Abstract

Studies of visual detection of a signal superimposed on one of two identical backgrounds show performance degradation when the background has high contrast and is similar in spatial frequency and/or orientation to the signal. To account for this finding, models include a contrast gain control mechanism that pools activity across spatial frequency, orientation and space to inhibit (divisively) the response of the receptor sensitive to the signal. In tasks in which the observer has to detect a known signal added to one of M different backgrounds due to added visual noise, the main sources of degradation are the stochastic noise in the image and the suboptimal visual processing. We investigate how these two sources of degradation (contrast gain control and variations in the background) interact in a task in which the signal is embedded in one of M locations in a complex spatially varying background (structured background). We use backgrounds extracted from patient digital medical images. To isolate effects of the fixed deterministic background (the contrast gain control) from the effects of the background variations, we conduct detection experiments with three different background conditions: (1) uniform background, (2) a repeated sample of structured background, and (3) different samples of structured background. Results show that human visual detection degrades from the uniform background condition to the repeated background condition and degrades even further in the different backgrounds condition. These results suggest that both the contrast gain control mechanism and the background random variations degrade human performance in detection of a signal in a complex, spatially varying background. A filter model and added white noise are used to generate estimates of sampling efficiencies, an equivalent internal noise, an equivalent contrast-gain-control-induced noise, and an equivalent noise due to the variations in the structured background.

© 1997 Optical Society of America

Full Article  |  PDF Article

References

  • View by:
  • |
  • |
  • |

  1. G. E. Legge, J. M. Foley, “Contrast masking in human vision,” J. Opt. Soc. Am. 70, 1458–1471 (1980).
    [Crossref] [PubMed]
  2. J. M. Foley, “Human luminance pattern-vision mechanisms: masking experiments require a new model,” J. Opt. Soc. Am. A 11, 1710–1719 (1994).
    [Crossref]
  3. A. B. Watson, J. Solomon, “Model of contrast gain control in human vision,” J. Opt. Soc. Am. A 14, 2379–2391 (1997).
    [Crossref]
  4. D. J. Heeger, “Nonlinear model of neural responses in cat visual cortex,” Visual Neurosci.181–197 (1992).
    [Crossref]
  5. W. S. Geisler, D. G. Albrecht, “Cortical neurons: isolation of contrast gain control,” Vision Res. 32, 1409–1410 (1992).
    [Crossref] [PubMed]
  6. A. J. Ahumada, A. B. Watson, A. M. Rohaly, “Models of human image discrimination predict object detection in natural backgrounds,” in Human Vision, Visual Processing, and Digital Display VI, B. Rogowitz, J. Allebach, eds., Proc. SPIE2411, 355–362 (1995).
    [Crossref]
  7. A. B. Watson, “DCTune: a technique for visual optimization of DCT quantization matrices for individual images,” in Digest of Technical Papers 24 (Society for Information Display, Santa Ana, Calif., 1993), pp. 946–949.
  8. A. E. Burgess, R. F. Wagner, R. J. Jennings, H. B. Barlow, “Efficiency of human visual signal discrimination,” Science 214, 93–94 (1981).
    [Crossref] [PubMed]
  9. A. E. Burgess, “Visual signal detection. III. On Bayesian use of prior knowledge and cross correlation,” J. Opt. Soc. Am. A 2, 1498–1507 (1985).
    [Crossref] [PubMed]
  10. J. P. Rolland, H. H. Barrett, “Effect of random inhomogeneity on observer detection performance,” J. Opt. Soc. Am. A 9, 649–658 (1992).
    [Crossref] [PubMed]
  11. K. J. Myers, H. H. Barrett, M. C. Borgstrom, D. D. Patton, G. W. Seeley, “Effect of noise correlation on detectability of disk signals in medical imaging,” J. Opt. Soc. Am. A 2, 1752–1759 (1985).
    [Crossref] [PubMed]
  12. K. J. Myers, H. H. Barrett, “Addition of a channel mechanism to the ideal observer,” J. Opt. Soc. Am. A 4, 2447–2457 (1987).
    [Crossref] [PubMed]
  13. A. E. Burgess, “Statistically defined backgrounds: performance of a modified nonprewhitening matched filter model,” J. Opt. Soc. Am. A 11, 1237–1242 (1994).
    [Crossref]
  14. A. E. Burgess, B. Colborne, “Visual signal detection. IV. Observer inconsistency,” J. Opt. Soc. Am. A 5, 617–627 (1988).
    [Crossref] [PubMed]
  15. H. L. Kundel, “Medical image perception,” in Proceedings of the Conference on Developing a Long-Term Plan for Imaging Research, B. L. Holman, S. H. Edwards, eds. (National Institutes of Health, Bethesda, Md., 1994), pp. 39–42.
  16. M. P. Eckstein, C. A. Morioka, J. S. Whiting, N. L. Eigler, “Psychophysical evaluation of the effect of JPEG, full-frame DCT and wavelet image compression on signal detection in medical image noise,” in Medical Imaging 1995: Image Perception, H. Kundel, ed., Proc. SPIE2436, 79–89 (1995).
    [Crossref]
  17. M. P. Eckstein, J. S. Whiting, “Lesion detection in structured noise,” Acad. Radiol. 3, 249–253 (1995).
    [PubMed]
  18. N. L. Eigler, M. P. Eckstein, D. Honig, J. S. Whiting, “Improving detection of coronary morphologic features from digital angiograms: effect of stenosis stabilized display,” Circulation 89, 2700–2709 (1994).
    [Crossref] [PubMed]
  19. M. P. Eckstein, J. S. Whiting, “Visual signal detection in structured backgrounds. I. Effect of number of possible locations and signal contrast,” J. Opt. Soc. Am. A 13, 1777–1787 (1996).
    [Crossref]
  20. D. G. Pelli, “Effects of visual noise,” Ph.D. dissertation (Cambridge U. Press, Cambridge, 1981).
  21. W. W. Peterson, T. G. Birdsall, W. C. Fox, “The theory of signal detectability,” IRE Trans. Inf. Theor. PGIT-4, 171–212 (1954).
    [Crossref]
  22. H. B. Barlow, “The absolute efficiency of perceptual decisions,” Proc. R. Soc. London 290, 71–91 (1980).
    [PubMed]
  23. M. P. Eckstein, J. S. Whiting, J. P. Thomas, “Role of knowledge in human visual temporal integration in spatiotemporal noise,” J. Opt. Soc. Am. A 13, 1960–1968 (1996).
    [Crossref]
  24. M. P. Eckstein, J. S. Whiting, J. P. Thomas, “Detection and discrimination of moving signal in Gaussian uncorrelated noise,” in Medical Imaging 1996: Image Perception, H. Kundel, ed., Proc. SPIE2712, 9–25 (1996).
    [Crossref]
  25. A. B. Burgess, H. Ghandeharian, “Visual signal detection. I. Ability to use phase information,” J. Opt. Soc. Am. A 1, 900–905 (1984).
    [Crossref] [PubMed]
  26. D. M. Green, J. A. Swets, Signal Detection Theory and Psychophysics (Wiley, New York, 1966).
  27. G. E. Legge, D. Kersten, A. E. Burgess, “Contrast discrimination in noise,” J. Opt. Soc. Am. A 4, 391–404 (1987).
    [Crossref] [PubMed]
  28. D. G. Pelli, “Uncertainty explains many aspects of visual contrast detection and discrimination,” J. Opt. Soc. Am. A 2, 1508–1530 (1985).
    [Crossref] [PubMed]
  29. D. J. Tolhurst, J. A. Movshson, A. F. Dean, “The statistical reliability of signals in single neurons in cat and monkey visual cortex,” Vision Res. 23, 775–785 (1982).
    [Crossref]
  30. W. A. Wickelgren, “Unidimensional strength theory and component analysis of noise in absolute and comparative judgments,” J. Math. Psychol. 5, 102–122 (1968).
    [Crossref]
  31. J. M. Foley, G. E. Legge, “Contrast detection and near threshold discrimination in human vision,” Vision Res. 21, 1041–1053 (1981).
    [Crossref]
  32. J. Nachmias, R. Sansbury, “Grating contrast: discrimination may be better than detection,” Vision Res. 14, 1039–1042 (1974).
    [Crossref] [PubMed]
  33. A. E. Burgess, H. Ghandeharian, “Visual signal detection. II. Signal location identification,” J. Opt. Soc. Am. A 1, 900–905 (1984).
    [Crossref] [PubMed]
  34. A. E. Burgess, “Detection and identification efficiency: an update,” in Application of Optical Instrumentation in Medicine XIII: Medical Image Production, Processing, and Displays, S. J. Dwyer, R. H. Schneider, eds., Proc. SPIE535, 50–56 (1985).
    [Crossref]
  35. A. J. Ahumada, “Putting the visual system noise back in the picture,” J. Opt. Soc. Am. A 4, 2372–2378 (1987).
    [Crossref] [PubMed]
  36. J. Yao, H. H. Barrett, “Predicting human performance by a channelized Hotelling observer model,” in Mathematical Methods in Medical Imaging, D. C. Wilson, J. N. Wilson, eds., Proc. SPIE1768, 161–168 (1992).
    [Crossref]
  37. C. K. Abbey, H. H. Barrett, D. W. Wilson, “Observer signal to noise ratio for the ML/EM algorithm,” in Medical Imaging 1996: Image Perception, H. Kundel, ed., Proc. SPIE2712, 47–58 (1996).
    [Crossref]
  38. M. P. Eckstein, J. S. Whiting, “Using computer observer models to predict the effect of JPEG image compression on human lesion detection,” Opt. Photonics News 5(8), 128 (1994) (Optical Society of America Annual Meeting Suppl.).
  39. A. E. Burgess, X. Li, C. Abbey, “Visual signal detectability with two noise components: anomalous masking effects,” J. Opt. Soc. Am. A 14, 2420–2442 (1997).
    [Crossref]
  40. M. P. Eckstein, J. S. Whiting, A. E. Burgess, J. P. Thomas, S. S. Shimozaki, “Signal positional uncertainty and signals in dynamic noise,” Opt. Photonics News 5(8), 128 (1994) (Optical Society of America Annual Meeting Suppl.).
  41. J. Ross, H. D. Speed, M. J. Morgan, “The effects of adaptation and masking on incremental threshold for contrast,” Vision Res. 33, 2051–2056 (1993).
    [Crossref] [PubMed]
  42. J. M. Foley, “Simultaneous pattern masking: How come threshold elevation bandwidth decreases as stimulus duration increases,” Invest. Ophthalmol. Visual Sci. Suppl. 37, 4205 (1996).
  43. A. J. Ahumada, B. Beard, “Image discrimination models predict detection in fixed but not random noise,” J. Opt. Soc. Am. A 14, 2471–2476 (1997).
    [Crossref]
  44. R. A. Smith, D. J. Swift, “Spatial frequency masking and Birdsall’s theorem,” J. Opt. Soc. Am. A 2, 1593–1599 (1985).
    [Crossref] [PubMed]
  45. N. S. Nagaraja, “Effect of luminance noise on contrast thresholds,” J. Opt. Soc. Am. 57, 401–406 (1967).
  46. H. H. Barrett, J. Yao, J. P. Rolland, K. J. Myers, “Model observers for assessment of image quality,” Proc. Natl. Acad. Sci. USA 90, 9758–9765 (1993).
    [Crossref] [PubMed]
  47. C. K. Abbey, H. H. Barrett, M. P. Eckstein, “Practical issues and methodology in assessment of image quality using model observers,” in Medical Imaging: The Physics of Medical Imaging, R. L. Van Metter, J. Beuttel, eds., Proc. SPIE3032, 182–194 (1997).
    [Crossref]

1997 (3)

1996 (3)

1995 (1)

M. P. Eckstein, J. S. Whiting, “Lesion detection in structured noise,” Acad. Radiol. 3, 249–253 (1995).
[PubMed]

1994 (5)

N. L. Eigler, M. P. Eckstein, D. Honig, J. S. Whiting, “Improving detection of coronary morphologic features from digital angiograms: effect of stenosis stabilized display,” Circulation 89, 2700–2709 (1994).
[Crossref] [PubMed]

A. E. Burgess, “Statistically defined backgrounds: performance of a modified nonprewhitening matched filter model,” J. Opt. Soc. Am. A 11, 1237–1242 (1994).
[Crossref]

J. M. Foley, “Human luminance pattern-vision mechanisms: masking experiments require a new model,” J. Opt. Soc. Am. A 11, 1710–1719 (1994).
[Crossref]

M. P. Eckstein, J. S. Whiting, A. E. Burgess, J. P. Thomas, S. S. Shimozaki, “Signal positional uncertainty and signals in dynamic noise,” Opt. Photonics News 5(8), 128 (1994) (Optical Society of America Annual Meeting Suppl.).

M. P. Eckstein, J. S. Whiting, “Using computer observer models to predict the effect of JPEG image compression on human lesion detection,” Opt. Photonics News 5(8), 128 (1994) (Optical Society of America Annual Meeting Suppl.).

1993 (2)

J. Ross, H. D. Speed, M. J. Morgan, “The effects of adaptation and masking on incremental threshold for contrast,” Vision Res. 33, 2051–2056 (1993).
[Crossref] [PubMed]

H. H. Barrett, J. Yao, J. P. Rolland, K. J. Myers, “Model observers for assessment of image quality,” Proc. Natl. Acad. Sci. USA 90, 9758–9765 (1993).
[Crossref] [PubMed]

1992 (3)

J. P. Rolland, H. H. Barrett, “Effect of random inhomogeneity on observer detection performance,” J. Opt. Soc. Am. A 9, 649–658 (1992).
[Crossref] [PubMed]

D. J. Heeger, “Nonlinear model of neural responses in cat visual cortex,” Visual Neurosci.181–197 (1992).
[Crossref]

W. S. Geisler, D. G. Albrecht, “Cortical neurons: isolation of contrast gain control,” Vision Res. 32, 1409–1410 (1992).
[Crossref] [PubMed]

1988 (1)

1987 (3)

1985 (4)

1984 (2)

1982 (1)

D. J. Tolhurst, J. A. Movshson, A. F. Dean, “The statistical reliability of signals in single neurons in cat and monkey visual cortex,” Vision Res. 23, 775–785 (1982).
[Crossref]

1981 (2)

J. M. Foley, G. E. Legge, “Contrast detection and near threshold discrimination in human vision,” Vision Res. 21, 1041–1053 (1981).
[Crossref]

A. E. Burgess, R. F. Wagner, R. J. Jennings, H. B. Barlow, “Efficiency of human visual signal discrimination,” Science 214, 93–94 (1981).
[Crossref] [PubMed]

1980 (2)

G. E. Legge, J. M. Foley, “Contrast masking in human vision,” J. Opt. Soc. Am. 70, 1458–1471 (1980).
[Crossref] [PubMed]

H. B. Barlow, “The absolute efficiency of perceptual decisions,” Proc. R. Soc. London 290, 71–91 (1980).
[PubMed]

1974 (1)

J. Nachmias, R. Sansbury, “Grating contrast: discrimination may be better than detection,” Vision Res. 14, 1039–1042 (1974).
[Crossref] [PubMed]

1968 (1)

W. A. Wickelgren, “Unidimensional strength theory and component analysis of noise in absolute and comparative judgments,” J. Math. Psychol. 5, 102–122 (1968).
[Crossref]

1967 (1)

1954 (1)

W. W. Peterson, T. G. Birdsall, W. C. Fox, “The theory of signal detectability,” IRE Trans. Inf. Theor. PGIT-4, 171–212 (1954).
[Crossref]

Abbey, C.

Abbey, C. K.

C. K. Abbey, H. H. Barrett, D. W. Wilson, “Observer signal to noise ratio for the ML/EM algorithm,” in Medical Imaging 1996: Image Perception, H. Kundel, ed., Proc. SPIE2712, 47–58 (1996).
[Crossref]

C. K. Abbey, H. H. Barrett, M. P. Eckstein, “Practical issues and methodology in assessment of image quality using model observers,” in Medical Imaging: The Physics of Medical Imaging, R. L. Van Metter, J. Beuttel, eds., Proc. SPIE3032, 182–194 (1997).
[Crossref]

Ahumada, A. J.

A. J. Ahumada, B. Beard, “Image discrimination models predict detection in fixed but not random noise,” J. Opt. Soc. Am. A 14, 2471–2476 (1997).
[Crossref]

A. J. Ahumada, “Putting the visual system noise back in the picture,” J. Opt. Soc. Am. A 4, 2372–2378 (1987).
[Crossref] [PubMed]

A. J. Ahumada, A. B. Watson, A. M. Rohaly, “Models of human image discrimination predict object detection in natural backgrounds,” in Human Vision, Visual Processing, and Digital Display VI, B. Rogowitz, J. Allebach, eds., Proc. SPIE2411, 355–362 (1995).
[Crossref]

Albrecht, D. G.

W. S. Geisler, D. G. Albrecht, “Cortical neurons: isolation of contrast gain control,” Vision Res. 32, 1409–1410 (1992).
[Crossref] [PubMed]

Barlow, H. B.

A. E. Burgess, R. F. Wagner, R. J. Jennings, H. B. Barlow, “Efficiency of human visual signal discrimination,” Science 214, 93–94 (1981).
[Crossref] [PubMed]

H. B. Barlow, “The absolute efficiency of perceptual decisions,” Proc. R. Soc. London 290, 71–91 (1980).
[PubMed]

Barrett, H. H.

H. H. Barrett, J. Yao, J. P. Rolland, K. J. Myers, “Model observers for assessment of image quality,” Proc. Natl. Acad. Sci. USA 90, 9758–9765 (1993).
[Crossref] [PubMed]

J. P. Rolland, H. H. Barrett, “Effect of random inhomogeneity on observer detection performance,” J. Opt. Soc. Am. A 9, 649–658 (1992).
[Crossref] [PubMed]

K. J. Myers, H. H. Barrett, “Addition of a channel mechanism to the ideal observer,” J. Opt. Soc. Am. A 4, 2447–2457 (1987).
[Crossref] [PubMed]

K. J. Myers, H. H. Barrett, M. C. Borgstrom, D. D. Patton, G. W. Seeley, “Effect of noise correlation on detectability of disk signals in medical imaging,” J. Opt. Soc. Am. A 2, 1752–1759 (1985).
[Crossref] [PubMed]

C. K. Abbey, H. H. Barrett, M. P. Eckstein, “Practical issues and methodology in assessment of image quality using model observers,” in Medical Imaging: The Physics of Medical Imaging, R. L. Van Metter, J. Beuttel, eds., Proc. SPIE3032, 182–194 (1997).
[Crossref]

C. K. Abbey, H. H. Barrett, D. W. Wilson, “Observer signal to noise ratio for the ML/EM algorithm,” in Medical Imaging 1996: Image Perception, H. Kundel, ed., Proc. SPIE2712, 47–58 (1996).
[Crossref]

J. Yao, H. H. Barrett, “Predicting human performance by a channelized Hotelling observer model,” in Mathematical Methods in Medical Imaging, D. C. Wilson, J. N. Wilson, eds., Proc. SPIE1768, 161–168 (1992).
[Crossref]

Beard, B.

Birdsall, T. G.

W. W. Peterson, T. G. Birdsall, W. C. Fox, “The theory of signal detectability,” IRE Trans. Inf. Theor. PGIT-4, 171–212 (1954).
[Crossref]

Borgstrom, M. C.

Burgess, A. B.

Burgess, A. E.

A. E. Burgess, X. Li, C. Abbey, “Visual signal detectability with two noise components: anomalous masking effects,” J. Opt. Soc. Am. A 14, 2420–2442 (1997).
[Crossref]

A. E. Burgess, “Statistically defined backgrounds: performance of a modified nonprewhitening matched filter model,” J. Opt. Soc. Am. A 11, 1237–1242 (1994).
[Crossref]

M. P. Eckstein, J. S. Whiting, A. E. Burgess, J. P. Thomas, S. S. Shimozaki, “Signal positional uncertainty and signals in dynamic noise,” Opt. Photonics News 5(8), 128 (1994) (Optical Society of America Annual Meeting Suppl.).

A. E. Burgess, B. Colborne, “Visual signal detection. IV. Observer inconsistency,” J. Opt. Soc. Am. A 5, 617–627 (1988).
[Crossref] [PubMed]

G. E. Legge, D. Kersten, A. E. Burgess, “Contrast discrimination in noise,” J. Opt. Soc. Am. A 4, 391–404 (1987).
[Crossref] [PubMed]

A. E. Burgess, “Visual signal detection. III. On Bayesian use of prior knowledge and cross correlation,” J. Opt. Soc. Am. A 2, 1498–1507 (1985).
[Crossref] [PubMed]

A. E. Burgess, H. Ghandeharian, “Visual signal detection. II. Signal location identification,” J. Opt. Soc. Am. A 1, 900–905 (1984).
[Crossref] [PubMed]

A. E. Burgess, R. F. Wagner, R. J. Jennings, H. B. Barlow, “Efficiency of human visual signal discrimination,” Science 214, 93–94 (1981).
[Crossref] [PubMed]

A. E. Burgess, “Detection and identification efficiency: an update,” in Application of Optical Instrumentation in Medicine XIII: Medical Image Production, Processing, and Displays, S. J. Dwyer, R. H. Schneider, eds., Proc. SPIE535, 50–56 (1985).
[Crossref]

Colborne, B.

Dean, A. F.

D. J. Tolhurst, J. A. Movshson, A. F. Dean, “The statistical reliability of signals in single neurons in cat and monkey visual cortex,” Vision Res. 23, 775–785 (1982).
[Crossref]

Eckstein, M. P.

M. P. Eckstein, J. S. Whiting, “Visual signal detection in structured backgrounds. I. Effect of number of possible locations and signal contrast,” J. Opt. Soc. Am. A 13, 1777–1787 (1996).
[Crossref]

M. P. Eckstein, J. S. Whiting, J. P. Thomas, “Role of knowledge in human visual temporal integration in spatiotemporal noise,” J. Opt. Soc. Am. A 13, 1960–1968 (1996).
[Crossref]

M. P. Eckstein, J. S. Whiting, “Lesion detection in structured noise,” Acad. Radiol. 3, 249–253 (1995).
[PubMed]

N. L. Eigler, M. P. Eckstein, D. Honig, J. S. Whiting, “Improving detection of coronary morphologic features from digital angiograms: effect of stenosis stabilized display,” Circulation 89, 2700–2709 (1994).
[Crossref] [PubMed]

M. P. Eckstein, J. S. Whiting, A. E. Burgess, J. P. Thomas, S. S. Shimozaki, “Signal positional uncertainty and signals in dynamic noise,” Opt. Photonics News 5(8), 128 (1994) (Optical Society of America Annual Meeting Suppl.).

M. P. Eckstein, J. S. Whiting, “Using computer observer models to predict the effect of JPEG image compression on human lesion detection,” Opt. Photonics News 5(8), 128 (1994) (Optical Society of America Annual Meeting Suppl.).

C. K. Abbey, H. H. Barrett, M. P. Eckstein, “Practical issues and methodology in assessment of image quality using model observers,” in Medical Imaging: The Physics of Medical Imaging, R. L. Van Metter, J. Beuttel, eds., Proc. SPIE3032, 182–194 (1997).
[Crossref]

M. P. Eckstein, J. S. Whiting, J. P. Thomas, “Detection and discrimination of moving signal in Gaussian uncorrelated noise,” in Medical Imaging 1996: Image Perception, H. Kundel, ed., Proc. SPIE2712, 9–25 (1996).
[Crossref]

M. P. Eckstein, C. A. Morioka, J. S. Whiting, N. L. Eigler, “Psychophysical evaluation of the effect of JPEG, full-frame DCT and wavelet image compression on signal detection in medical image noise,” in Medical Imaging 1995: Image Perception, H. Kundel, ed., Proc. SPIE2436, 79–89 (1995).
[Crossref]

Eigler, N. L.

N. L. Eigler, M. P. Eckstein, D. Honig, J. S. Whiting, “Improving detection of coronary morphologic features from digital angiograms: effect of stenosis stabilized display,” Circulation 89, 2700–2709 (1994).
[Crossref] [PubMed]

M. P. Eckstein, C. A. Morioka, J. S. Whiting, N. L. Eigler, “Psychophysical evaluation of the effect of JPEG, full-frame DCT and wavelet image compression on signal detection in medical image noise,” in Medical Imaging 1995: Image Perception, H. Kundel, ed., Proc. SPIE2436, 79–89 (1995).
[Crossref]

Foley, J. M.

J. M. Foley, “Simultaneous pattern masking: How come threshold elevation bandwidth decreases as stimulus duration increases,” Invest. Ophthalmol. Visual Sci. Suppl. 37, 4205 (1996).

J. M. Foley, “Human luminance pattern-vision mechanisms: masking experiments require a new model,” J. Opt. Soc. Am. A 11, 1710–1719 (1994).
[Crossref]

J. M. Foley, G. E. Legge, “Contrast detection and near threshold discrimination in human vision,” Vision Res. 21, 1041–1053 (1981).
[Crossref]

G. E. Legge, J. M. Foley, “Contrast masking in human vision,” J. Opt. Soc. Am. 70, 1458–1471 (1980).
[Crossref] [PubMed]

Fox, W. C.

W. W. Peterson, T. G. Birdsall, W. C. Fox, “The theory of signal detectability,” IRE Trans. Inf. Theor. PGIT-4, 171–212 (1954).
[Crossref]

Geisler, W. S.

W. S. Geisler, D. G. Albrecht, “Cortical neurons: isolation of contrast gain control,” Vision Res. 32, 1409–1410 (1992).
[Crossref] [PubMed]

Ghandeharian, H.

Green, D. M.

D. M. Green, J. A. Swets, Signal Detection Theory and Psychophysics (Wiley, New York, 1966).

Heeger, D. J.

D. J. Heeger, “Nonlinear model of neural responses in cat visual cortex,” Visual Neurosci.181–197 (1992).
[Crossref]

Honig, D.

N. L. Eigler, M. P. Eckstein, D. Honig, J. S. Whiting, “Improving detection of coronary morphologic features from digital angiograms: effect of stenosis stabilized display,” Circulation 89, 2700–2709 (1994).
[Crossref] [PubMed]

Jennings, R. J.

A. E. Burgess, R. F. Wagner, R. J. Jennings, H. B. Barlow, “Efficiency of human visual signal discrimination,” Science 214, 93–94 (1981).
[Crossref] [PubMed]

Kersten, D.

Kundel, H. L.

H. L. Kundel, “Medical image perception,” in Proceedings of the Conference on Developing a Long-Term Plan for Imaging Research, B. L. Holman, S. H. Edwards, eds. (National Institutes of Health, Bethesda, Md., 1994), pp. 39–42.

Legge, G. E.

Li, X.

Morgan, M. J.

J. Ross, H. D. Speed, M. J. Morgan, “The effects of adaptation and masking on incremental threshold for contrast,” Vision Res. 33, 2051–2056 (1993).
[Crossref] [PubMed]

Morioka, C. A.

M. P. Eckstein, C. A. Morioka, J. S. Whiting, N. L. Eigler, “Psychophysical evaluation of the effect of JPEG, full-frame DCT and wavelet image compression on signal detection in medical image noise,” in Medical Imaging 1995: Image Perception, H. Kundel, ed., Proc. SPIE2436, 79–89 (1995).
[Crossref]

Movshson, J. A.

D. J. Tolhurst, J. A. Movshson, A. F. Dean, “The statistical reliability of signals in single neurons in cat and monkey visual cortex,” Vision Res. 23, 775–785 (1982).
[Crossref]

Myers, K. J.

Nachmias, J.

J. Nachmias, R. Sansbury, “Grating contrast: discrimination may be better than detection,” Vision Res. 14, 1039–1042 (1974).
[Crossref] [PubMed]

Nagaraja, N. S.

Patton, D. D.

Pelli, D. G.

Peterson, W. W.

W. W. Peterson, T. G. Birdsall, W. C. Fox, “The theory of signal detectability,” IRE Trans. Inf. Theor. PGIT-4, 171–212 (1954).
[Crossref]

Rohaly, A. M.

A. J. Ahumada, A. B. Watson, A. M. Rohaly, “Models of human image discrimination predict object detection in natural backgrounds,” in Human Vision, Visual Processing, and Digital Display VI, B. Rogowitz, J. Allebach, eds., Proc. SPIE2411, 355–362 (1995).
[Crossref]

Rolland, J. P.

H. H. Barrett, J. Yao, J. P. Rolland, K. J. Myers, “Model observers for assessment of image quality,” Proc. Natl. Acad. Sci. USA 90, 9758–9765 (1993).
[Crossref] [PubMed]

J. P. Rolland, H. H. Barrett, “Effect of random inhomogeneity on observer detection performance,” J. Opt. Soc. Am. A 9, 649–658 (1992).
[Crossref] [PubMed]

Ross, J.

J. Ross, H. D. Speed, M. J. Morgan, “The effects of adaptation and masking on incremental threshold for contrast,” Vision Res. 33, 2051–2056 (1993).
[Crossref] [PubMed]

Sansbury, R.

J. Nachmias, R. Sansbury, “Grating contrast: discrimination may be better than detection,” Vision Res. 14, 1039–1042 (1974).
[Crossref] [PubMed]

Seeley, G. W.

Shimozaki, S. S.

M. P. Eckstein, J. S. Whiting, A. E. Burgess, J. P. Thomas, S. S. Shimozaki, “Signal positional uncertainty and signals in dynamic noise,” Opt. Photonics News 5(8), 128 (1994) (Optical Society of America Annual Meeting Suppl.).

Smith, R. A.

Solomon, J.

Speed, H. D.

J. Ross, H. D. Speed, M. J. Morgan, “The effects of adaptation and masking on incremental threshold for contrast,” Vision Res. 33, 2051–2056 (1993).
[Crossref] [PubMed]

Swets, J. A.

D. M. Green, J. A. Swets, Signal Detection Theory and Psychophysics (Wiley, New York, 1966).

Swift, D. J.

Thomas, J. P.

M. P. Eckstein, J. S. Whiting, J. P. Thomas, “Role of knowledge in human visual temporal integration in spatiotemporal noise,” J. Opt. Soc. Am. A 13, 1960–1968 (1996).
[Crossref]

M. P. Eckstein, J. S. Whiting, A. E. Burgess, J. P. Thomas, S. S. Shimozaki, “Signal positional uncertainty and signals in dynamic noise,” Opt. Photonics News 5(8), 128 (1994) (Optical Society of America Annual Meeting Suppl.).

M. P. Eckstein, J. S. Whiting, J. P. Thomas, “Detection and discrimination of moving signal in Gaussian uncorrelated noise,” in Medical Imaging 1996: Image Perception, H. Kundel, ed., Proc. SPIE2712, 9–25 (1996).
[Crossref]

Tolhurst, D. J.

D. J. Tolhurst, J. A. Movshson, A. F. Dean, “The statistical reliability of signals in single neurons in cat and monkey visual cortex,” Vision Res. 23, 775–785 (1982).
[Crossref]

Wagner, R. F.

A. E. Burgess, R. F. Wagner, R. J. Jennings, H. B. Barlow, “Efficiency of human visual signal discrimination,” Science 214, 93–94 (1981).
[Crossref] [PubMed]

Watson, A. B.

A. B. Watson, J. Solomon, “Model of contrast gain control in human vision,” J. Opt. Soc. Am. A 14, 2379–2391 (1997).
[Crossref]

A. B. Watson, “DCTune: a technique for visual optimization of DCT quantization matrices for individual images,” in Digest of Technical Papers 24 (Society for Information Display, Santa Ana, Calif., 1993), pp. 946–949.

A. J. Ahumada, A. B. Watson, A. M. Rohaly, “Models of human image discrimination predict object detection in natural backgrounds,” in Human Vision, Visual Processing, and Digital Display VI, B. Rogowitz, J. Allebach, eds., Proc. SPIE2411, 355–362 (1995).
[Crossref]

Whiting, J. S.

M. P. Eckstein, J. S. Whiting, J. P. Thomas, “Role of knowledge in human visual temporal integration in spatiotemporal noise,” J. Opt. Soc. Am. A 13, 1960–1968 (1996).
[Crossref]

M. P. Eckstein, J. S. Whiting, “Visual signal detection in structured backgrounds. I. Effect of number of possible locations and signal contrast,” J. Opt. Soc. Am. A 13, 1777–1787 (1996).
[Crossref]

M. P. Eckstein, J. S. Whiting, “Lesion detection in structured noise,” Acad. Radiol. 3, 249–253 (1995).
[PubMed]

N. L. Eigler, M. P. Eckstein, D. Honig, J. S. Whiting, “Improving detection of coronary morphologic features from digital angiograms: effect of stenosis stabilized display,” Circulation 89, 2700–2709 (1994).
[Crossref] [PubMed]

M. P. Eckstein, J. S. Whiting, A. E. Burgess, J. P. Thomas, S. S. Shimozaki, “Signal positional uncertainty and signals in dynamic noise,” Opt. Photonics News 5(8), 128 (1994) (Optical Society of America Annual Meeting Suppl.).

M. P. Eckstein, J. S. Whiting, “Using computer observer models to predict the effect of JPEG image compression on human lesion detection,” Opt. Photonics News 5(8), 128 (1994) (Optical Society of America Annual Meeting Suppl.).

M. P. Eckstein, J. S. Whiting, J. P. Thomas, “Detection and discrimination of moving signal in Gaussian uncorrelated noise,” in Medical Imaging 1996: Image Perception, H. Kundel, ed., Proc. SPIE2712, 9–25 (1996).
[Crossref]

M. P. Eckstein, C. A. Morioka, J. S. Whiting, N. L. Eigler, “Psychophysical evaluation of the effect of JPEG, full-frame DCT and wavelet image compression on signal detection in medical image noise,” in Medical Imaging 1995: Image Perception, H. Kundel, ed., Proc. SPIE2436, 79–89 (1995).
[Crossref]

Wickelgren, W. A.

W. A. Wickelgren, “Unidimensional strength theory and component analysis of noise in absolute and comparative judgments,” J. Math. Psychol. 5, 102–122 (1968).
[Crossref]

Wilson, D. W.

C. K. Abbey, H. H. Barrett, D. W. Wilson, “Observer signal to noise ratio for the ML/EM algorithm,” in Medical Imaging 1996: Image Perception, H. Kundel, ed., Proc. SPIE2712, 47–58 (1996).
[Crossref]

Yao, J.

H. H. Barrett, J. Yao, J. P. Rolland, K. J. Myers, “Model observers for assessment of image quality,” Proc. Natl. Acad. Sci. USA 90, 9758–9765 (1993).
[Crossref] [PubMed]

J. Yao, H. H. Barrett, “Predicting human performance by a channelized Hotelling observer model,” in Mathematical Methods in Medical Imaging, D. C. Wilson, J. N. Wilson, eds., Proc. SPIE1768, 161–168 (1992).
[Crossref]

Acad. Radiol. (1)

M. P. Eckstein, J. S. Whiting, “Lesion detection in structured noise,” Acad. Radiol. 3, 249–253 (1995).
[PubMed]

Circulation (1)

N. L. Eigler, M. P. Eckstein, D. Honig, J. S. Whiting, “Improving detection of coronary morphologic features from digital angiograms: effect of stenosis stabilized display,” Circulation 89, 2700–2709 (1994).
[Crossref] [PubMed]

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

J. M. Foley, “Simultaneous pattern masking: How come threshold elevation bandwidth decreases as stimulus duration increases,” Invest. Ophthalmol. Visual Sci. Suppl. 37, 4205 (1996).

IRE Trans. Inf. Theor. (1)

W. W. Peterson, T. G. Birdsall, W. C. Fox, “The theory of signal detectability,” IRE Trans. Inf. Theor. PGIT-4, 171–212 (1954).
[Crossref]

J. Math. Psychol. (1)

W. A. Wickelgren, “Unidimensional strength theory and component analysis of noise in absolute and comparative judgments,” J. Math. Psychol. 5, 102–122 (1968).
[Crossref]

J. Opt. Soc. Am. (2)

J. Opt. Soc. Am. A (18)

M. P. Eckstein, J. S. Whiting, J. P. Thomas, “Role of knowledge in human visual temporal integration in spatiotemporal noise,” J. Opt. Soc. Am. A 13, 1960–1968 (1996).
[Crossref]

A. E. Burgess, “Statistically defined backgrounds: performance of a modified nonprewhitening matched filter model,” J. Opt. Soc. Am. A 11, 1237–1242 (1994).
[Crossref]

J. M. Foley, “Human luminance pattern-vision mechanisms: masking experiments require a new model,” J. Opt. Soc. Am. A 11, 1710–1719 (1994).
[Crossref]

A. B. Burgess, H. Ghandeharian, “Visual signal detection. I. Ability to use phase information,” J. Opt. Soc. Am. A 1, 900–905 (1984).
[Crossref] [PubMed]

A. E. Burgess, H. Ghandeharian, “Visual signal detection. II. Signal location identification,” J. Opt. Soc. Am. A 1, 900–905 (1984).
[Crossref] [PubMed]

A. B. Watson, J. Solomon, “Model of contrast gain control in human vision,” J. Opt. Soc. Am. A 14, 2379–2391 (1997).
[Crossref]

A. E. Burgess, X. Li, C. Abbey, “Visual signal detectability with two noise components: anomalous masking effects,” J. Opt. Soc. Am. A 14, 2420–2442 (1997).
[Crossref]

A. J. Ahumada, B. Beard, “Image discrimination models predict detection in fixed but not random noise,” J. Opt. Soc. Am. A 14, 2471–2476 (1997).
[Crossref]

A. E. Burgess, “Visual signal detection. III. On Bayesian use of prior knowledge and cross correlation,” J. Opt. Soc. Am. A 2, 1498–1507 (1985).
[Crossref] [PubMed]

D. G. Pelli, “Uncertainty explains many aspects of visual contrast detection and discrimination,” J. Opt. Soc. Am. A 2, 1508–1530 (1985).
[Crossref] [PubMed]

R. A. Smith, D. J. Swift, “Spatial frequency masking and Birdsall’s theorem,” J. Opt. Soc. Am. A 2, 1593–1599 (1985).
[Crossref] [PubMed]

K. J. Myers, H. H. Barrett, M. C. Borgstrom, D. D. Patton, G. W. Seeley, “Effect of noise correlation on detectability of disk signals in medical imaging,” J. Opt. Soc. Am. A 2, 1752–1759 (1985).
[Crossref] [PubMed]

G. E. Legge, D. Kersten, A. E. Burgess, “Contrast discrimination in noise,” J. Opt. Soc. Am. A 4, 391–404 (1987).
[Crossref] [PubMed]

A. J. Ahumada, “Putting the visual system noise back in the picture,” J. Opt. Soc. Am. A 4, 2372–2378 (1987).
[Crossref] [PubMed]

K. J. Myers, H. H. Barrett, “Addition of a channel mechanism to the ideal observer,” J. Opt. Soc. Am. A 4, 2447–2457 (1987).
[Crossref] [PubMed]

A. E. Burgess, B. Colborne, “Visual signal detection. IV. Observer inconsistency,” J. Opt. Soc. Am. A 5, 617–627 (1988).
[Crossref] [PubMed]

J. P. Rolland, H. H. Barrett, “Effect of random inhomogeneity on observer detection performance,” J. Opt. Soc. Am. A 9, 649–658 (1992).
[Crossref] [PubMed]

M. P. Eckstein, J. S. Whiting, “Visual signal detection in structured backgrounds. I. Effect of number of possible locations and signal contrast,” J. Opt. Soc. Am. A 13, 1777–1787 (1996).
[Crossref]

Opt. Photonics News (2)

M. P. Eckstein, J. S. Whiting, “Using computer observer models to predict the effect of JPEG image compression on human lesion detection,” Opt. Photonics News 5(8), 128 (1994) (Optical Society of America Annual Meeting Suppl.).

M. P. Eckstein, J. S. Whiting, A. E. Burgess, J. P. Thomas, S. S. Shimozaki, “Signal positional uncertainty and signals in dynamic noise,” Opt. Photonics News 5(8), 128 (1994) (Optical Society of America Annual Meeting Suppl.).

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

H. H. Barrett, J. Yao, J. P. Rolland, K. J. Myers, “Model observers for assessment of image quality,” Proc. Natl. Acad. Sci. USA 90, 9758–9765 (1993).
[Crossref] [PubMed]

Proc. R. Soc. London (1)

H. B. Barlow, “The absolute efficiency of perceptual decisions,” Proc. R. Soc. London 290, 71–91 (1980).
[PubMed]

Science (1)

A. E. Burgess, R. F. Wagner, R. J. Jennings, H. B. Barlow, “Efficiency of human visual signal discrimination,” Science 214, 93–94 (1981).
[Crossref] [PubMed]

Vision Res. (5)

W. S. Geisler, D. G. Albrecht, “Cortical neurons: isolation of contrast gain control,” Vision Res. 32, 1409–1410 (1992).
[Crossref] [PubMed]

J. M. Foley, G. E. Legge, “Contrast detection and near threshold discrimination in human vision,” Vision Res. 21, 1041–1053 (1981).
[Crossref]

J. Nachmias, R. Sansbury, “Grating contrast: discrimination may be better than detection,” Vision Res. 14, 1039–1042 (1974).
[Crossref] [PubMed]

D. J. Tolhurst, J. A. Movshson, A. F. Dean, “The statistical reliability of signals in single neurons in cat and monkey visual cortex,” Vision Res. 23, 775–785 (1982).
[Crossref]

J. Ross, H. D. Speed, M. J. Morgan, “The effects of adaptation and masking on incremental threshold for contrast,” Vision Res. 33, 2051–2056 (1993).
[Crossref] [PubMed]

Visual Neurosci. (1)

D. J. Heeger, “Nonlinear model of neural responses in cat visual cortex,” Visual Neurosci.181–197 (1992).
[Crossref]

Other (11)

D. G. Pelli, “Effects of visual noise,” Ph.D. dissertation (Cambridge U. Press, Cambridge, 1981).

J. Yao, H. H. Barrett, “Predicting human performance by a channelized Hotelling observer model,” in Mathematical Methods in Medical Imaging, D. C. Wilson, J. N. Wilson, eds., Proc. SPIE1768, 161–168 (1992).
[Crossref]

C. K. Abbey, H. H. Barrett, D. W. Wilson, “Observer signal to noise ratio for the ML/EM algorithm,” in Medical Imaging 1996: Image Perception, H. Kundel, ed., Proc. SPIE2712, 47–58 (1996).
[Crossref]

A. J. Ahumada, A. B. Watson, A. M. Rohaly, “Models of human image discrimination predict object detection in natural backgrounds,” in Human Vision, Visual Processing, and Digital Display VI, B. Rogowitz, J. Allebach, eds., Proc. SPIE2411, 355–362 (1995).
[Crossref]

A. B. Watson, “DCTune: a technique for visual optimization of DCT quantization matrices for individual images,” in Digest of Technical Papers 24 (Society for Information Display, Santa Ana, Calif., 1993), pp. 946–949.

H. L. Kundel, “Medical image perception,” in Proceedings of the Conference on Developing a Long-Term Plan for Imaging Research, B. L. Holman, S. H. Edwards, eds. (National Institutes of Health, Bethesda, Md., 1994), pp. 39–42.

M. P. Eckstein, C. A. Morioka, J. S. Whiting, N. L. Eigler, “Psychophysical evaluation of the effect of JPEG, full-frame DCT and wavelet image compression on signal detection in medical image noise,” in Medical Imaging 1995: Image Perception, H. Kundel, ed., Proc. SPIE2436, 79–89 (1995).
[Crossref]

M. P. Eckstein, J. S. Whiting, J. P. Thomas, “Detection and discrimination of moving signal in Gaussian uncorrelated noise,” in Medical Imaging 1996: Image Perception, H. Kundel, ed., Proc. SPIE2712, 9–25 (1996).
[Crossref]

D. M. Green, J. A. Swets, Signal Detection Theory and Psychophysics (Wiley, New York, 1966).

A. E. Burgess, “Detection and identification efficiency: an update,” in Application of Optical Instrumentation in Medicine XIII: Medical Image Production, Processing, and Displays, S. J. Dwyer, R. H. Schneider, eds., Proc. SPIE535, 50–56 (1985).
[Crossref]

C. K. Abbey, H. H. Barrett, M. P. Eckstein, “Practical issues and methodology in assessment of image quality using model observers,” in Medical Imaging: The Physics of Medical Imaging, R. L. Van Metter, J. Beuttel, eds., Proc. SPIE3032, 182–194 (1997).
[Crossref]

Cited By

OSA participates in Crossref's Cited-By Linking service. Citing articles from OSA journals and other participating publishers are listed here.

Alert me when this article is cited.


Figures (4)

Fig. 1
Fig. 1

Images used in a four-alternative forced-choice detection task in which the observer had to indicate the signal location among four possible locations. The signal was always embedded at the horizontal and vertical center in one of the four simulated arteries (lower-contrast bars in the image). The study included three experimental background conditions: (1) uniform gray background (left-hand image); (2) repeated structured background condition in which the same sample of background was used for each of the four possible locations (middle image); (3) different structured background condition in which a different random sample of background from a population of backgrounds was used for each of the four possible locations (right-hand image). The displayed photograph was scaled for presentation purposes.

Fig. 2
Fig. 2

(a)–(e) Performance for observer KS as measured by d (M=4, U=0), Eq. (4), as a function of square-root signal contrast energy for three background conditions: uniform gray background (□), repeated structured background (♦), and different structured background (○). The five panels correspond to five different levels of added rms white noise: (a) 0, (b) 0.071, (c) 0.125, (d) 0.18, (e) 0.25, respectively. The symbols correspond to data points from an experiment based on 210 trials per data point. The error bars correspond to 95% confidence intervals based on the propagated binomial variance. The solid curves represent the best fits of Eq. (6) to the data for each condition. The dashed line represents performance for the ideal observer calculated from Eq. (2).

Fig. 3
Fig. 3

Same as Fig. 2, but for observer GN.

Fig. 4
Fig. 4

Slope of psychometric functions for (a) observer KS and (b) observer GN as a function of the external noise rms for the three background conditions: uniform background (□), repeated structured background (♦), and different structured background (○). The solid curves correspond to the simultaneous fit of Eqs. (5), (7), and (8) for the corresponding background conditions with six free parameters: three sampling efficiencies, equivalent internal noise, equivalent contrast gain control noise, and equivalent background variation noise. The dotted curve corresponds to the ideal observer performance in white noise.

Tables (3)

Tables Icon

Table 1 Best Fits to the Individual Psychometric Functions by Use of Eq. (6), Which Allows for Possible Signal Uncertainty a

Tables Icon

Table 2 Best Fits to the Variation of the Psychometric Slope (δ) as a Function of the External Added White Noise, Obtained by Use of Eq. (5) for Uniform Background Condition, Eq. (7) for the Repeated Structured Background Condition, and Eq. (8) for the Different Structured Background Condition (Observer KS) a

Tables Icon

Table 3 Same as Table 2, but for Observer GN

Equations (11)

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

d=λs-λnσλ,
SNR=EN0.
E=S2(x, y)dxdy,
Pc(M, d)=-+g(x-d)GM-1(x)dx,
g(x)=12π exp-x22,
G(x)=-xg(y)dy.
d=δE,whereδ=Jubσi2+σe2 ,
Pc(M, U, d)=-+g(x-d)[G(x)][M(1+U)-1]+Ug(x)[G(x)][M(1+U)-2]G(x-d)dx,
d=δE,whereδ=Jsbσi2+σe2+σcgc21/2
d=δE,where
δ=jrbσe2+σi2+σcgc2+σrbv21/2,

Metrics