Abstract

Small suprathreshold color differences around five CIE color centers were investigated on a typical liquid crystal display (LCD) with fluorescent backlight using the method of constant stimuli. The results were evaluated using probit analysis and compared with surface-color differences of the RIT-DuPont dataset. We focused especially on the relationship between T50 distances obtained from LCD and surface-color stimuli and on the influence of the display’s narrowband primaries and its relatively low luminance level on interobserver uncertainty. The low luminance level of the LCD decreases the perceived color differences. However, considering the visual uncertainty of the experimental data, we could not reject the hypothesis that T50 distances from the RIT-DuPont and our experiment agree up to a constant scaling factor. In addition, we found significantly higher interobserver variability in the estimation of small color differences if the colors are viewed on an LCD. There are some indications that color-difference perception might be influenced by individual color-matching functions and, thus, by the spectral power distribution of the stimuli. We provide the experimental data, including all spectral stimuli shown to the observers, on our website.

© 2011 Optical Society of America

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References

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  1. M. D. Fairchild and D. R. Wyble, “Mean observer metamerism and the selection of display primaries,” in Fifteenth Color Imaging Conference: Color Science and Engineering Systems, Technologies, and Applications (The Society for Imaging Science and Technology, 2007), pp. 151–156.
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    [CrossRef]
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  12. I. Sprow, T. Stamm, and P. Zolliker, “Evaluation of color differences: use of LCD monitor,” in Eighteenth Color Imaging Conference: Color Science and Engineering Systems, Technologies, and Applications (The Society for Imaging Science and Technology, 2010), pp. 115–120.
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  25. H. N. Mangine, “Variability in experimental color matching conditions: effects of observers, daylight simulators, and color inconstancy,” Ph.D. thesis (Ohio State University, 2005).
  26. A. Sarkar, L. Blondé, P. L. Callet, F. Autrusseau, P. Morvan, and J. Stauder, “Toward reducing observer metamerism in industrial applications: colorimetric observer categories and observer classification,” in Eighteenth Color Imaging Conference: Color Science and Engineering Systems, Technologies, and Applications (The Society for Imaging Science and Technology, 2010), pp. 307–313.
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2011 (1)

S. Shen and R. S. Berns, “Color-difference formula performance for several datasets of small color differences based on visual uncertainty,” Color Res. Appl. 36, 15–26 (2011).
[CrossRef]

2010 (2)

I. Lissner and P. Urban, “Upgrading color-difference formulas,” J. Opt. Soc. Am. A 27, 1620–1629 (2010).
[CrossRef]

A. Trémeau, C. Godau, and D. Muselet, “Supplementary dataset for color difference evaluation,” Proc. SPIE 7528, 75280K (2010).
[CrossRef]

2009 (2)

S. Shen and R. S. Berns, “Evaluating color difference equation performance incorporating visual uncertainty,” Color Res. Appl. 34, 375–390 (2009).
[CrossRef]

R. G. Kuehni, “Variability in estimation of suprathreshold small color differences,” Color Res. Appl. 34, 367–374 (2009).
[CrossRef]

2008 (1)

2007 (2)

2005 (1)

R. W. Pridmore and M. Melgosa, “Effect of luminance of samples on color discrimination ellipses: analysis and prediction of data,” Color Res. Appl. 30, 186–197 (2005).
[CrossRef]

2004 (1)

E. A. Day, L. Taplin, and R. S. Berns, “Colorimetric characterization of a computer-controlled liquid crystal display,” Color Res. Appl. 29, 365–373 (2004).
[CrossRef]

2003 (1)

E. D. Montag and D. C. Wilber, “A comparison of constant stimuli and gray-scale methods of color difference scaling,” Color Res. Appl. 28, 36–44 (2003).
[CrossRef]

1999 (3)

S.-S. Guan and M. R. Luo, “Investigation of parametric effects using small colour differences,” Color Res. Appl. 24, 331–343(1999).
[CrossRef]

K. Witt, “Geometric relations between scales of small colour differences,” Color Res. Appl. 24, 78–92 (1999).
[CrossRef]

M. Melgosa, M. M. Pérez, A. E. Moraghi, and E. Hita, “Color discrimination results from a CRT device: influence of luminance,” Color Res. Appl. 24, 38–44 (1999).
[CrossRef]

1997 (2)

M. Melgosa, E. Hita, A. J. Poza, D. H. Alman, and R. S. Berns, “Suprathreshold color-difference ellipsoids for surface colors,” Color Res. Appl. 22, 148–155 (1997).
[CrossRef]

D. H. Brainard, “The psychophysics toolbox,” Spat. Vis. 10, 433–436 (1997).
[CrossRef] [PubMed]

1991 (1)

R. S. Berns, D. H. Alman, L. Reniff, G. D. Snyder, and M. R. Balonon-Rosen, “Visual determination of suprathreshold color-difference tolerances using probit analysis,” Color Res. Appl. 16, 297–316 (1991).
[CrossRef]

1986 (1)

M. R. Luo and B. Rigg, “Chromaticity-discrimination ellipses for surface colours,” Color Res. Appl. 11, 25–42 (1986).
[CrossRef]

1978 (1)

A. R. Robertson, “CIE guidelines for coordinated research on colour-difference evaluation,” Color Res. Appl. 3, 149–151 (1978).

1963 (1)

1952 (1)

1951 (1)

Alman, D. H.

M. Melgosa, E. Hita, A. J. Poza, D. H. Alman, and R. S. Berns, “Suprathreshold color-difference ellipsoids for surface colors,” Color Res. Appl. 22, 148–155 (1997).
[CrossRef]

R. S. Berns, D. H. Alman, L. Reniff, G. D. Snyder, and M. R. Balonon-Rosen, “Visual determination of suprathreshold color-difference tolerances using probit analysis,” Color Res. Appl. 16, 297–316 (1991).
[CrossRef]

Autrusseau, F.

A. Sarkar, L. Blondé, P. L. Callet, F. Autrusseau, J. Stauder, and P. Morvan, “Study of observer variability in modern display colorimetry: an analysis of CIE 2006 model,” in Proceedings of the 11th Congress of the International Colour Association (AIC) (CD), D.Smith, P.Green-Armytage, M.A.Pope, and N.Harknesss, eds. (Colour Society of Australia, 2009).

A. Sarkar, L. Blondé, P. L. Callet, F. Autrusseau, P. Morvan, and J. Stauder, “Toward reducing observer metamerism in industrial applications: colorimetric observer categories and observer classification,” in Eighteenth Color Imaging Conference: Color Science and Engineering Systems, Technologies, and Applications (The Society for Imaging Science and Technology, 2010), pp. 307–313.

Balonon-Rosen, M. R.

R. S. Berns, D. H. Alman, L. Reniff, G. D. Snyder, and M. R. Balonon-Rosen, “Visual determination of suprathreshold color-difference tolerances using probit analysis,” Color Res. Appl. 16, 297–316 (1991).
[CrossRef]

Berns, R. S.

S. Shen and R. S. Berns, “Color-difference formula performance for several datasets of small color differences based on visual uncertainty,” Color Res. Appl. 36, 15–26 (2011).
[CrossRef]

S. Shen and R. S. Berns, “Evaluating color difference equation performance incorporating visual uncertainty,” Color Res. Appl. 34, 375–390 (2009).
[CrossRef]

M. Melgosa, R. Huertas, and R. S. Berns, “Performance of recent advanced color-difference formulas using the standardized residual sum of squares index,” J. Opt. Soc. Am. A 25, 1828–1834(2008).
[CrossRef]

E. A. Day, L. Taplin, and R. S. Berns, “Colorimetric characterization of a computer-controlled liquid crystal display,” Color Res. Appl. 29, 365–373 (2004).
[CrossRef]

M. Melgosa, E. Hita, A. J. Poza, D. H. Alman, and R. S. Berns, “Suprathreshold color-difference ellipsoids for surface colors,” Color Res. Appl. 22, 148–155 (1997).
[CrossRef]

R. S. Berns, D. H. Alman, L. Reniff, G. D. Snyder, and M. R. Balonon-Rosen, “Visual determination of suprathreshold color-difference tolerances using probit analysis,” Color Res. Appl. 16, 297–316 (1991).
[CrossRef]

Blondé, L.

A. Sarkar, L. Blondé, P. L. Callet, F. Autrusseau, J. Stauder, and P. Morvan, “Study of observer variability in modern display colorimetry: an analysis of CIE 2006 model,” in Proceedings of the 11th Congress of the International Colour Association (AIC) (CD), D.Smith, P.Green-Armytage, M.A.Pope, and N.Harknesss, eds. (Colour Society of Australia, 2009).

A. Sarkar, L. Blondé, P. L. Callet, F. Autrusseau, P. Morvan, and J. Stauder, “Toward reducing observer metamerism in industrial applications: colorimetric observer categories and observer classification,” in Eighteenth Color Imaging Conference: Color Science and Engineering Systems, Technologies, and Applications (The Society for Imaging Science and Technology, 2010), pp. 307–313.

Brainard, D.

M. Kleiner, D. Brainard, and D. Pelli, “What’s new in Psychtoolbox-3,” Perception 36, ECVP Abstract Supplement (2007).

Brainard, D. H.

D. H. Brainard, “The psychophysics toolbox,” Spat. Vis. 10, 433–436 (1997).
[CrossRef] [PubMed]

Brown, W. R. J.

Callet, P. L.

A. Sarkar, L. Blondé, P. L. Callet, F. Autrusseau, J. Stauder, and P. Morvan, “Study of observer variability in modern display colorimetry: an analysis of CIE 2006 model,” in Proceedings of the 11th Congress of the International Colour Association (AIC) (CD), D.Smith, P.Green-Armytage, M.A.Pope, and N.Harknesss, eds. (Colour Society of Australia, 2009).

A. Sarkar, L. Blondé, P. L. Callet, F. Autrusseau, P. Morvan, and J. Stauder, “Toward reducing observer metamerism in industrial applications: colorimetric observer categories and observer classification,” in Eighteenth Color Imaging Conference: Color Science and Engineering Systems, Technologies, and Applications (The Society for Imaging Science and Technology, 2010), pp. 307–313.

Cui, G.

P. A. García, R. Huertas, M. Melgosa, and G. Cui, “Measurement of the relationship between perceived and computed color differences,” J. Opt. Soc. Am. A 24, 1823–1829(2007).
[CrossRef]

R. Huertas, A. Tremeau, M. Melgosa, L. Gomez-Robledo, G. Cui, and M. R. Luo, “Checking recent colour-difference formulas with a dataset of metallic samples and just noticeable colour-difference assessments,” in CGIV 2010/MCS’10: Fifth European Conference on Colour in Graphics, Imaging, and Vision / 12th International Symposium on Multispectral Colour Science (CD-ROM) (Society for Imaging Science and Technology, 2010), pp. 504–509.

Day, E. A.

E. A. Day, L. Taplin, and R. S. Berns, “Colorimetric characterization of a computer-controlled liquid crystal display,” Color Res. Appl. 29, 365–373 (2004).
[CrossRef]

Fairchild, M. D.

M. D. Fairchild and D. R. Wyble, “Mean observer metamerism and the selection of display primaries,” in Fifteenth Color Imaging Conference: Color Science and Engineering Systems, Technologies, and Applications (The Society for Imaging Science and Technology, 2007), pp. 151–156.

García, P. A.

Godau, C.

A. Trémeau, C. Godau, and D. Muselet, “Supplementary dataset for color difference evaluation,” Proc. SPIE 7528, 75280K (2010).
[CrossRef]

Gomez-Robledo, L.

R. Huertas, A. Tremeau, M. Melgosa, L. Gomez-Robledo, G. Cui, and M. R. Luo, “Checking recent colour-difference formulas with a dataset of metallic samples and just noticeable colour-difference assessments,” in CGIV 2010/MCS’10: Fifth European Conference on Colour in Graphics, Imaging, and Vision / 12th International Symposium on Multispectral Colour Science (CD-ROM) (Society for Imaging Science and Technology, 2010), pp. 504–509.

Guan, S.-S.

S.-S. Guan and M. R. Luo, “Investigation of parametric effects using small colour differences,” Color Res. Appl. 24, 331–343(1999).
[CrossRef]

Hita, E.

M. Melgosa, M. M. Pérez, A. E. Moraghi, and E. Hita, “Color discrimination results from a CRT device: influence of luminance,” Color Res. Appl. 24, 38–44 (1999).
[CrossRef]

M. Melgosa, E. Hita, A. J. Poza, D. H. Alman, and R. S. Berns, “Suprathreshold color-difference ellipsoids for surface colors,” Color Res. Appl. 22, 148–155 (1997).
[CrossRef]

Huertas, R.

M. Melgosa, R. Huertas, and R. S. Berns, “Performance of recent advanced color-difference formulas using the standardized residual sum of squares index,” J. Opt. Soc. Am. A 25, 1828–1834(2008).
[CrossRef]

P. A. García, R. Huertas, M. Melgosa, and G. Cui, “Measurement of the relationship between perceived and computed color differences,” J. Opt. Soc. Am. A 24, 1823–1829(2007).
[CrossRef]

R. Huertas, A. Tremeau, M. Melgosa, L. Gomez-Robledo, G. Cui, and M. R. Luo, “Checking recent colour-difference formulas with a dataset of metallic samples and just noticeable colour-difference assessments,” in CGIV 2010/MCS’10: Fifth European Conference on Colour in Graphics, Imaging, and Vision / 12th International Symposium on Multispectral Colour Science (CD-ROM) (Society for Imaging Science and Technology, 2010), pp. 504–509.

Hunt, R. W. G.

Kim, D. H.

D. H. Kim and J. H. Nobbs, “New weighting functions for the weighted CIELAB colour difference formula,” in Proceedings of AIC Colour 97, Vol. 1 (AIC, 1997), pp. 446–449.

Kleiner, M.

M. Kleiner, D. Brainard, and D. Pelli, “What’s new in Psychtoolbox-3,” Perception 36, ECVP Abstract Supplement (2007).

Kuehni, R. G.

R. G. Kuehni, “Variability in estimation of suprathreshold small color differences,” Color Res. Appl. 34, 367–374 (2009).
[CrossRef]

Lissner, I.

Luo, M. R.

S.-S. Guan and M. R. Luo, “Investigation of parametric effects using small colour differences,” Color Res. Appl. 24, 331–343(1999).
[CrossRef]

M. R. Luo and B. Rigg, “Chromaticity-discrimination ellipses for surface colours,” Color Res. Appl. 11, 25–42 (1986).
[CrossRef]

R. Huertas, A. Tremeau, M. Melgosa, L. Gomez-Robledo, G. Cui, and M. R. Luo, “Checking recent colour-difference formulas with a dataset of metallic samples and just noticeable colour-difference assessments,” in CGIV 2010/MCS’10: Fifth European Conference on Colour in Graphics, Imaging, and Vision / 12th International Symposium on Multispectral Colour Science (CD-ROM) (Society for Imaging Science and Technology, 2010), pp. 504–509.

Mangine, H. N.

H. N. Mangine, “Variability in experimental color matching conditions: effects of observers, daylight simulators, and color inconstancy,” Ph.D. thesis (Ohio State University, 2005).

Melgosa, M.

M. Melgosa, R. Huertas, and R. S. Berns, “Performance of recent advanced color-difference formulas using the standardized residual sum of squares index,” J. Opt. Soc. Am. A 25, 1828–1834(2008).
[CrossRef]

P. A. García, R. Huertas, M. Melgosa, and G. Cui, “Measurement of the relationship between perceived and computed color differences,” J. Opt. Soc. Am. A 24, 1823–1829(2007).
[CrossRef]

R. W. Pridmore and M. Melgosa, “Effect of luminance of samples on color discrimination ellipses: analysis and prediction of data,” Color Res. Appl. 30, 186–197 (2005).
[CrossRef]

M. Melgosa, M. M. Pérez, A. E. Moraghi, and E. Hita, “Color discrimination results from a CRT device: influence of luminance,” Color Res. Appl. 24, 38–44 (1999).
[CrossRef]

M. Melgosa, E. Hita, A. J. Poza, D. H. Alman, and R. S. Berns, “Suprathreshold color-difference ellipsoids for surface colors,” Color Res. Appl. 22, 148–155 (1997).
[CrossRef]

R. Huertas, A. Tremeau, M. Melgosa, L. Gomez-Robledo, G. Cui, and M. R. Luo, “Checking recent colour-difference formulas with a dataset of metallic samples and just noticeable colour-difference assessments,” in CGIV 2010/MCS’10: Fifth European Conference on Colour in Graphics, Imaging, and Vision / 12th International Symposium on Multispectral Colour Science (CD-ROM) (Society for Imaging Science and Technology, 2010), pp. 504–509.

Montag, E. D.

E. D. Montag and D. C. Wilber, “A comparison of constant stimuli and gray-scale methods of color difference scaling,” Color Res. Appl. 28, 36–44 (2003).
[CrossRef]

Moraghi, A. E.

M. Melgosa, M. M. Pérez, A. E. Moraghi, and E. Hita, “Color discrimination results from a CRT device: influence of luminance,” Color Res. Appl. 24, 38–44 (1999).
[CrossRef]

Morvan, P.

A. Sarkar, L. Blondé, P. L. Callet, F. Autrusseau, J. Stauder, and P. Morvan, “Study of observer variability in modern display colorimetry: an analysis of CIE 2006 model,” in Proceedings of the 11th Congress of the International Colour Association (AIC) (CD), D.Smith, P.Green-Armytage, M.A.Pope, and N.Harknesss, eds. (Colour Society of Australia, 2009).

A. Sarkar, L. Blondé, P. L. Callet, F. Autrusseau, P. Morvan, and J. Stauder, “Toward reducing observer metamerism in industrial applications: colorimetric observer categories and observer classification,” in Eighteenth Color Imaging Conference: Color Science and Engineering Systems, Technologies, and Applications (The Society for Imaging Science and Technology, 2010), pp. 307–313.

Muselet, D.

A. Trémeau, C. Godau, and D. Muselet, “Supplementary dataset for color difference evaluation,” Proc. SPIE 7528, 75280K (2010).
[CrossRef]

Nobbs, J. H.

D. H. Kim and J. H. Nobbs, “New weighting functions for the weighted CIELAB colour difference formula,” in Proceedings of AIC Colour 97, Vol. 1 (AIC, 1997), pp. 446–449.

Pelli, D.

M. Kleiner, D. Brainard, and D. Pelli, “What’s new in Psychtoolbox-3,” Perception 36, ECVP Abstract Supplement (2007).

Pérez, M. M.

M. Melgosa, M. M. Pérez, A. E. Moraghi, and E. Hita, “Color discrimination results from a CRT device: influence of luminance,” Color Res. Appl. 24, 38–44 (1999).
[CrossRef]

Poza, A. J.

M. Melgosa, E. Hita, A. J. Poza, D. H. Alman, and R. S. Berns, “Suprathreshold color-difference ellipsoids for surface colors,” Color Res. Appl. 22, 148–155 (1997).
[CrossRef]

Pridmore, R. W.

R. W. Pridmore and M. Melgosa, “Effect of luminance of samples on color discrimination ellipses: analysis and prediction of data,” Color Res. Appl. 30, 186–197 (2005).
[CrossRef]

Reniff, L.

R. S. Berns, D. H. Alman, L. Reniff, G. D. Snyder, and M. R. Balonon-Rosen, “Visual determination of suprathreshold color-difference tolerances using probit analysis,” Color Res. Appl. 16, 297–316 (1991).
[CrossRef]

Rigg, B.

M. R. Luo and B. Rigg, “Chromaticity-discrimination ellipses for surface colours,” Color Res. Appl. 11, 25–42 (1986).
[CrossRef]

Robertson, A. R.

A. R. Robertson, “CIE guidelines for coordinated research on colour-difference evaluation,” Color Res. Appl. 3, 149–151 (1978).

Sarkar, A.

A. Sarkar, L. Blondé, P. L. Callet, F. Autrusseau, J. Stauder, and P. Morvan, “Study of observer variability in modern display colorimetry: an analysis of CIE 2006 model,” in Proceedings of the 11th Congress of the International Colour Association (AIC) (CD), D.Smith, P.Green-Armytage, M.A.Pope, and N.Harknesss, eds. (Colour Society of Australia, 2009).

A. Sarkar, L. Blondé, P. L. Callet, F. Autrusseau, P. Morvan, and J. Stauder, “Toward reducing observer metamerism in industrial applications: colorimetric observer categories and observer classification,” in Eighteenth Color Imaging Conference: Color Science and Engineering Systems, Technologies, and Applications (The Society for Imaging Science and Technology, 2010), pp. 307–313.

Shen, S.

S. Shen and R. S. Berns, “Color-difference formula performance for several datasets of small color differences based on visual uncertainty,” Color Res. Appl. 36, 15–26 (2011).
[CrossRef]

S. Shen and R. S. Berns, “Evaluating color difference equation performance incorporating visual uncertainty,” Color Res. Appl. 34, 375–390 (2009).
[CrossRef]

Snyder, G. D.

R. S. Berns, D. H. Alman, L. Reniff, G. D. Snyder, and M. R. Balonon-Rosen, “Visual determination of suprathreshold color-difference tolerances using probit analysis,” Color Res. Appl. 16, 297–316 (1991).
[CrossRef]

Sprow, I.

I. Sprow, T. Stamm, and P. Zolliker, “Evaluation of color differences: use of LCD monitor,” in Eighteenth Color Imaging Conference: Color Science and Engineering Systems, Technologies, and Applications (The Society for Imaging Science and Technology, 2010), pp. 115–120.

Stamm, T.

I. Sprow, T. Stamm, and P. Zolliker, “Evaluation of color differences: use of LCD monitor,” in Eighteenth Color Imaging Conference: Color Science and Engineering Systems, Technologies, and Applications (The Society for Imaging Science and Technology, 2010), pp. 115–120.

Stauder, J.

A. Sarkar, L. Blondé, P. L. Callet, F. Autrusseau, J. Stauder, and P. Morvan, “Study of observer variability in modern display colorimetry: an analysis of CIE 2006 model,” in Proceedings of the 11th Congress of the International Colour Association (AIC) (CD), D.Smith, P.Green-Armytage, M.A.Pope, and N.Harknesss, eds. (Colour Society of Australia, 2009).

A. Sarkar, L. Blondé, P. L. Callet, F. Autrusseau, P. Morvan, and J. Stauder, “Toward reducing observer metamerism in industrial applications: colorimetric observer categories and observer classification,” in Eighteenth Color Imaging Conference: Color Science and Engineering Systems, Technologies, and Applications (The Society for Imaging Science and Technology, 2010), pp. 307–313.

Stevens, J. C.

Stevens, S. S.

Taplin, L.

E. A. Day, L. Taplin, and R. S. Berns, “Colorimetric characterization of a computer-controlled liquid crystal display,” Color Res. Appl. 29, 365–373 (2004).
[CrossRef]

Tremeau, A.

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Figures (10)

Fig. 1
Fig. 1

Spectral primaries of the LCD used in our experiment.

Fig. 2
Fig. 2

Experimental setup (top) and stimulus arrangement on the display (bottom).

Fig. 3
Fig. 3

Evaluated color-difference directions.

Fig. 4
Fig. 4

Example of a cumulative Gaussian distribution fitted to the frequency-of-rejection data of a particular color-difference direction. Left: In the pilot experiment the cumulative Gaussian distribution function was fitted to frequency-of-rejection data points corresponding to CIEDE2000 distances of 0.4 , , 4 from the color center. To obtain five test colors for the main experiment, the cumulative Gaussian distribution was inverted at probabilities 0.2, 0.35, 0.5, 0.65, and 0.8, resulting in new distances x 1 , , x 5 . Right: In the main experiment the cumulative Gaussian distribution function was fitted to frequency-of-rejection data points corresponding to measurements of test colors with distances x 1 , , x 5 to the color center. Because of instabilities of the display, these distances usually deviate from the intended distances x 1 , , x 5 obtained in the pilot experiment. The T50 distance is computed by inverting the cumulative Gaussian distribution function at probability 0.5.

Fig. 5
Fig. 5

Filtering algorithm applied to the raw experimental data according to Berns et al. [9]. This filtering step serves to reduce the intraobserver uncertainty.

Fig. 6
Fig. 6

Ellipsoids fitted to the RIT-DuPont data (black, smaller) compared with ellipsoids fitted to the results of the IDD-LCD experiment (red, larger) at the five investigated color centers.

Fig. 7
Fig. 7

(a)–(e) Comparisons between CVs of the RIT-DuPont and IDD-LCD datasets, (f) comparison of estimated standard deviations between opposite color-difference directions ( + dir. and dir. ) of the IDD-LCD dataset.

Fig. 8
Fig. 8

Computation of (a) single-observer thresholds μ a b obs and (b) mean thresholds μ a b for all observers. If there are multiple crossings of the 0.5-threshold (dotted line) as in (a), the mean of the corresponding Δ E a b * values is used as an observer threshold.

Fig. 9
Fig. 9

Mean deviations of individual observers from the average (percent).

Fig. 10
Fig. 10

Distributions of 5000 randomly computed lengths for corresponding IDD-LCD/RIT-DuPont directions 3/B (top) and 11/G (bottom) at the gray color center.

Tables (5)

Tables Icon

Table 1 CIELAB Values of the Five Color Centers Recommended by the CIE, the Stimuli Shown in Our Experiment [Color Centers, Anchor Pair (AP) Colors, Background Color, and Color of the White Border], and the Stimuli Used in the RIT-DuPont Experiment

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Table 2 Evaluation of the Intraobserver Variability: p-Values Resulting from the Goodness-of-Fit Tests for All Investigated Color Centers and Directions a

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Table 3 STRESS Values between + T 50 Distances and 5000 Corresponding Randomized Distances for the IDD-LCD and the RIT-DuPont Data, with STRESS Values between IDD-LCD and RIT-DuPont + T 50 Distances a

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Table 4 Percentages of 5000 F-tests That Indicate Significant Differences between + T 50 Distances of the IDD-LCD and RIT-DuPont Datasets and between ± T 50 Distances of the IDD-LCD Dataset, Considering Visual Uncertainty a , b

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Table 5 STRESS Values between ± T 50 Distances of the IDD-LCD Dataset and 5000 Corresponding Randomized Distances, with STRESS Values between Corresponding IDD-LCD + T 50 and T 50 Distances a , b

Equations (4)

Equations on this page are rendered with MathJax. Learn more.

C T 50 = C Center + T 50 EV EV 2 ,
CV = S T 50 ,
CV surface RIT CV LCD IDD CV LCD RIT .
CV surface IDD CV surface RIT CV LCD IDD ,

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