.0 pM / Mn,CRT 0.00.0 0.0 pS / Sn,CRT

A p =1 / Ln,Pr int 0.0 0.0

0.0 1 / Mn,Pr int 0.00.0 0.0 1 / Sn,Pr int

C =1 c cc 1 cc c 1

c = 0.219 – 0.0784 log10 (Yn)

Ln

Mn

Sn

= M100 / Yn 0.0 0.0

0.0 100 / Yn 0.00.0 0.0 100 / Yn

Xn

Yn

Zn

pL =

(1 + Yn1/3 + lE )

(1 + Yn1/3 + 1 / lE )

lE

3(Ln / 102.70)Ln / 102.70 + Mn / 98.47 + Sn / 91.82

pM =

(1 + Yn1/3 + mE )

(1 + Yn1/3 + 1 / mE )

mE

3(Mn / 98.47)Ln / 102.70 + Mn / 98.47 + Sn / 91.82

pS =

(1 + Yn1/3 + sE )

(1 + Yn1/3 + 1 / sE )

sE

3(Sn / 91.82)Ln / 102.70 + Mn / 98.47 + Sn / 91.82

.

Here Xn, Yn, and Zn, are the measured peak whitetristimulus values of each device (described in Sec. 2.3) inunits of candelas per square meter. Matrix M transforms X,

262—Recent Progress in Color Processing

Y, and Z tristimulus values of each pixel to fundamentaltristimulus values. Matrix A accounts for chromatic adap-tation. Incomplete adaptation was assumed for the CRTdisplay and complete adaptation was assumed for the prints,regardless of the percentage of mixed application. Matrix Caccounts for changes in colorfulness and dynamic rangewith changes in luminance.

2.8 Experimental ParametersCorresponding images were calculated for five differ-

ent conditions to be referred to as cases 1 through 5. Theyare listed in Table 1. The chromaticities comprising theseconditions are shown in Fig. 3. For case 1, it was assumedthat the observer completely adapts to each device, the usualmethod of using a color appearance model. For case 2, it wasassumed that the observer had a steady-state adaptationequal to the midpoint of the two devices. For case 3, it wasassumed that adaptation was affected by both alternatedevices; the CRT adaptational state was 75% CRT and 25%print while the print adaptational state was 75% print and25% CRT. For case 4, it was assumed that only printadaptation was affected; the CRT adaptational state was100% CRT while the print adaptational state was 75% printand 25% CRT. For case 5, it was assumed that only CRTadaptation was affected; the CRT adaptational state was75% CRT and 25% print while the print adaptational statewas 100% print. The tristimulus values used for RLAB ofeach case are listed in Table 2. Cases 4 and 5 are similar toKatoh.5 Cases 1 through 5 are shown in Fig. 4 for the “FujiGirl” image. Case 1 has the least bluish color balance whilecase 2 has the most bluish cast. Cases 3, 4, and 5 have colorbalances intermediary to these two extremes.

2.9 Visual TaskObservers were instructed to compare the CRT “origi-

nal” image with the image pair and select the image thatmost closely matched the original in color. They were theninstructed to categorize the closest image as either “accept-able,” “marginally acceptable,” or “unacceptable.”

The CRT was then turned off and the observers wereinstructed to compare each image pair and select the pre-ferred image.

Sixteen observers participated in the experiment. Ittook between 40 and 60 min to complete both visual tasks.

2.10 Data AnalysisOrdinal judgments were converted to interval scales

using Thurstone’s law of comparative judgments.16 Propor-tion matrix elements of each pairwise judgment were con-verted to Z scores. The average Z score by column definedthe interval scale value. Ninety-five percent confidencelimits were calculated by ± 1.38/√N where N counts thenumber of observations.

3 Results and Discussion

The matching results for each image are shown in Fig. 5where the visual scale values are plotted in descendingorder. Ninety-five percent confidence limits are delineatedby the vertical lines. Images are significantly different (α =0.05) if the scale value of the image with the lower value isnot within the confidence limit of the image with the largerscale value. For example, for “Motorcycles,’’ case 1 issignificantly different from all the other cases while cases 3and 4 are not significantly different from one another. Forall four images, case 1 had the lowest scale value (poorestmatches), case 5 had the penultimate scale value, and case3 had the highest scale value (closest matches). Cases 2 and4 exchanged orders depending on the image. The “FujiGirl” image resulted in the most sensitive result (fivestatistically significant categories) while “Motorcycles”resulted in the least sensitive scale (three categories).

The combined result for all four images is shown in Fig.6. Case 3, where it was assumed that both devices and theirviewing conditions affected the observer’s state of adapta-tion, resulted in the closest visual match; the observer’sadaptation to each image was influenced by the alternateimage. Case 2, where it was assumed that the observer wasadapted to the average of the two conditions, always re-sulted in the second statistical category. Selecting case 2images as the closest match implies that the observers arecontinually looking back and forth between the two imagesspending an equal amount of time viewing each image.Selecting case 3 implies that the observers will have periodsof steady-state viewing where they will view the CRTdisplay and memorize the image’s color appearance, thenview one or more pairs of prints. When their memorybecomes fatigued, they will repeat the process. Since case3 was ranked above case 2, the latter type of viewing

Table 1. Assumed adaptation states of cases 1 through 5. Letter designations correspond to Fig. 3.

Case CRT adaptation condition Print adaptation condition

1 A (100% CRT) E (100% print) 2 C (50% CRT and 50% print) C (50% CRT and 50% print) 3 B (75% CRT and 25% print) D (25% CRT and 75% print) 4 A (100% CRT) D (25% CRT and 75% print) 5 B (75% CRT and 25% print) E (100% print)

Table 2. Tristimulus values in units of candelas per square meter of the assumed adaptation state of cases 1 through 5.

Case CRT Print Xn Yn Zn Xn Yn Zn

1 59.9 61.4 72.6 75.1 75.7 51.1 2 67.5 68.6 61.9 67.5 68.6 61.9 3 63.77 65.0 67.2 71.3 72.1 56.5 4 59.9 61.4 72.6 71.3 72.1 56.5 5 63.7 65.0 67.2 75.1 75.7 51.1

Chapter I—Color Appearance—263

Figure 5. Interval scale value versus case number from the matching experiment for each listed image. Average value shown as filledsquare. Ninety-five percent confidence interval shown as vertical line bounded by filled dots.

occurred most often. This is consistent with the authors’personal experiences in performing these kinds of experi-ments. Case 1, where it was assumed that observers wereadapted in a single, steady-state fashion, always resulted inthe poorest match. This agrees with Braun and Fairchild.4

The use of an appearance model without controlling view-ing can result in poor-quality reproductions based on side-by-side matching.

Noting that the case 3 total adaptational change was50%, the present experiment is also supportive of Katoh.5

Katoh’s optimal images were based on the assumption thatobservers were fully adapted to the print-viewing condition(chromaticity position E) and around halfway between bothdevices for the CRT images (around chromaticity positionC). The colorimetric differences in the images due todifferences in the actual chromaticities between the presentexperiment (D and B) and Katoh (E and C) may not have asignificant visual difference. This implies that for thesesmall changes in colorimetry, the images have approximatecolor constancy, a reasonable assumption for the Pictro-graphy dye set.

Figure 6. Interval scale value versus case number from thematching experiment for all four images combined. Averagevalue shown as filled square. Ninety-five percent confidenceinterval shown as vertical line bounded by filled dots.

264—Recent Progress in Color Processing

Figure 7. Percent “acceptable” and “marginally acceptable” for each image from matching experiment.

The category scaling, expressed in percentages, isshown in Fig. 7 for each image and in Fig. 8 for the fourcombined images. Case 3, the closest match, yielded about45% acceptability and, combined with the “marginallyacceptable” category, about 84% on average. Although thisis a reasonable result, there is clearly room for improve-ment. The lack of acceptability is related to printer repeat-

ability, printer colorimetry, color gamut mapping, color-appearance model accuracy, spatial image quality, and alack of adaptational stability causing a continual change inthe color appearance of the images undergoing evaluation.The category scaling results were also image dependent.Different colors were reproduced with different degrees ofaccuracy for each case. Depending on the image content,

Chapter I—Color Appearance—265

this would affect acceptability. For example, the “Motor-cycles” image had obvious primaries (yellow, red, andgreen) and a large area of ground. Grass green would be acritical color to reproduce for the “Picnic” image. Whitesand skin tones would be critical for “Fuji Girl” and “BalloonGirl.’’ Similar to the matching scale results, “Fuji Girl” wasa sensitive image.

As stated in the introduction, it is also important to havethe reproduction have quality as a stand-alone image. Thepreference judgments directly addressed this issue. Theseresults are shown in Fig. 9 for each image and Fig. 10 for thefour combined images. On average, cases 5 and 3 were themost preferred images and case 2 was the least preferredimage. Although case 2 resulted in reasonable matches tothe CRT, the images had a decidedly bluish color balancethat were very unacceptable as stand-alone images; colori-metric color reproduction is not equivalent to appearancecolor reproduction. With the exception of “Motorcycles,”cases 5 and 3 produced the preferred result. (Case 5 assumedthat the observer’s adaptation to the CRT was shifted 25%and the adaptation to the print was totally dependent on theambient conditions.) Figure 8. Percent “acceptable” and “marginally acceptable” for

all four images from matching experiment.

Figure 9. Interval scale value versus case number from the preference experiment for each listed image. Average value shown as filledsquare. Ninety-five percent confidence interval shown as vertical line bounded by filled dots.

266—Recent Progress in Color Processing

Figure 10. Interval scale value versus case number from thepreference experiment for all four images combined. Averagevalue shown as filled square. Ninety-five percent confidenceinterval shown as vertical line bounded by filled dots.

Figure 11. Correlation between matching and preference experi-ments. Solid line represents regression yielding an R2 of 0.006.

Case 1, appearance color reproduction, was never thepreferred image. This was a surprising result. We had anexpectation that case 1 would result in a poor match and apreferred stand-alone image. Each original image had anarbitrary color balance. Cases 3 and 5 produced prints inwhich critical colors were reproduced in a more preferredway than case 1. This can be observed in Fig. 4. Cases 3 and5 have a slight bluish overall color balance in comparisonwith case 1. The observers preferred bluish neutrals; this isthe usual preference for our geographic location. It isinteresting that when visually comparing all of these repro-

duced images with the original Japan ElectrophotographicSociety reflection test target, case 1 is the closest colormatch when viewed under cool-white fluorescent illumina-tion. The original target is color balanced without a notice-able hue shift. Thus, observers did not prefer accurate colorreproductions as stand-alone prints. This has been the goalof many consumer imaging systems, such as amateur pho-tography: producing images that look pleasing. Each imagecontained critical colors such as skin tones, grass, and sky.Comparing the chromaticities of these critical colors withthe preferred color reproduction ellipses summarized byHunt17 revealed a high correlation. (A Judd-type chromaticadaptation transformation was used to translate the CIEsource C results to the present white point of F2.) Observerswere using different criteria when evaluating the quality ofmatching and the quality of the standalone images. The differ-ences in criteria are supported quantitatively by plotting thevisual scales from the two experiments for each conditionand image as shown in Fig. 11. The lack of correlationsupports this notion of different observer criteria.

4 Conclusions

An experiment was performed to evaluate the effect ofviewing CRT images and their hard-copy reproductionssimultaneously under mixed chromatic adaptation. Althoughthis practice is not recommended, it is a common practice.The RLAB color appearance model was used to take thiseffect into suitable account. Observers visually scaled fourpictorial images and found that prints produced in which theappearance of the CRT images was based on an adaptationalstate shifted 25% toward the print viewing environment andwhere the appearance of the print images was based on anadaptational state shifted 25% toward the CRT viewingenvironment yielded the closest matches (case 3). Theseprints were rated acceptable 45.2% of the time and margin-ally acceptable 38.6% of the time. They were also in thehighest ranking along with case 5 as the most preferredimages when viewed as stand-alone images under a singlesteady-state adaptation. Thus when deriving WYSIWYGtransforms for CRT to reflection-print matching undermixed chromatic adaptation, this change in color appear-ance definition should be used. This will result in anacceptable match and a preferred stand-alone image provid-ing that critical colors such as white, green grass, blue sky,and skin tones are reproduced near or within regions ofpreferred color reproduction. However, if the CRT image isoptimized in terms of preferred color reproduction, caremust be taken to ensure that the stand-alone image does nothave its critical colors shifted outside of the regions ofpreferred color reproduction. If it is likely that the imagewill have critical colors overly shifted, one must considerwhether it is more important to have close matching undermixed adaptation or close matching as a stand-alone image.For the latter, the case 1 conditions should be used.

In the future, this experiment should be extended wherethe “original” images are balanced on the CRT display suchthat their critical colors are within preferred color reproduc-tion boundaries. This way, the preference results will be anevaluation of the accuracy of estimating the mixed adapta-tional states for CRT viewing rather than preferred colorreproduction. Cases 2, 4, and 5 should be dropped from the

Chapter I—Color Appearance—267

experiment and replaced with changes that all correspond toa total change of 50%, such as chromaticity locations A andC and locations C and E. Finally, if only a single image canbe evaluated, an image similar to the “Fuji Girl’’ imageshould be used since it produced excellent scale sensitivity.

Acknowledgments

This research was supported by the Samsung AdvancedInstitute of Technology and the Richard S. Hunter Profes-sorship. The authors also acknowledge the recent equip-ment donations by Fuji Photo Film Ltd., Lichtmesstechnik(LMT), Macbeth, and Minolta.

References

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published previously in JEI—The Journal of ElectronicImaging, Vol. 4(4), 1995, page 347