Abstract

The appearance of four different images from three different distances was simulated by using the individual contrast sensitivity functions (CSF’s) of normally sighted observers. The simulations were generated by using the observers’ CSF’s as a threshold in a pyramidal vision model of band-limited local contrast [ J. Opt. Soc. Am. A 7, 2030 ( 1990)]. Simulations based on CSF’s obtained in an orientation discrimination task underestimated the observer’s sensitivity in discriminating the images. Simulations based on CSF’s obtained in a detection task provided a good estimate of observer’s performance. The testing method was shown to be sensitive enough to be affected by the high-frequency residual, which is frequently ignored in visual models and simulations. An image-dependence effect found when the high-frequency residual was present was eliminated when the residual artifact was removed. The simulations based on the pyramidal vision model accurately predicted the distance at which they were discriminated from the original image, and thus this model may also serve as the basis for image-quality metrics. The testing method developed can also be used to determine the type of CSF that best represents observer performance in a task.

© 1996 Optical Society of America

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References

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  1. B. L. Lundh, G. Derefeldt, S. Nyberg, G. Lennerstrand, “Picture simulation of contrast sensitivity in organic and functional amblyopia,” Acta Ophthalmol. 59, 774–783 (1981).
  2. D. Pelli, “What is low vision?” Videotape presentation, Syracuse University, Syracuse, N.Y., 1990.
  3. A. P. Ginsburg, “Visual information processing based on spatial filters constrained by biological data,” Ph.D. dissertation (Cambridge University, Cambridge, 1978).
  4. L. N. Thibos, A. Bradley, “The limits of performance in central and peripheral vision,” in 1991 SID International Symposium, Vol. 22 of 1991 SID Digest of Technical Papers (Society for Information Display, Playa del Rey, Calif., 1991), pp. 301–303.
  5. J. Larimer, “Desigining tomorrow’s displays,”NASA Tech. Briefs 17(4), 14–16 (1993).
  6. J. Lubin, “A visual discrimination model for imaging system design and evaluation,” in Vision Models for Target Detection and Recognition, E. Peli, ed. (World Scientific, Singapore, 1995), pp. 245–283.
    [Crossref]
  7. E. Peli, ed., Vision Models for Target Detection and Recognition (World Scientific, Singapore, 1995).
    [Crossref]
  8. E. Peli, “Contrast in complex images,” J. Opt. Soc. Am. A 7, 2030–2040 (1990).
    [Crossref]
  9. E. Peli, R. B. Goldstein, G. M. Young, C. L. Trempe, S. M. Buzney, “Image enhancement for the visually impaired: simulations and experimental results,” Invest. Ophthalmol. Vis. Sci. 32, 2337–2350 (1991).
    [PubMed]
  10. E. Peli, E. Lee, C. L. Trempe, S. Buzney, “Image enhancement for the visually impaired: the effects of enhancement on face recognition,” J. Opt. Soc. Am. A 11, 1929–1939 (1994).
    [Crossref]
  11. E. Peli, J. Yang, R. Goldstein, “Image invariance with changes in size: the role of peripheral contrast thresholds,” J. Opt. Soc. Am. A 8, 1762–1774 (1991).
    [Crossref] [PubMed]
  12. M. Duval-Destin, “A spatio-temporal complete description of contrast,” in 1991 SID International Symposium, Vol. 22 of 1991 SID Digest of Technical Papers (Society for Information Display, Playa del Rey, Calif., 1991), pp. 615–618.
  13. S. Daly, “The visual differences predictor: an algorithm for the assessment of image fidelity,” in Human Vision, Visual Processing, and Digital Display III, B. E. Rogowitz, ed., Proc. SPIE1666, 2–15 (1992).
    [Crossref]
  14. E. Peli, L. Arend, G. Young, R. Goldstein, “Contrast sensitivity to patch stimuli: effects of spatial bandwidth and temporal presentation,” Spatial Vis. 7, 1–14 (1993).
    [Crossref]
  15. C. W. Tyler, “Is the illusory triangle physical or imaginary?” Perception 6, 603–604 (1977).
    [PubMed]
  16. E. Peli, “Simulating normal and low vision,” in Vision Models for Target Detection and Recognition, E. Peli, ed. (World Scientific, Singapore, 1995), pp. 63–87.
    [Crossref]
  17. N. Brady, D. J. Field, “What’s constant in contrast constancy? The effects of scaling on the perceived contrast of bandpass patterns,” Vision Res. 35, 739–756 (1995).
    [Crossref] [PubMed]
  18. B. R. Stephens, M. S. Banks, “The development of contrast constancy,”J. Exp. Child Psychol. 40, 528–547 (1985).
    [Crossref] [PubMed]
  19. D. J. Field, “Relations between the statistics of natural images and the response properties of cortical cells,” J. Opt. Soc. Am. A 4, 2379–2394 (1987).
    [Crossref] [PubMed]
  20. D. J. Tolhurst, Y. Tadmor, T. Chao, “The amplitude spectra of natural images,” Ophthalmic Physiol. Opt. 12, 229–232 (1992).
    [Crossref] [PubMed]
  21. E. Peli, R. B. Goldstein, G. M. Young, L. E. Arend, “Contrast sensitivity functions for analysis and simulation of visual perception,” in Noninvasive Assessment of the Visual System, Vol. 3 of 1990 OSA Technical Digest Series (Optical Society of America, Washington, D.C., 1990), pp. 126–129.
  22. A. B. Watson, “The cortex transform: rapid computation of simulated neural images,” Comput. Vision, Graphics, Image Process. 39, 311–327 (1987).
    [Crossref]
  23. E. Peli, “Display nonlinearity in digital image processing for visual communications,” Opt. Eng. 31, 2374–2382 (1992).
    [Crossref]
  24. A. B. Watson, “Efficiency of a model human image code,” J. Opt. Soc. Am. A 4, 2401–2417 (1987).
    [Crossref] [PubMed]
  25. E. Peli, “Hilbert transform pairs mechanisms,” Invest. Ophthalmol. Vis. Sci. Suppl. 30, 110 (1989).
  26. F. W. Campbell, J. J. Kulikowski, J. Levinson, “The effect of orientation on the visual resolution of gratings,”J. Physiol. (London) 187, 427–436 (1966).

1995 (1)

N. Brady, D. J. Field, “What’s constant in contrast constancy? The effects of scaling on the perceived contrast of bandpass patterns,” Vision Res. 35, 739–756 (1995).
[Crossref] [PubMed]

1994 (1)

1993 (2)

E. Peli, L. Arend, G. Young, R. Goldstein, “Contrast sensitivity to patch stimuli: effects of spatial bandwidth and temporal presentation,” Spatial Vis. 7, 1–14 (1993).
[Crossref]

J. Larimer, “Desigining tomorrow’s displays,”NASA Tech. Briefs 17(4), 14–16 (1993).

1992 (2)

D. J. Tolhurst, Y. Tadmor, T. Chao, “The amplitude spectra of natural images,” Ophthalmic Physiol. Opt. 12, 229–232 (1992).
[Crossref] [PubMed]

E. Peli, “Display nonlinearity in digital image processing for visual communications,” Opt. Eng. 31, 2374–2382 (1992).
[Crossref]

1991 (2)

E. Peli, R. B. Goldstein, G. M. Young, C. L. Trempe, S. M. Buzney, “Image enhancement for the visually impaired: simulations and experimental results,” Invest. Ophthalmol. Vis. Sci. 32, 2337–2350 (1991).
[PubMed]

E. Peli, J. Yang, R. Goldstein, “Image invariance with changes in size: the role of peripheral contrast thresholds,” J. Opt. Soc. Am. A 8, 1762–1774 (1991).
[Crossref] [PubMed]

1990 (1)

E. Peli, “Contrast in complex images,” J. Opt. Soc. Am. A 7, 2030–2040 (1990).
[Crossref]

1989 (1)

E. Peli, “Hilbert transform pairs mechanisms,” Invest. Ophthalmol. Vis. Sci. Suppl. 30, 110 (1989).

1987 (3)

1985 (1)

B. R. Stephens, M. S. Banks, “The development of contrast constancy,”J. Exp. Child Psychol. 40, 528–547 (1985).
[Crossref] [PubMed]

1981 (1)

B. L. Lundh, G. Derefeldt, S. Nyberg, G. Lennerstrand, “Picture simulation of contrast sensitivity in organic and functional amblyopia,” Acta Ophthalmol. 59, 774–783 (1981).

1977 (1)

C. W. Tyler, “Is the illusory triangle physical or imaginary?” Perception 6, 603–604 (1977).
[PubMed]

1966 (1)

F. W. Campbell, J. J. Kulikowski, J. Levinson, “The effect of orientation on the visual resolution of gratings,”J. Physiol. (London) 187, 427–436 (1966).

Arend, L.

E. Peli, L. Arend, G. Young, R. Goldstein, “Contrast sensitivity to patch stimuli: effects of spatial bandwidth and temporal presentation,” Spatial Vis. 7, 1–14 (1993).
[Crossref]

Arend, L. E.

E. Peli, R. B. Goldstein, G. M. Young, L. E. Arend, “Contrast sensitivity functions for analysis and simulation of visual perception,” in Noninvasive Assessment of the Visual System, Vol. 3 of 1990 OSA Technical Digest Series (Optical Society of America, Washington, D.C., 1990), pp. 126–129.

Banks, M. S.

B. R. Stephens, M. S. Banks, “The development of contrast constancy,”J. Exp. Child Psychol. 40, 528–547 (1985).
[Crossref] [PubMed]

Bradley, A.

L. N. Thibos, A. Bradley, “The limits of performance in central and peripheral vision,” in 1991 SID International Symposium, Vol. 22 of 1991 SID Digest of Technical Papers (Society for Information Display, Playa del Rey, Calif., 1991), pp. 301–303.

Brady, N.

N. Brady, D. J. Field, “What’s constant in contrast constancy? The effects of scaling on the perceived contrast of bandpass patterns,” Vision Res. 35, 739–756 (1995).
[Crossref] [PubMed]

Buzney, S.

Buzney, S. M.

E. Peli, R. B. Goldstein, G. M. Young, C. L. Trempe, S. M. Buzney, “Image enhancement for the visually impaired: simulations and experimental results,” Invest. Ophthalmol. Vis. Sci. 32, 2337–2350 (1991).
[PubMed]

Campbell, F. W.

F. W. Campbell, J. J. Kulikowski, J. Levinson, “The effect of orientation on the visual resolution of gratings,”J. Physiol. (London) 187, 427–436 (1966).

Chao, T.

D. J. Tolhurst, Y. Tadmor, T. Chao, “The amplitude spectra of natural images,” Ophthalmic Physiol. Opt. 12, 229–232 (1992).
[Crossref] [PubMed]

Daly, S.

S. Daly, “The visual differences predictor: an algorithm for the assessment of image fidelity,” in Human Vision, Visual Processing, and Digital Display III, B. E. Rogowitz, ed., Proc. SPIE1666, 2–15 (1992).
[Crossref]

Derefeldt, G.

B. L. Lundh, G. Derefeldt, S. Nyberg, G. Lennerstrand, “Picture simulation of contrast sensitivity in organic and functional amblyopia,” Acta Ophthalmol. 59, 774–783 (1981).

Duval-Destin, M.

M. Duval-Destin, “A spatio-temporal complete description of contrast,” in 1991 SID International Symposium, Vol. 22 of 1991 SID Digest of Technical Papers (Society for Information Display, Playa del Rey, Calif., 1991), pp. 615–618.

Field, D. J.

N. Brady, D. J. Field, “What’s constant in contrast constancy? The effects of scaling on the perceived contrast of bandpass patterns,” Vision Res. 35, 739–756 (1995).
[Crossref] [PubMed]

D. J. Field, “Relations between the statistics of natural images and the response properties of cortical cells,” J. Opt. Soc. Am. A 4, 2379–2394 (1987).
[Crossref] [PubMed]

Ginsburg, A. P.

A. P. Ginsburg, “Visual information processing based on spatial filters constrained by biological data,” Ph.D. dissertation (Cambridge University, Cambridge, 1978).

Goldstein, R.

E. Peli, L. Arend, G. Young, R. Goldstein, “Contrast sensitivity to patch stimuli: effects of spatial bandwidth and temporal presentation,” Spatial Vis. 7, 1–14 (1993).
[Crossref]

E. Peli, J. Yang, R. Goldstein, “Image invariance with changes in size: the role of peripheral contrast thresholds,” J. Opt. Soc. Am. A 8, 1762–1774 (1991).
[Crossref] [PubMed]

Goldstein, R. B.

E. Peli, R. B. Goldstein, G. M. Young, C. L. Trempe, S. M. Buzney, “Image enhancement for the visually impaired: simulations and experimental results,” Invest. Ophthalmol. Vis. Sci. 32, 2337–2350 (1991).
[PubMed]

E. Peli, R. B. Goldstein, G. M. Young, L. E. Arend, “Contrast sensitivity functions for analysis and simulation of visual perception,” in Noninvasive Assessment of the Visual System, Vol. 3 of 1990 OSA Technical Digest Series (Optical Society of America, Washington, D.C., 1990), pp. 126–129.

Kulikowski, J. J.

F. W. Campbell, J. J. Kulikowski, J. Levinson, “The effect of orientation on the visual resolution of gratings,”J. Physiol. (London) 187, 427–436 (1966).

Larimer, J.

J. Larimer, “Desigining tomorrow’s displays,”NASA Tech. Briefs 17(4), 14–16 (1993).

Lee, E.

Lennerstrand, G.

B. L. Lundh, G. Derefeldt, S. Nyberg, G. Lennerstrand, “Picture simulation of contrast sensitivity in organic and functional amblyopia,” Acta Ophthalmol. 59, 774–783 (1981).

Levinson, J.

F. W. Campbell, J. J. Kulikowski, J. Levinson, “The effect of orientation on the visual resolution of gratings,”J. Physiol. (London) 187, 427–436 (1966).

Lubin, J.

J. Lubin, “A visual discrimination model for imaging system design and evaluation,” in Vision Models for Target Detection and Recognition, E. Peli, ed. (World Scientific, Singapore, 1995), pp. 245–283.
[Crossref]

Lundh, B. L.

B. L. Lundh, G. Derefeldt, S. Nyberg, G. Lennerstrand, “Picture simulation of contrast sensitivity in organic and functional amblyopia,” Acta Ophthalmol. 59, 774–783 (1981).

Nyberg, S.

B. L. Lundh, G. Derefeldt, S. Nyberg, G. Lennerstrand, “Picture simulation of contrast sensitivity in organic and functional amblyopia,” Acta Ophthalmol. 59, 774–783 (1981).

Peli, E.

E. Peli, E. Lee, C. L. Trempe, S. Buzney, “Image enhancement for the visually impaired: the effects of enhancement on face recognition,” J. Opt. Soc. Am. A 11, 1929–1939 (1994).
[Crossref]

E. Peli, L. Arend, G. Young, R. Goldstein, “Contrast sensitivity to patch stimuli: effects of spatial bandwidth and temporal presentation,” Spatial Vis. 7, 1–14 (1993).
[Crossref]

E. Peli, “Display nonlinearity in digital image processing for visual communications,” Opt. Eng. 31, 2374–2382 (1992).
[Crossref]

E. Peli, J. Yang, R. Goldstein, “Image invariance with changes in size: the role of peripheral contrast thresholds,” J. Opt. Soc. Am. A 8, 1762–1774 (1991).
[Crossref] [PubMed]

E. Peli, R. B. Goldstein, G. M. Young, C. L. Trempe, S. M. Buzney, “Image enhancement for the visually impaired: simulations and experimental results,” Invest. Ophthalmol. Vis. Sci. 32, 2337–2350 (1991).
[PubMed]

E. Peli, “Contrast in complex images,” J. Opt. Soc. Am. A 7, 2030–2040 (1990).
[Crossref]

E. Peli, “Hilbert transform pairs mechanisms,” Invest. Ophthalmol. Vis. Sci. Suppl. 30, 110 (1989).

E. Peli, “Simulating normal and low vision,” in Vision Models for Target Detection and Recognition, E. Peli, ed. (World Scientific, Singapore, 1995), pp. 63–87.
[Crossref]

E. Peli, R. B. Goldstein, G. M. Young, L. E. Arend, “Contrast sensitivity functions for analysis and simulation of visual perception,” in Noninvasive Assessment of the Visual System, Vol. 3 of 1990 OSA Technical Digest Series (Optical Society of America, Washington, D.C., 1990), pp. 126–129.

Pelli, D.

D. Pelli, “What is low vision?” Videotape presentation, Syracuse University, Syracuse, N.Y., 1990.

Stephens, B. R.

B. R. Stephens, M. S. Banks, “The development of contrast constancy,”J. Exp. Child Psychol. 40, 528–547 (1985).
[Crossref] [PubMed]

Tadmor, Y.

D. J. Tolhurst, Y. Tadmor, T. Chao, “The amplitude spectra of natural images,” Ophthalmic Physiol. Opt. 12, 229–232 (1992).
[Crossref] [PubMed]

Thibos, L. N.

L. N. Thibos, A. Bradley, “The limits of performance in central and peripheral vision,” in 1991 SID International Symposium, Vol. 22 of 1991 SID Digest of Technical Papers (Society for Information Display, Playa del Rey, Calif., 1991), pp. 301–303.

Tolhurst, D. J.

D. J. Tolhurst, Y. Tadmor, T. Chao, “The amplitude spectra of natural images,” Ophthalmic Physiol. Opt. 12, 229–232 (1992).
[Crossref] [PubMed]

Trempe, C. L.

E. Peli, E. Lee, C. L. Trempe, S. Buzney, “Image enhancement for the visually impaired: the effects of enhancement on face recognition,” J. Opt. Soc. Am. A 11, 1929–1939 (1994).
[Crossref]

E. Peli, R. B. Goldstein, G. M. Young, C. L. Trempe, S. M. Buzney, “Image enhancement for the visually impaired: simulations and experimental results,” Invest. Ophthalmol. Vis. Sci. 32, 2337–2350 (1991).
[PubMed]

Tyler, C. W.

C. W. Tyler, “Is the illusory triangle physical or imaginary?” Perception 6, 603–604 (1977).
[PubMed]

Watson, A. B.

A. B. Watson, “Efficiency of a model human image code,” J. Opt. Soc. Am. A 4, 2401–2417 (1987).
[Crossref] [PubMed]

A. B. Watson, “The cortex transform: rapid computation of simulated neural images,” Comput. Vision, Graphics, Image Process. 39, 311–327 (1987).
[Crossref]

Yang, J.

Young, G.

E. Peli, L. Arend, G. Young, R. Goldstein, “Contrast sensitivity to patch stimuli: effects of spatial bandwidth and temporal presentation,” Spatial Vis. 7, 1–14 (1993).
[Crossref]

Young, G. M.

E. Peli, R. B. Goldstein, G. M. Young, C. L. Trempe, S. M. Buzney, “Image enhancement for the visually impaired: simulations and experimental results,” Invest. Ophthalmol. Vis. Sci. 32, 2337–2350 (1991).
[PubMed]

E. Peli, R. B. Goldstein, G. M. Young, L. E. Arend, “Contrast sensitivity functions for analysis and simulation of visual perception,” in Noninvasive Assessment of the Visual System, Vol. 3 of 1990 OSA Technical Digest Series (Optical Society of America, Washington, D.C., 1990), pp. 126–129.

Acta Ophthalmol. (1)

B. L. Lundh, G. Derefeldt, S. Nyberg, G. Lennerstrand, “Picture simulation of contrast sensitivity in organic and functional amblyopia,” Acta Ophthalmol. 59, 774–783 (1981).

Comput. Vision, Graphics, Image Process. (1)

A. B. Watson, “The cortex transform: rapid computation of simulated neural images,” Comput. Vision, Graphics, Image Process. 39, 311–327 (1987).
[Crossref]

Invest. Ophthalmol. Vis. Sci. (1)

E. Peli, R. B. Goldstein, G. M. Young, C. L. Trempe, S. M. Buzney, “Image enhancement for the visually impaired: simulations and experimental results,” Invest. Ophthalmol. Vis. Sci. 32, 2337–2350 (1991).
[PubMed]

Invest. Ophthalmol. Vis. Sci. Suppl. (1)

E. Peli, “Hilbert transform pairs mechanisms,” Invest. Ophthalmol. Vis. Sci. Suppl. 30, 110 (1989).

J. Exp. Child Psychol. (1)

B. R. Stephens, M. S. Banks, “The development of contrast constancy,”J. Exp. Child Psychol. 40, 528–547 (1985).
[Crossref] [PubMed]

J. Opt. Soc. Am. A (5)

J. Physiol. (London) (1)

F. W. Campbell, J. J. Kulikowski, J. Levinson, “The effect of orientation on the visual resolution of gratings,”J. Physiol. (London) 187, 427–436 (1966).

NASA Tech. Briefs (1)

J. Larimer, “Desigining tomorrow’s displays,”NASA Tech. Briefs 17(4), 14–16 (1993).

Ophthalmic Physiol. Opt. (1)

D. J. Tolhurst, Y. Tadmor, T. Chao, “The amplitude spectra of natural images,” Ophthalmic Physiol. Opt. 12, 229–232 (1992).
[Crossref] [PubMed]

Opt. Eng. (1)

E. Peli, “Display nonlinearity in digital image processing for visual communications,” Opt. Eng. 31, 2374–2382 (1992).
[Crossref]

Perception (1)

C. W. Tyler, “Is the illusory triangle physical or imaginary?” Perception 6, 603–604 (1977).
[PubMed]

Spatial Vis. (1)

E. Peli, L. Arend, G. Young, R. Goldstein, “Contrast sensitivity to patch stimuli: effects of spatial bandwidth and temporal presentation,” Spatial Vis. 7, 1–14 (1993).
[Crossref]

Vision Res. (1)

N. Brady, D. J. Field, “What’s constant in contrast constancy? The effects of scaling on the perceived contrast of bandpass patterns,” Vision Res. 35, 739–756 (1995).
[Crossref] [PubMed]

Other (9)

E. Peli, “Simulating normal and low vision,” in Vision Models for Target Detection and Recognition, E. Peli, ed. (World Scientific, Singapore, 1995), pp. 63–87.
[Crossref]

J. Lubin, “A visual discrimination model for imaging system design and evaluation,” in Vision Models for Target Detection and Recognition, E. Peli, ed. (World Scientific, Singapore, 1995), pp. 245–283.
[Crossref]

E. Peli, ed., Vision Models for Target Detection and Recognition (World Scientific, Singapore, 1995).
[Crossref]

E. Peli, R. B. Goldstein, G. M. Young, L. E. Arend, “Contrast sensitivity functions for analysis and simulation of visual perception,” in Noninvasive Assessment of the Visual System, Vol. 3 of 1990 OSA Technical Digest Series (Optical Society of America, Washington, D.C., 1990), pp. 126–129.

M. Duval-Destin, “A spatio-temporal complete description of contrast,” in 1991 SID International Symposium, Vol. 22 of 1991 SID Digest of Technical Papers (Society for Information Display, Playa del Rey, Calif., 1991), pp. 615–618.

S. Daly, “The visual differences predictor: an algorithm for the assessment of image fidelity,” in Human Vision, Visual Processing, and Digital Display III, B. E. Rogowitz, ed., Proc. SPIE1666, 2–15 (1992).
[Crossref]

D. Pelli, “What is low vision?” Videotape presentation, Syracuse University, Syracuse, N.Y., 1990.

A. P. Ginsburg, “Visual information processing based on spatial filters constrained by biological data,” Ph.D. dissertation (Cambridge University, Cambridge, 1978).

L. N. Thibos, A. Bradley, “The limits of performance in central and peripheral vision,” in 1991 SID International Symposium, Vol. 22 of 1991 SID Digest of Technical Papers (Society for Information Display, Playa del Rey, Calif., 1991), pp. 301–303.

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Figures (8)

Fig. 1
Fig. 1

Relationships among spatial frequency spectra of images and contrast thresholds. Spatial frequency is expressed in cycles per degree and cycles per image for different image sizes. Thin solid-curve spectrum, 2-deg image; thin dashed-curve spectrum, 4-deg image. (a) Simulation with patch CSF, (b) simulation with fixed-aperture CSF. Medium-thick solid curve, CSF used for simulation. Contrast below that curve is below the simulated subject’s contrast threshold. Therefore I removed image components to the right of the point where the threshold curve intersects the 2-deg image spectrum (thick dashed curve). At the 2-deg distance the removed components are below threshold, and thus the original image and the simulation should appear identical. When both are moved to the 4-deg distance a portion of the removed components (shaded area) will be above threshold and be visible if the CSF used for the simulation is an accurate description of the viewer’s visual system. When tested, viewers can see the difference at 4 deg between the patch simulation and the original, indicating that the viewer’s threshold curve lies below the shaded area of Fig. 1(a) and above the shaded area of Fig. 1(b). Note the shift of the spectrum under change of observation distance (see text for explanation).

Fig. 2
Fig. 2

Illustrations of the appearance of the original (far-left column) and of simulated images for three simulated observation distances as noted: when the image spans 4 deg (second column), for a span of 2 deg (middle column), and for a span of 1 deg (fourth and fifth columns). The photographic and printing process prohibit direct evaluation of the effect; however, it is possible to appreciate that only small changes are effected by all simulations. The simulation for a span of 1 deg, using a model without local normalization by mean luminance (far-right column) is presented for comparison. In this case all bandpassed-filtered versions were normalized by the global image mean. The changes between the local and global simulations are of similar magnitude, as are the differences between the 1- and 2-deg simulations. The original images presented here are without the high-frequency residual (i.e., the originals used in experiment 3).

Fig. 3
Fig. 3

CSF (contrast threshold) measured with a 1-octave Gabor patch for orientation discrimination and detection. Data shown are means and standard errors of the mean of subjects in experiments 1 and 2.

Fig. 4
Fig. 4

Results of testing central-vision simulation by using the CSF based on discrimination of the orientation of 1-octave Gabor patches. The data and the psychometric function fits indicate that the subject could distinguish the simulation from the original at distances larger than the distances assumed in the simulations (see diamond inserts at bottom of graph).

Fig. 5
Fig. 5

Results of simulation testing with the CSF based on detection of 1-octave Gabor patches. Here the subject could distinguish the simulation from the original approximately at the distance assumed in the simulations (see diamond inserts at bottom of graph).

Fig. 6
Fig. 6

Distance thresholds for discriminating the simulations from the original calculated separately for the four different images (averaged over the four observers). The results for the 4-deg (40-in.) and 2-deg (80-in.) simulations are superimposed over the results for the 1-deg (160-in.) simulation.

Fig. 7
Fig. 7

Distance thresholds for discriminating the simulations from the original calculated separately for the four different images (averaged over the four observers). The results for the 2-deg (80-in.) simulation are superimposed over the results for the 1-deg (160-in.) simulation. Note the excellent agreement with the predictions of the results obtained without the high-frequency residual.

Fig. 8
Fig. 8

Example of the discrimination data analyzed separately for each image for the experiment without the high-frequency residual for the same subject as in Fig. 5.

Tables (2)

Tables Icon

Table 1 Discrimination Threshold Distances (in Inches) Averaged from Four Subjects by Using the Detection CSF’s with High-Frequency Residual (Experiment 2)a

Tables Icon

Table 2 Discrimination Threshold Distances (in inches) Averaged from Four Subjects by Using the Detection CSF’s without High-Frequency Residual (Experiment 3)a

Metrics