OSA's Digital Library

Virtual Journal for Biomedical Optics

Virtual Journal for Biomedical Optics

| EXPLORING THE INTERFACE OF LIGHT AND BIOMEDICINE

  • Editors: Andrew Dunn and Anthony Durkin
  • Vol. 8, Iss. 7 — Aug. 1, 2013

Power spectrum model of visual masking: simulations and empirical data

Ignacio Serrano-Pedraza, Vicente Sierra-Vázquez, and Andrew M. Derrington  »View Author Affiliations


JOSA A, Vol. 30, Issue 6, pp. 1119-1135 (2013)
http://dx.doi.org/10.1364/JOSAA.30.001119


View Full Text Article

Enhanced HTML    Acrobat PDF (1076 KB)





Browse Journals / Lookup Meetings

Browse by Journal and Year


   


Lookup Conference Papers

Close Browse Journals / Lookup Meetings

Article Tools

Share
Citations

Abstract

In the study of the spatial characteristics of the visual channels, the power spectrum model of visual masking is one of the most widely used. When the task is to detect a signal masked by visual noise, this classical model assumes that the signal and the noise are previously processed by a bank of linear channels and that the power of the signal at threshold is proportional to the power of the noise passing through the visual channel that mediates detection. The model also assumes that this visual channel will have the highest ratio of signal power to noise power at its output. According to this, there are masking conditions where the highest signal-to-noise ratio (SNR) occurs in a channel centered in a spatial frequency different from the spatial frequency of the signal (off-frequency looking). Under these conditions the channel mediating detection could vary with the type of noise used in the masking experiment and this could affect the estimation of the shape and the bandwidth of the visual channels. It is generally believed that notched noise, white noise and double bandpass noise prevent off-frequency looking, and high-pass, low-pass and bandpass noises can promote it independently of the channel’s shape. In this study, by means of a procedure that finds the channel that maximizes the SNR at its output, we performed numerical simulations using the power spectrum model to study the characteristics of masking caused by six types of one-dimensional noise (white, high-pass, low-pass, bandpass, notched, and double bandpass) for two types of channel’s shape (symmetric and asymmetric). Our simulations confirm that (1) high-pass, low-pass, and bandpass noises do not prevent the off-frequency looking, (2) white noise satisfactorily prevents the off-frequency looking independently of the shape and bandwidth of the visual channel, and interestingly we proved for the first time that (3) notched and double bandpass noises prevent off-frequency looking only when the noise cutoffs around the spatial frequency of the signal match the shape of the visual channel (symmetric or asymmetric) involved in the detection. In order to test the explanatory power of the model with empirical data, we performed six visual masking experiments. We show that this model, with only two free parameters, fits the empirical masking data with high precision. Finally, we provide equations of the power spectrum model for six masking noises used in the simulations and in the experiments.

© 2013 Optical Society of America

OCIS Codes
(330.1800) Vision, color, and visual optics : Vision - contrast sensitivity
(330.4060) Vision, color, and visual optics : Vision modeling
(330.5510) Vision, color, and visual optics : Psychophysics

ToC Category:
Vision, Color, and Visual Optics

History
Original Manuscript: February 25, 2013
Manuscript Accepted: April 14, 2013
Published: May 14, 2013

Virtual Issues
Vol. 8, Iss. 7 Virtual Journal for Biomedical Optics

Citation
Ignacio Serrano-Pedraza, Vicente Sierra-Vázquez, and Andrew M. Derrington, "Power spectrum model of visual masking: simulations and empirical data," J. Opt. Soc. Am. A 30, 1119-1135 (2013)
http://www.opticsinfobase.org/vjbo/abstract.cfm?URI=josaa-30-6-1119


Sort:  Author  |  Year  |  Journal  |  Reset  

References

  1. F. W. Campbell and J. G. Robson, “Application of Fourier analysis to the visibility of gratings,” J. Physiol. 197, 551–566 (1968).
  2. C. Blakemore and F. W. Campbell, “On the existence of neurones in the human visual system selectively sensitive to the orientation and size of retinal images,” J. Physiol. 203, 237–260 (1969).
  3. N. Graham and J. Nachmias, “Detection of grating patterns containing two spatial frequencies: a comparison of single-channel and multiple-channels models,” Vis. Res. 11, 251–259 (1971). [CrossRef]
  4. M. B. Sachs, J. Nachmias, and J. G. Robson, “Spatial-frequency channels in human vision,” J. Opt. Soc. Am. 61, 1176–1186 (1971). [CrossRef]
  5. C. F. Stromeyer and S. Klein, “Evidence against narrow-band spatial frequency channels in human vision: the detectability of frequency modulated gratings,” Vis. Res. 15, 899–910 (1975). [CrossRef]
  6. O. Braddick, F. W. Campbell, and J. Atkinson, “Channels in vision: basic aspects,” in Handbook of Sensory Physiology, R. Held, H. W. Leibowitz, and H. L. Teuber, eds. (Springer Verlag, 1978), pp. 3–38.
  7. H. Fletcher, “Auditory patterns,” Rev. Mod. Phys. 12, 47–65 (1940). [CrossRef]
  8. R. D. Patterson and B. C. J. Moore, “Auditory filters and excitation patterns as representations of frequency resolution,” in Frequency Selectivity in Hearing, B. C. J. Moore, ed. (Academic, 1986), pp. 123–177.
  9. B. C. J. Moore, An Introduction to the Psychology of Hearing (Academic, 1997).
  10. C. F. Stromeyer and B. Julesz, “Spatial-frequency masking in vision: critical bands and spread of masking,” J. Opt. Soc. Am. 62, 1221–1232 (1972). [CrossRef]
  11. D. G. Pelli, “Effects of visual noise,” Ph.D. dissertation (Cambridge University, 1981).
  12. M. E. Perkins and M. S. Landy, “Nonadditivity of masking by narrow-band noises,” Vis. Res. 31, 1053–1065 (1991). [CrossRef]
  13. M. A. Losada and K. T. Mullen, “Color and luminance spatial tuning estimated by noise masking in the absence of off-frequency looking,” J. Opt. Soc. Am. A 12, 250–260 (1995). [CrossRef]
  14. K. T. Mullen and M. A. Losada, “The spatial tuning of color and luminance peripheral vision measured with notch filtered noise masking,” Vis. Res. 39, 721–731 (1999). [CrossRef]
  15. K. T. Blackwell, “The effect of white and filtered noise on contrast detection thresholds,” Vis. Res. 38, 267–280 (1998). [CrossRef]
  16. J. A. Solomon, “Channel selection with non-white-noise mask,” J. Opt. Soc. Am. A 17, 986–993 (2000). [CrossRef]
  17. I. Serrano-Pedraza and V. Sierra-Vázquez, “The effect of white-noise mask level on sine-wave contrast threshold and the critical band masking model,” Spanish J. Psychol. 9, 249–262 (2006).
  18. Z. M. Westrick, C. A. Henry, and M. S. Landy, “Inconsistent channel bandwidth estimates suggest winner-take-all nonlinearity in second-order vision,” Vis. Res. 81, 58–68 (2013). [CrossRef]
  19. J. A. Solomon and D. G. Pelli, “The visual filter mediating letter identification,” Nature 369, 395–397 (1994). [CrossRef]
  20. N. J. Majaj, D. G. Pelli, P. Kurshan, and M. Palomares, “The role of spatial frequency channels in letter identification,” Vis. Res. 42, 1165–1184 (2002). [CrossRef]
  21. C. P. Talgar, D. G. Pelli, and M. Carrasco, “Covert attention enhances letter identification without affecting channel tuning,” J. Vis. 4(1):3, 22–31 (2004).
  22. I. Oruc, M. S. Landy, and D. G. Pelli, “Noise masking reveals channels for second-order letters,” Vis. Res. 46, 1493–1506 (2006). [CrossRef]
  23. I. Oruc and M. S. Landy, “Scale dependence and channel switching in letter identification,” J. Vis. 9(9):4, 1–19 (2009).
  24. I. Oruç and J. J. S. Barton, “Critical frequencies in the perception of letters, faces, and novel shapes: evidence for limited scale invariance for faces,” J. Vis. 10(12):20, 1–12 (2010).
  25. D. G. Pelli, D. M. Levi, and S. T. L. Chung, “Using visual noise to characterize amblyopic letter identification,” J. Vis. 4(10):6, 904–920 (2004).
  26. R. D. Patterson, “Auditory filter shape,” J. Acoust. Soc. Am. 55, 802–809 (1974). [CrossRef]
  27. W. B. Davenport and W. L. Root, An Introduction to the Theory of Random Signals and Noise (Wiley-IEEE, 1958).
  28. D. M. Green and J. A. Swets, Signal Detection Theory and Psychophysics (Wiley, 1966). Reprinted with corrections, 1974.
  29. R. D. Patterson and G. B. Henning, “Stimulus variability and auditory filter shape,” J. Acoust. Soc. Am. 62, 649–664 (1977). [CrossRef]
  30. G. B. Henning, B. G. Hertz, and J. L. Hinton, “Effects of different hypothetical detection mechanisms on the shape of spatial-frequency filters inferred from masking,” J. Opt. Soc. Am. 71, 574–581 (1981). [CrossRef]
  31. G. B. Henning and F. A. Wichmann, “Some observations on the pedestal effect,” J. Vis. 7(1):3, 1–15 (2007). [CrossRef]
  32. B. Leshowitz and F. L. Wightman, “On-frequency masking with continuous sinusoids,” J. Acoust. Soc. Am. 49, 1180–1190 (1971).
  33. R. D. Patterson, “Auditory filter shapes derived with noise stimuli,” J. Acoust. Soc. Am. 59, 640–654 (1976). [CrossRef]
  34. C. V. Hutchinson and T. Ledgeway, “Spatial frequency selective masking of first-order and second-order motion in the absence of off-frequency looking,” Vis. Res. 44, 1499–1510 (2004). [CrossRef]
  35. R. D. Patterson and I. Nimmo-Smith, “Off-frequency listening and auditory-filter asymmetry,” J. Acoust. Soc. Am. 67, 229–245 (1980). [CrossRef]
  36. B. C. J. Moore, An Introduction to the Psychology of Hearing (Academic, 1997).
  37. I. Serrano-Pedraza, “Procesos visuales de demodulación espacial,” Doctoral dissertation (Universidad Complutense, 2005) (unpublished). Available at http://www.ucm.es/BUCM/tesis/psi/ucm-t28909.pdf .
  38. I. Serrano-Pedraza and V. Sierra-Vazquez, “The effect of white-noise mask level on sinewave contrast detection thresholds and the critical-band-masking model,” Spanish J. Psychol. 9, 249–262 (2006).
  39. D. H. Kelly, “Spatial frequency selectivity in the retina,” Vis. Res. 15, 665–672 (1975). [CrossRef]
  40. M. C. Morrone and D. C. Burr, “Feature detection in human vision: a phase-dependent energy model,” Proc. R. Soc. Lond. B 235, 221–245 (1988).
  41. M. A. García-Pérez and V. Sierra-Vázquez, “Deriving channel gains from large-area sine-wave contrast sensitivity data,” Spatial Vis. 9, 235–260 (1995).
  42. A. Schofield and M. A. Georgeson, “Sensitivity to contrast modulation: the spatial frequency dependence of second-order vision,” Vis. Res. 43, 243–259 (2003). [CrossRef]
  43. H. R. Wilson, D. K. McFarlane, and G. C. Phillips, “Spatial frequency tuning of orientation selective units estimated by oblique masking,” Vis. Res. 23, 873–882 (1983). [CrossRef]
  44. J. Rovamo, R. Fransilla, and R. Näsänen, “Contrast sensitivity as a function of spatial frequency, viewing distance and eccentricity with and without spatial noise,” Vis. Res. 32, 631–637 (1992). [CrossRef]
  45. A. Schofield and M. A. Georgeson, “Sensitivity to modulations of luminance and contrast in visual white noise: separate mechanisms with similar behaviour,” Vis. Res. 39, 2697–2716 (1999). [CrossRef]
  46. P. E. King-Smith, S. S. Grigsby, A. J. Vingrys, S. C. Benes, and A. Supowit, “Efficient and unbiased modifications of the QUEST threshold method: theory, simulations, experimental evaluation and practical implementation,” Vis. Res. 34, 885–912 (1994). [CrossRef]
  47. J. A. Nelder and R. Mead, “A simplex method for function minimization,” Comput. J. 7, 308–313 (1965).

Cited By

Alert me when this paper is cited

OSA is able to provide readers links to articles that cite this paper by participating in CrossRef's Cited-By Linking service. CrossRef includes content from more than 3000 publishers and societies. In addition to listing OSA journal articles that cite this paper, citing articles from other participating publishers will also be listed.


« Previous Article  |  Next Article »

OSA is a member of CrossRef.

CrossCheck Deposited