Abstract

We generalize, to images with continuously varying colors, our previously published model for comparing color differences of spatially discrete visual fields (icons, symbols) of disparate sizes. Our model is structural, including scattering of light by the intraocular media, followed by sparse retinal cone cell sampling of each physiological color primary. We use our model to show that small subtense of less than half a degree drastically reduces the number of discriminable colors available within a color gamut. The proposed generalization predicts and explains appearance of color fields having a wide range of subtenses (from 1/8deg to 44 deg in examples given).

© 2012 Optical Society of America

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References

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  1. R. C. Carter and L. D. Silverstein, “Size matters: improved color-difference estimation for small visual targets,” J. Soc. Inf. Disp. 18, 17–28 (2010).
    [CrossRef]
  2. X. Zhang and B. A. Wandell, “A spatial extension of CIELAB for digital color image reproduction,” SID Symp. Digest 27, 731–734 (1996).
  3. G. Kutas and P. Bodrogi, “Color appearance of a large homogeneous visual field,” Color Res. Appl. 33, 45–54 (2008).
    [CrossRef]
  4. K. Xiao, R. M. Luo, C. Li, and H. Gouwei, “Color appearance of room colors,” Color Res. Appl. 35, 284–293 (2010).
    [CrossRef]
  5. F. A. A. Kingdom and P. Whittle, “Contrast discrimination at high contrasts reveals the influence of local light adaptation on contrast processing,” Vision Res. 36, 817–829 (1996).
    [CrossRef]
  6. I. K. Ijspeert, T. J. T. P. van den Berg, and H. Spekreijse, “An improved mathematical description of the foveal visual point spread function with parameters for age, pupil size and pigmentation,” Vision Res. 33, 15–20 (1993).
    [CrossRef]
  7. T. J. T. P. van den Berg, “Analysis of intraocular straylight, especially in relation to age,” Optom. Vision Sci. 72, 52–59 (1995).
    [CrossRef]
  8. S. M. Highnote, “Color discrimination of small targets,” Ph.D. dissertation (University of California, San Diego, 2003), available from UMI ProQuest www.il.proquest.com .
  9. A. R. Jacobsen, “Predictive color modeling for targets of small visual angle,” Soc. Info. Display Digest 19, 69–72 (1988).
  10. A. B. Poirson and B. A. Wandell, “Pattern-color separable pathways predict sensitivity to simple colored patterns,” Vision Res. 35, 2458–2470 (1996).
    [CrossRef]
  11. R. Carter and E. Carter, “Color coding for rapid location of small symbols,” Color Res. Appl. 13, 226–234 (1988).
    [CrossRef]
  12. T. Regier, P. Kay, and N. Khetarpal, “Color naming reflects optimal partitions of color space,” Proc. Natl. Acad. Sci. USA 104, 1436–1441 (2007).
    [CrossRef]
  13. Personal communication from Harvey Smallman to the senior author in 2009, based upon H. S. Smallman and R. M. Boynton, “Segregation of basic colors in an information display,” J. Opt. Soc. Am. A 7, 1985–1994 (1990).
    [CrossRef]
  14. G. Deutscher, Through The Language Glass (Metropolitan Books Henry Holt & Co., 2010), ISBN 978-0-8050-8195-4.
  15. K. L. Kelly, “Twenty-two colors of maximum contrast,” Color Eng. 3, 26–27 (1965).
  16. M. C. Cahill and R. C. Carter, “Color code size for searching displays of different density,” Hum. Factors 18, 273–280 (1976).
  17. R. C. Carter and E. C. Carter, “High-contrast sets of colors,” Appl. Opt. 21, 2936–2939 (1982).
    [CrossRef]
  18. L. D. Silverstein, J. S. Lepkowski, R. C. Carter, and E. C. Carter, “Modeling of display color parameters and algorithmic color selection,” Proc. SPIE 624, 26–34 (1986).
    [CrossRef]
  19. R. C. Carter and R. Huertas, “Ultra-large color difference and small subtense,” Color Res. Appl. 35, 4–17 (2010).
    [CrossRef]
  20. R. S. Berns, Billmeyer and Saltzman’s Principles of Color Technology, 2nd ed. (Wiley, 2000).
  21. K. Xiao, M. R. Luo, C. Li, G. Cui, and D. Park, “Investigation of colour size effect for colour appearance assessment,” Color Res. Appl.36, 201–209 (2011).
    [CrossRef]
  22. B. R. Wooten and G. A. Geri, “Psychophysical determination of intraocular light scatter as a function of wavelength,” Vision Res. 27, 1291–1298 (1987).
    [CrossRef]
  23. A. Guirao, C. Gonzalez, M. Redondo, E. Geraghty, S. Norrby, and P. Arial, “Average optical performance of the human eye as a function of age in a normal population,” Invest. Ophthalmol. Vision Sci. 40, 203–213 (1999).
  24. J. McLellan, S. Marcos, and S. Burns, “Age-related changes in monochromatic wave aberrations of the human eye,” Invest. Ophthalmol. Vision Sci. 42, 1390–1395 (2001).
  25. C. McKee, Human Engineering Laboratory, Aberdeen Proving Ground (personal communication, 1997).
  26. G. M. Johnson and M. D. Fairchild, “A top-down description of S-CIELAB and CIEDE2000,” Color Res. Appl. 28, 425–435 (2003).
    [CrossRef]

2010 (3)

R. C. Carter and L. D. Silverstein, “Size matters: improved color-difference estimation for small visual targets,” J. Soc. Inf. Disp. 18, 17–28 (2010).
[CrossRef]

K. Xiao, R. M. Luo, C. Li, and H. Gouwei, “Color appearance of room colors,” Color Res. Appl. 35, 284–293 (2010).
[CrossRef]

R. C. Carter and R. Huertas, “Ultra-large color difference and small subtense,” Color Res. Appl. 35, 4–17 (2010).
[CrossRef]

2008 (1)

G. Kutas and P. Bodrogi, “Color appearance of a large homogeneous visual field,” Color Res. Appl. 33, 45–54 (2008).
[CrossRef]

2007 (1)

T. Regier, P. Kay, and N. Khetarpal, “Color naming reflects optimal partitions of color space,” Proc. Natl. Acad. Sci. USA 104, 1436–1441 (2007).
[CrossRef]

2003 (1)

G. M. Johnson and M. D. Fairchild, “A top-down description of S-CIELAB and CIEDE2000,” Color Res. Appl. 28, 425–435 (2003).
[CrossRef]

2001 (1)

J. McLellan, S. Marcos, and S. Burns, “Age-related changes in monochromatic wave aberrations of the human eye,” Invest. Ophthalmol. Vision Sci. 42, 1390–1395 (2001).

1999 (1)

A. Guirao, C. Gonzalez, M. Redondo, E. Geraghty, S. Norrby, and P. Arial, “Average optical performance of the human eye as a function of age in a normal population,” Invest. Ophthalmol. Vision Sci. 40, 203–213 (1999).

1996 (3)

F. A. A. Kingdom and P. Whittle, “Contrast discrimination at high contrasts reveals the influence of local light adaptation on contrast processing,” Vision Res. 36, 817–829 (1996).
[CrossRef]

X. Zhang and B. A. Wandell, “A spatial extension of CIELAB for digital color image reproduction,” SID Symp. Digest 27, 731–734 (1996).

A. B. Poirson and B. A. Wandell, “Pattern-color separable pathways predict sensitivity to simple colored patterns,” Vision Res. 35, 2458–2470 (1996).
[CrossRef]

1995 (1)

T. J. T. P. van den Berg, “Analysis of intraocular straylight, especially in relation to age,” Optom. Vision Sci. 72, 52–59 (1995).
[CrossRef]

1993 (1)

I. K. Ijspeert, T. J. T. P. van den Berg, and H. Spekreijse, “An improved mathematical description of the foveal visual point spread function with parameters for age, pupil size and pigmentation,” Vision Res. 33, 15–20 (1993).
[CrossRef]

1990 (1)

1988 (2)

A. R. Jacobsen, “Predictive color modeling for targets of small visual angle,” Soc. Info. Display Digest 19, 69–72 (1988).

R. Carter and E. Carter, “Color coding for rapid location of small symbols,” Color Res. Appl. 13, 226–234 (1988).
[CrossRef]

1987 (1)

B. R. Wooten and G. A. Geri, “Psychophysical determination of intraocular light scatter as a function of wavelength,” Vision Res. 27, 1291–1298 (1987).
[CrossRef]

1986 (1)

L. D. Silverstein, J. S. Lepkowski, R. C. Carter, and E. C. Carter, “Modeling of display color parameters and algorithmic color selection,” Proc. SPIE 624, 26–34 (1986).
[CrossRef]

1982 (1)

1976 (1)

M. C. Cahill and R. C. Carter, “Color code size for searching displays of different density,” Hum. Factors 18, 273–280 (1976).

1965 (1)

K. L. Kelly, “Twenty-two colors of maximum contrast,” Color Eng. 3, 26–27 (1965).

Arial, P.

A. Guirao, C. Gonzalez, M. Redondo, E. Geraghty, S. Norrby, and P. Arial, “Average optical performance of the human eye as a function of age in a normal population,” Invest. Ophthalmol. Vision Sci. 40, 203–213 (1999).

Berns, R. S.

R. S. Berns, Billmeyer and Saltzman’s Principles of Color Technology, 2nd ed. (Wiley, 2000).

Bodrogi, P.

G. Kutas and P. Bodrogi, “Color appearance of a large homogeneous visual field,” Color Res. Appl. 33, 45–54 (2008).
[CrossRef]

Boynton, R. M.

Burns, S.

J. McLellan, S. Marcos, and S. Burns, “Age-related changes in monochromatic wave aberrations of the human eye,” Invest. Ophthalmol. Vision Sci. 42, 1390–1395 (2001).

Cahill, M. C.

M. C. Cahill and R. C. Carter, “Color code size for searching displays of different density,” Hum. Factors 18, 273–280 (1976).

Carter, E.

R. Carter and E. Carter, “Color coding for rapid location of small symbols,” Color Res. Appl. 13, 226–234 (1988).
[CrossRef]

Carter, E. C.

L. D. Silverstein, J. S. Lepkowski, R. C. Carter, and E. C. Carter, “Modeling of display color parameters and algorithmic color selection,” Proc. SPIE 624, 26–34 (1986).
[CrossRef]

R. C. Carter and E. C. Carter, “High-contrast sets of colors,” Appl. Opt. 21, 2936–2939 (1982).
[CrossRef]

Carter, R.

R. Carter and E. Carter, “Color coding for rapid location of small symbols,” Color Res. Appl. 13, 226–234 (1988).
[CrossRef]

Carter, R. C.

R. C. Carter and R. Huertas, “Ultra-large color difference and small subtense,” Color Res. Appl. 35, 4–17 (2010).
[CrossRef]

R. C. Carter and L. D. Silverstein, “Size matters: improved color-difference estimation for small visual targets,” J. Soc. Inf. Disp. 18, 17–28 (2010).
[CrossRef]

L. D. Silverstein, J. S. Lepkowski, R. C. Carter, and E. C. Carter, “Modeling of display color parameters and algorithmic color selection,” Proc. SPIE 624, 26–34 (1986).
[CrossRef]

R. C. Carter and E. C. Carter, “High-contrast sets of colors,” Appl. Opt. 21, 2936–2939 (1982).
[CrossRef]

M. C. Cahill and R. C. Carter, “Color code size for searching displays of different density,” Hum. Factors 18, 273–280 (1976).

Cui, G.

K. Xiao, M. R. Luo, C. Li, G. Cui, and D. Park, “Investigation of colour size effect for colour appearance assessment,” Color Res. Appl.36, 201–209 (2011).
[CrossRef]

Deutscher, G.

G. Deutscher, Through The Language Glass (Metropolitan Books Henry Holt & Co., 2010), ISBN 978-0-8050-8195-4.

Fairchild, M. D.

G. M. Johnson and M. D. Fairchild, “A top-down description of S-CIELAB and CIEDE2000,” Color Res. Appl. 28, 425–435 (2003).
[CrossRef]

Geraghty, E.

A. Guirao, C. Gonzalez, M. Redondo, E. Geraghty, S. Norrby, and P. Arial, “Average optical performance of the human eye as a function of age in a normal population,” Invest. Ophthalmol. Vision Sci. 40, 203–213 (1999).

Geri, G. A.

B. R. Wooten and G. A. Geri, “Psychophysical determination of intraocular light scatter as a function of wavelength,” Vision Res. 27, 1291–1298 (1987).
[CrossRef]

Gonzalez, C.

A. Guirao, C. Gonzalez, M. Redondo, E. Geraghty, S. Norrby, and P. Arial, “Average optical performance of the human eye as a function of age in a normal population,” Invest. Ophthalmol. Vision Sci. 40, 203–213 (1999).

Gouwei, H.

K. Xiao, R. M. Luo, C. Li, and H. Gouwei, “Color appearance of room colors,” Color Res. Appl. 35, 284–293 (2010).
[CrossRef]

Guirao, A.

A. Guirao, C. Gonzalez, M. Redondo, E. Geraghty, S. Norrby, and P. Arial, “Average optical performance of the human eye as a function of age in a normal population,” Invest. Ophthalmol. Vision Sci. 40, 203–213 (1999).

Highnote, S. M.

S. M. Highnote, “Color discrimination of small targets,” Ph.D. dissertation (University of California, San Diego, 2003), available from UMI ProQuest www.il.proquest.com .

Huertas, R.

R. C. Carter and R. Huertas, “Ultra-large color difference and small subtense,” Color Res. Appl. 35, 4–17 (2010).
[CrossRef]

Ijspeert, I. K.

I. K. Ijspeert, T. J. T. P. van den Berg, and H. Spekreijse, “An improved mathematical description of the foveal visual point spread function with parameters for age, pupil size and pigmentation,” Vision Res. 33, 15–20 (1993).
[CrossRef]

Jacobsen, A. R.

A. R. Jacobsen, “Predictive color modeling for targets of small visual angle,” Soc. Info. Display Digest 19, 69–72 (1988).

Johnson, G. M.

G. M. Johnson and M. D. Fairchild, “A top-down description of S-CIELAB and CIEDE2000,” Color Res. Appl. 28, 425–435 (2003).
[CrossRef]

Kay, P.

T. Regier, P. Kay, and N. Khetarpal, “Color naming reflects optimal partitions of color space,” Proc. Natl. Acad. Sci. USA 104, 1436–1441 (2007).
[CrossRef]

Kelly, K. L.

K. L. Kelly, “Twenty-two colors of maximum contrast,” Color Eng. 3, 26–27 (1965).

Khetarpal, N.

T. Regier, P. Kay, and N. Khetarpal, “Color naming reflects optimal partitions of color space,” Proc. Natl. Acad. Sci. USA 104, 1436–1441 (2007).
[CrossRef]

Kingdom, F. A. A.

F. A. A. Kingdom and P. Whittle, “Contrast discrimination at high contrasts reveals the influence of local light adaptation on contrast processing,” Vision Res. 36, 817–829 (1996).
[CrossRef]

Kutas, G.

G. Kutas and P. Bodrogi, “Color appearance of a large homogeneous visual field,” Color Res. Appl. 33, 45–54 (2008).
[CrossRef]

Lepkowski, J. S.

L. D. Silverstein, J. S. Lepkowski, R. C. Carter, and E. C. Carter, “Modeling of display color parameters and algorithmic color selection,” Proc. SPIE 624, 26–34 (1986).
[CrossRef]

Li, C.

K. Xiao, R. M. Luo, C. Li, and H. Gouwei, “Color appearance of room colors,” Color Res. Appl. 35, 284–293 (2010).
[CrossRef]

K. Xiao, M. R. Luo, C. Li, G. Cui, and D. Park, “Investigation of colour size effect for colour appearance assessment,” Color Res. Appl.36, 201–209 (2011).
[CrossRef]

Luo, M. R.

K. Xiao, M. R. Luo, C. Li, G. Cui, and D. Park, “Investigation of colour size effect for colour appearance assessment,” Color Res. Appl.36, 201–209 (2011).
[CrossRef]

Luo, R. M.

K. Xiao, R. M. Luo, C. Li, and H. Gouwei, “Color appearance of room colors,” Color Res. Appl. 35, 284–293 (2010).
[CrossRef]

Marcos, S.

J. McLellan, S. Marcos, and S. Burns, “Age-related changes in monochromatic wave aberrations of the human eye,” Invest. Ophthalmol. Vision Sci. 42, 1390–1395 (2001).

McKee, C.

C. McKee, Human Engineering Laboratory, Aberdeen Proving Ground (personal communication, 1997).

McLellan, J.

J. McLellan, S. Marcos, and S. Burns, “Age-related changes in monochromatic wave aberrations of the human eye,” Invest. Ophthalmol. Vision Sci. 42, 1390–1395 (2001).

Norrby, S.

A. Guirao, C. Gonzalez, M. Redondo, E. Geraghty, S. Norrby, and P. Arial, “Average optical performance of the human eye as a function of age in a normal population,” Invest. Ophthalmol. Vision Sci. 40, 203–213 (1999).

Park, D.

K. Xiao, M. R. Luo, C. Li, G. Cui, and D. Park, “Investigation of colour size effect for colour appearance assessment,” Color Res. Appl.36, 201–209 (2011).
[CrossRef]

Poirson, A. B.

A. B. Poirson and B. A. Wandell, “Pattern-color separable pathways predict sensitivity to simple colored patterns,” Vision Res. 35, 2458–2470 (1996).
[CrossRef]

Redondo, M.

A. Guirao, C. Gonzalez, M. Redondo, E. Geraghty, S. Norrby, and P. Arial, “Average optical performance of the human eye as a function of age in a normal population,” Invest. Ophthalmol. Vision Sci. 40, 203–213 (1999).

Regier, T.

T. Regier, P. Kay, and N. Khetarpal, “Color naming reflects optimal partitions of color space,” Proc. Natl. Acad. Sci. USA 104, 1436–1441 (2007).
[CrossRef]

Silverstein, L. D.

R. C. Carter and L. D. Silverstein, “Size matters: improved color-difference estimation for small visual targets,” J. Soc. Inf. Disp. 18, 17–28 (2010).
[CrossRef]

L. D. Silverstein, J. S. Lepkowski, R. C. Carter, and E. C. Carter, “Modeling of display color parameters and algorithmic color selection,” Proc. SPIE 624, 26–34 (1986).
[CrossRef]

Smallman, H. S.

Spekreijse, H.

I. K. Ijspeert, T. J. T. P. van den Berg, and H. Spekreijse, “An improved mathematical description of the foveal visual point spread function with parameters for age, pupil size and pigmentation,” Vision Res. 33, 15–20 (1993).
[CrossRef]

van den Berg, T. J. T. P.

T. J. T. P. van den Berg, “Analysis of intraocular straylight, especially in relation to age,” Optom. Vision Sci. 72, 52–59 (1995).
[CrossRef]

I. K. Ijspeert, T. J. T. P. van den Berg, and H. Spekreijse, “An improved mathematical description of the foveal visual point spread function with parameters for age, pupil size and pigmentation,” Vision Res. 33, 15–20 (1993).
[CrossRef]

Wandell, B. A.

A. B. Poirson and B. A. Wandell, “Pattern-color separable pathways predict sensitivity to simple colored patterns,” Vision Res. 35, 2458–2470 (1996).
[CrossRef]

X. Zhang and B. A. Wandell, “A spatial extension of CIELAB for digital color image reproduction,” SID Symp. Digest 27, 731–734 (1996).

Whittle, P.

F. A. A. Kingdom and P. Whittle, “Contrast discrimination at high contrasts reveals the influence of local light adaptation on contrast processing,” Vision Res. 36, 817–829 (1996).
[CrossRef]

Wooten, B. R.

B. R. Wooten and G. A. Geri, “Psychophysical determination of intraocular light scatter as a function of wavelength,” Vision Res. 27, 1291–1298 (1987).
[CrossRef]

Xiao, K.

K. Xiao, R. M. Luo, C. Li, and H. Gouwei, “Color appearance of room colors,” Color Res. Appl. 35, 284–293 (2010).
[CrossRef]

K. Xiao, M. R. Luo, C. Li, G. Cui, and D. Park, “Investigation of colour size effect for colour appearance assessment,” Color Res. Appl.36, 201–209 (2011).
[CrossRef]

Zhang, X.

X. Zhang and B. A. Wandell, “A spatial extension of CIELAB for digital color image reproduction,” SID Symp. Digest 27, 731–734 (1996).

Appl. Opt. (1)

Color Eng. (1)

K. L. Kelly, “Twenty-two colors of maximum contrast,” Color Eng. 3, 26–27 (1965).

Color Res. Appl. (5)

G. M. Johnson and M. D. Fairchild, “A top-down description of S-CIELAB and CIEDE2000,” Color Res. Appl. 28, 425–435 (2003).
[CrossRef]

G. Kutas and P. Bodrogi, “Color appearance of a large homogeneous visual field,” Color Res. Appl. 33, 45–54 (2008).
[CrossRef]

K. Xiao, R. M. Luo, C. Li, and H. Gouwei, “Color appearance of room colors,” Color Res. Appl. 35, 284–293 (2010).
[CrossRef]

R. Carter and E. Carter, “Color coding for rapid location of small symbols,” Color Res. Appl. 13, 226–234 (1988).
[CrossRef]

R. C. Carter and R. Huertas, “Ultra-large color difference and small subtense,” Color Res. Appl. 35, 4–17 (2010).
[CrossRef]

Hum. Factors (1)

M. C. Cahill and R. C. Carter, “Color code size for searching displays of different density,” Hum. Factors 18, 273–280 (1976).

Invest. Ophthalmol. Vision Sci. (2)

A. Guirao, C. Gonzalez, M. Redondo, E. Geraghty, S. Norrby, and P. Arial, “Average optical performance of the human eye as a function of age in a normal population,” Invest. Ophthalmol. Vision Sci. 40, 203–213 (1999).

J. McLellan, S. Marcos, and S. Burns, “Age-related changes in monochromatic wave aberrations of the human eye,” Invest. Ophthalmol. Vision Sci. 42, 1390–1395 (2001).

J. Opt. Soc. Am. A (1)

J. Soc. Inf. Disp. (1)

R. C. Carter and L. D. Silverstein, “Size matters: improved color-difference estimation for small visual targets,” J. Soc. Inf. Disp. 18, 17–28 (2010).
[CrossRef]

Optom. Vision Sci. (1)

T. J. T. P. van den Berg, “Analysis of intraocular straylight, especially in relation to age,” Optom. Vision Sci. 72, 52–59 (1995).
[CrossRef]

Proc. Natl. Acad. Sci. USA (1)

T. Regier, P. Kay, and N. Khetarpal, “Color naming reflects optimal partitions of color space,” Proc. Natl. Acad. Sci. USA 104, 1436–1441 (2007).
[CrossRef]

Proc. SPIE (1)

L. D. Silverstein, J. S. Lepkowski, R. C. Carter, and E. C. Carter, “Modeling of display color parameters and algorithmic color selection,” Proc. SPIE 624, 26–34 (1986).
[CrossRef]

SID Symp. Digest (1)

X. Zhang and B. A. Wandell, “A spatial extension of CIELAB for digital color image reproduction,” SID Symp. Digest 27, 731–734 (1996).

Soc. Info. Display Digest (1)

A. R. Jacobsen, “Predictive color modeling for targets of small visual angle,” Soc. Info. Display Digest 19, 69–72 (1988).

Vision Res. (4)

A. B. Poirson and B. A. Wandell, “Pattern-color separable pathways predict sensitivity to simple colored patterns,” Vision Res. 35, 2458–2470 (1996).
[CrossRef]

F. A. A. Kingdom and P. Whittle, “Contrast discrimination at high contrasts reveals the influence of local light adaptation on contrast processing,” Vision Res. 36, 817–829 (1996).
[CrossRef]

I. K. Ijspeert, T. J. T. P. van den Berg, and H. Spekreijse, “An improved mathematical description of the foveal visual point spread function with parameters for age, pupil size and pigmentation,” Vision Res. 33, 15–20 (1993).
[CrossRef]

B. R. Wooten and G. A. Geri, “Psychophysical determination of intraocular light scatter as a function of wavelength,” Vision Res. 27, 1291–1298 (1987).
[CrossRef]

Other (5)

G. Deutscher, Through The Language Glass (Metropolitan Books Henry Holt & Co., 2010), ISBN 978-0-8050-8195-4.

S. M. Highnote, “Color discrimination of small targets,” Ph.D. dissertation (University of California, San Diego, 2003), available from UMI ProQuest www.il.proquest.com .

C. McKee, Human Engineering Laboratory, Aberdeen Proving Ground (personal communication, 1997).

R. S. Berns, Billmeyer and Saltzman’s Principles of Color Technology, 2nd ed. (Wiley, 2000).

K. Xiao, M. R. Luo, C. Li, G. Cui, and D. Park, “Investigation of colour size effect for colour appearance assessment,” Color Res. Appl.36, 201–209 (2011).
[CrossRef]

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Figures (5)

Fig. 1.
Fig. 1.

Diagram of the structural model of Carter and Silverstein [1], in which measured tristimulus values from discrete color targets are transformed to cone primaries (LMS). Cone primaries are attenuated first to account for intraocular scattering and second to account for sparse sampling by the retinal mosaic of cone cells. The resulting attenuated cone primaries are back-transformed to tristimulus values, which may be used to calculate any metric representing the color difference between the targets.

Fig. 2.
Fig. 2.

Cone primary attenuation due to visual subtense, translated from three different sources [2,8,9]. Scatterplot matrix (with 95% confidence ellipses); Key: L, M, and S attenuations represented, respectively, by red, green, and blue symbols; disks for 60, solid boxes for 30, circles for 15, asterisks for 7.5, and a hollow square for the normalized 120 value of unity.

Fig. 3.
Fig. 3.

Inverse search time (1/s) from Carter and Carter [11] as a function of color difference (CIEDE2000 mediated by the Generalized Model using intraocular scattering coefficients derived from the van den Berg PSF) between color-coded targets and distracters. Geometric symbols represent 120 data: black disks for black surround, asterisks for gray surround, white-interior square for white surround, and white-interior circles for bright white surround. Letters represent 7.5 data: X for black surround, Y for gray surround, Δ for white surround, and Z for bright white surround. Small black blocks represent intermediate subtenses. Figure 3 for the GM may be compared to the similar Figures for S-CIEDE2000 and the SM (and uncorrected CIEDE2000) published by Carter and Silverstein [1].

Fig. 4.
Fig. 4.

Lightnesses (L*) observed at Leeds versus L* predicted by the GM for 10 color loci at 2, 8, 19, and 22 deg subtense. Kernel and PSF subtenses in degrees are indicated in the abscissa label. These are data from groups 1 and 2, with 44 deg data used as the standard from which the 2, 8, 19, and 22 deg predictions were calculated by the GM. Colors of the data points correspond to Xiao’s [21] names, with names modified by II being represented by darker symbols. Disks, squares, asterisks and boxes stand, respectively, for 2, 8, 19, and 22 deg. Red curve is the 95% confidence ellipse for a normal distribution. The GM was calculated with 27 deg PSF, and 0.5 and 15 deg RG and BY kernels, and with a 5 deg LD kernel.

Fig. 5.
Fig. 5.

Colorfulness (DE2000 C*) observed at Leeds versus C* predicted by the GM for 10 color loci at 2, 8, 19, and 22 deg subtense. Kernel and PSF subtenses in degrees are indicated in the abscissa label. These are data from groups 1 and 2, with 44 deg data used as the standard from which the 2, 8, 19, and 22 deg predictions were calculated by the GM. Colors of the data points correspond to Xiao’s [21] names, with names modified by II being represented by darker symbols. Disks, squares, asterisks, and boxes stand, respectively, for 2, 8, 19, and 22 deg. Red curve is the 95% confidence ellipse for a normal distribution. The GM was calculated with 27 deg PSF, and 0.5 and 15 deg RG and BY kernels, and with a 5 deg LD kernel.

Tables (9)

Tables Icon

Table 1. Multivariate Correlations of Cone Primary Attenuations Derived from Experiments of Jacobsen, Highnote, and Zhang–Wandell (for 120, 60, 30, 15 and 7.5; normalized to 120threshold=1)

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Table 2. Proportion of Target Contrast (|Target IntensitySurround Intensity|) That Is Lost to Scatteringa

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Table 3. Relation between Inverse Search Time (1/s) and CIEDE2000, as Mediated by Various Models of Effects of Subtense

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Table 4. Statistics Associated with Fig 3, Inverse Search Time versus CIEDE2000 Calculated from Tristimulus Values Preprocessed with the GM Using Zhang–Wandell Kernels and the van den Berg PSF

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Table 5. Display Primary Tristimulus Values

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Table 6. Example of Optimal Selection of Four Colors Corresponding to the 4-Color 2 Deg Result in Table 7

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Table 7. Maximized Minimum Color Difference (CIEDE2000) for 2 to 17 Colors

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Table 8. Jacobsen’s [9] CIELUV Color Difference Thresholds

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Table 9. Contribution of the GM to Predicting Leeds Data Variance beyond Baseline

Equations (10)

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

x=27u/(18u48v+36)
y=12v/(18u48v+36).
x=X/(X+Y+Z)
y=Y/(X+Y+Z).
X=(Y)(x/y)
Z=(Y/y)(1x)Y,
dX=duXu+dvXv+dLXL.
dX=du([L+16116]327Yo12v)+dv(27u12v2[L+16116]3Yo)+dL(Yo116327u12v[3L2+96L+768])
dY=dLYo(3L2+96L+768)1163
dZ=du(L+16116)3Yo(912v)+dv(L+16116)3Yo((12)(48)u12v(18u48v+36)+{27u18u48v+361}{(12)(18u+36)(12v)2})+dL(1116)3Yo(3L2+96L+768)((3660v9u)12v).

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