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Journal of the Optical Society of America A

Journal of the Optical Society of America A

| OPTICS, IMAGE SCIENCE, AND VISION

  • Vol. 20, Iss. 7 — Jul. 1, 2003
  • pp: 1164–1180

Effects of natural images on the detectability of simple and compound wavelet subband quantization distortions

Damon M. Chandler and Sheila S. Hemami  »View Author Affiliations


JOSA A, Vol. 20, Issue 7, pp. 1164-1180 (2003)
http://dx.doi.org/10.1364/JOSAA.20.001164


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Abstract

Quantization of the coefficients within a discrete wavelet transform subband gives rise to distortions in the reconstructed image that are localized in spatial frequency and orientation and are spatially correlated with the image. We investigated the detectability of these distortions: Contrast thresholds were measured for both simple and compound distortions presented in the unmasked paradigm and against two natural-image maskers. Simple and compound distortions were generated through uniform scalar quantization of one or two subbands. Unmasked detection thresholds for simple distortions yielded contrast sensitivity functions similar to those reported for 1-octave Gabor patches. Detection thresholds for simple distortions presented against two natural-image backgrounds revealed that thresholds were elevated across the frequency range of 1.15–18.4 cycles per degree with the greatest elevation for low-frequency distortions. Unmasked thresholds for compound distortions revealed relative sensitivities of 1.1–1.2, suggesting that summation of responses to wavelet distortions is similar to summation of responses to gratings. Masked thresholds for compound distortions revealed relative sensitivities of 1.5–1.7, suggesting greater summation when distortions are masked by natural images.

© 2003 Optical Society of America

OCIS Codes
(100.7410) Image processing : Wavelets
(330.1800) Vision, color, and visual optics : Vision - contrast sensitivity
(330.1880) Vision, color, and visual optics : Detection
(330.5020) Vision, color, and visual optics : Perception psychology
(330.5510) Vision, color, and visual optics : Psychophysics

Citation
Damon M. Chandler and Sheila S. Hemami, "Effects of natural images on the detectability of simple and compound wavelet subband quantization distortions," J. Opt. Soc. Am. A 20, 1164-1180 (2003)
http://www.opticsinfobase.org/josaa/abstract.cfm?URI=josaa-20-7-1164


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References

  1. R. L. DeValois and K. K. Devalois, Spatial Vision (Oxford U. Press, New York, 1990).
  2. D. Regan, Human Perception of Objects: Early Visual Processing of Spatial Form Defined by Luminance, Color, Texture, Motion, and Binocular Disparity (Sinauer, Sunderland, Mass., 2000).
  3. I. J. Cox and M. L. Miller, “A review of watermarking and the importance of perceptual modeling,” in Human Vision and Electronic Imaging II, B. Rogowitz, and T. Pappas, eds., Proc. SPIE 3016, 92–99 (1997).
  4. D. J. Heeger and J. R. Bergen, “Pyramid-based texture analysis/synthesis,” in Proceedings of SIGGRAPH 95 (Association for Computing Machinery, Los Angeles, Calif., 1995), pp. 229–238.
  5. D. J. Jobson, Z. Rahman, and G. A. Woodell, “A multi-scale Retinex for bridging the gap between color images and the human observation of scenes,” IEEE Trans. Image Process. 6, 965–976 (1997).
  6. “Information technology–JPEG 2000 image coding system: core coding system,” Tech. Rep. ISO/IEC FDIS15444–1 (International Organization for Standardization, Geneva, Switzerland, 2000).
  7. T. Caelli and G. Moraglia, “On the detection of signals embedded in natural scenes,” Percept. Psychophys. 39, 87–95 (1986).
  8. 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).
  9. D. C. Knill, D. J. Field, and D. Kersten, “Human discrimination of fractal images,” J. Opt. Soc. Am. A 7, 1113–1123 (1990).
  10. E. P. Simoncelli and B. A. Olshausen, “Natural image statistics and neural representation,” Annu. Rev. Neurosci. 24, 1193–1216 (2001).
  11. C. A. Parraga, T. Troscianko, and D. J. Tolhurst, “The human visual system is optimised for processing the spatial information in natural visual images,” Curr. Biol. 10, 35–38 (2000).
  12. M. A. Webster and E. Miyahara, “Contrast adaptation and the spatial structure of natural image,” J. Opt. Soc. Am. A 14, 2355–2366 (1997).
  13. A. V. Oppenheim and J. S. Lim, “The importance of phase in signals,” Proc. IEEE 69, 529–541 (1981).
  14. M. G. A. Thomson, D. H. Foster, and R. J. Summers, “Human sensitivity to phase perturbations in natural images: a statistical framework,” Perception 29, 1057–1069 (2000).
  15. P. J. Bex and W. Makous, “Spatial frequency, phase, and the contrast of natural images,” J. Opt. Soc. Am. A 19, 1096–1106 (2002).
  16. W. S. Geisler, J. S. Perry, B. J. Super, and D. P. Gallogly, “Edge co-occurrence in natural images predicts contour grouping performance,” Vision Res. 41, 711–724 (2001).
  17. J. J. Atick, “Could information theory provide an ecological theory of sensory processing?” Network 3, 213–251 (1992).
  18. B. A. Olshausen and D. J. Field, “Sparse coding with an overcomplete basis set: a strategy employed by V1?” Vision Res. 37, 3311–3325 (1997).
  19. A. Hyvärinen and P. O. Hoyer, “A two-layer sparse coding model learns simple and complex cell receptive fields and topography from natural images,” Vision Res. 41, 2413–2423 (2001).
  20. A. Hyvärinen and P. O. Hoyer, “Emergence of phase and shift invariant features by decomposition of natural images into independent feature subspaces,” Neural Comput. 12, 1705–1720 (2000).
  21. P. O. Hoyer and A. Hyvärinen, “A multi-layer sparse coding network learns contour coding from natural images,” Vision Res. 42, 1593–1605 (2002).
  22. G. E. Legge and J. M. Foley, “Contrast masking in human vision,” J. Opt. Soc. Am. 70, 1458–1470 (1980).
  23. P. C. Teo and D. J. Heeger, “Perceptual image distortion,” in Human Vision, Visual Processing, and Digital Display V, B. Rogowitz and J. Allebach, eds., Proc. SPIE 2179, 127–141 (1994).
  24. J. M. Foley, “Human luminance pattern mechanisms: masking experiments require a new model,” J. Opt. Soc. Am. A 11, 1710–1719 (1994).
  25. J. M. Foley and C. C. Chen, “Pattern detection in the presence of maskers that differ in spatial phase and temporal offset: threshold measurements and a model,” Vision Res. 39, 3855–3872 (1999).
  26. A. B. Watson and J. A. Solomon, “A model of visual contrast gain control and pattern masking,” J. Opt. Soc. Am. A 14, 2379–2390 (1997).
  27. T. S. Meese and D. J. Holmes, “Adaptation and gain pool summation: alternative models and masking data,” Vision Res. 42, 1113–1125 (2002).
  28. D. G. Albrecht and W. S. Geisler, “Motion selectivity and the contrast-response function of simple cells in the visual cortex,” Visual Neurosci. 7, 531–546 (1991).
  29. D. J. Heeger, “Normalization of cell responses in cat striate cortex,” Visual Neurosci 9, 181–197 (1992).
  30. S. Daly, “Visible differences predictor: an algorithm for the assessment of image fidelity,” in Digital Images and Human Vision, A. B. Watson, ed. (MIT Press, Cambridge, Mass., 1993), pp. 179–206.
  31. P. W. Jones, S. Daly, R. S. Gaborsky, and M. Rabbani, “Comparative study of wavelet and DCT decompositions with equivalent quantization and encoding strategies for medical images,” in Medical Imaging, Y. Kim, ed., Proc. SPIE 2431, 571–582 (1995).
  32. W. Zeng, S. Daly, and S. Lei, “An overview of the visual optimization tools in JPEG 2000,” Signal Process. Image Commun. 17, 85–104 (2002).
  33. W. Zeng, S. Daly, and S. Lei, “Point-wise extended visual masking for JPEG-2000 image compression,” in Proceedings of the IEEE International Conference on Image Processing (Institute of Electrical and Electronics Engineers, New York, 2000), pp. 657–660.
  34. E. Peli, “Contrast in complex images,” J. Opt. Soc. Am. A 7, 2032–2040 (1990).
  35. F. W. Campbell and J. G. Robson, “Application of Fourier analysis to the visibility of gratings,” J. Physiol. (London) 197, 551–566 (1968).
  36. N. Graham, Visual Pattern Analyzers (Oxford U. Press, New York, 1989).
  37. V. Manahilov and W. A. Simpson, “Energy model for contrast detection: spatial-frequency and orientation selectivity in grating summation,” Vision Res. 41, 1547–1560 (2001).
  38. A. B. Watson, “Summation of grating patches indicates many types of detector at one retinal location,” Vision Res. 22, 17–25 (1982).
  39. R. F. Quick, “A vector magnitude model of contrast detection,” Kybernetik 16, 65–67 (1974).
  40. Y. Bonneh and D. Sagi, “Effects of spatial configuration on contrast detection,” Vision Res. 38, 3541–3553 (1998).
  41. C. R. Carlson, R. W. Cohen, and I. Gorog, “Visual processing of simple two-dimensional sine-wave luminance gratings,” Vision Res. 17, 351–358 (1977).
  42. N. Graham and J. Nachmias, “Detection of grating patterns containing two spatial frequencies: a comparison of single-channel and multiple-channels models,” Vision Res. 11, 251–259 (1971).
  43. M. B. Sachs, J. Nachmias, and J. G. Robson, “Spatial-frequency channels in human vision,” J. Opt. Soc. Am. 61, 1176–1186 (1971).
  44. G. Meinhardt, “Evidence for different nonlinear summation schemes for lines and gratings at threshold,” Biol. Cybern. 81, 263–277 (1999).
  45. A. B. Watson, G. Y. Yang, J. A. Solomon, and J. Villasenor, “Visibility of wavelet quantization noise,” IEEE Trans. Image Process. 6, 1164–1175 (1997).
  46. A. B. Watson, “The cortex transform: rapid computation of simulated neural images,” Comput. Vision Graph. Image Process. 39, 311–327 (1987).
  47. J. Villasenor, B. Belzer, and J. Liao, “Wavelet filter evaluation for image compression,” IEEE Trans. Image Process. 4, 1053–1060 (1995).
  48. M. G. Ramos and S. S. Hemami, “Suprathreshold wavelet coefficient quantization in complex stimuli: psychophysical evaluation and analysis,” J. Opt. Soc. Am. A 18, 2385–2397 (2001).
  49. R. M. Gray and D. L. Neuhoff, “Quantization,” IEEE Trans. Inf. Theory 44, 2325–2384 (1998).
  50. D. M. Chandler and S. S. Hemami, “Additivity models for suprathreshold distortion in quantized wavelet-coded images,” in Human Vision and Electronic Imaging VII, B. Rogowitz and T. Pappas, eds., Proc. SPIE 4662, 105–118 (2002).
  51. A. B. Watson and D. G. Pelli, “QUEST: a Bayesian adaptive psychometric method,” Percept. Psychophys. 33, 113–120 (1983).
  52. D. H. Brainard, “The Psychophysics Toolbox,” Spatial Vision 10, 433–436 (1997).
  53. D. G. Pelli, “The VideoToolbox software for visual psychophysics: transforming numbers into movies,” Spatial Vision 10, 437–442 (1997).
  54. R. A. Smith and D. J. Swift, “Spatial-frequency masking and Birdsall’s theorem,” J. Opt. Soc. Am. A 2, 1593–1599 (1985).
  55. A. B. Watson, M. Taylor, and R. Borthwick, “Image quality and entropy masking,” in Human Vision and Electronic Imaging II, B. Rogowitz and T. Pappas, eds., Proc. SPIE 3016, 2–12 (1997).
  56. Subject MM did not participate in the parts of experiments 2 and 4 that tested summation on the spatial-frequency dimension.
  57. K. Tiippana and R. Näsänen and J. Rovamo, “Contrast matching of two-dimensional compound gratings,” Vision Res. 34, 1157–1163 (1994).
  58. B. Moulden, F. A. A. Kingdom, and L. F. Gatley, “The standard deviation of luminance as a metric for contrast in random-dot images,” Perception 19, 79–101 (1990).
  59. F. A. A. Kingdom, A. Hayes, and D. J. Field, “Sensitivity to contrast histogram differences in synthetic wavelet-textures,” Vision Res. 41, 585–598 (2001).
  60. E. Peli, L. E. Arend, G. M. Young, and R. B. Goldstein, “Contrast sensitivity to patch stimuli: effects of spatial bandwidth and temporal presentation,” Spatial Vision 7, 1–14 (1993).
  61. N. Graham, “Visual detection of aperiodic spatial stimuli by probability summation among narrowband channels,” Vision Res. 17, 637–652 (1977).
  62. D. G. Pelli, “Effects of visual noise,” Ph.D. thesis (Cambridge University, Cambridge, UK, 1981).
  63. J. A. Solomon, “Channel selection with non-white-noise masks,” J. Opt. Soc. Am. A 17, 986–993 (2000).
  64. R. J. Safranek and J. D. Johnston, “A perceptually tuned sub-band image coder with image dependent quantization and post-quantization data compression,” in Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (Institute of Electrical and Electronics Engineers, New York, 1989), Vol. 3, pp. 1945–1948.
  65. The data and the two images used in this study are available online at http://foulard.ece.cornell.edu/dmc27/ImageEffects.html.
  66. Only the LH and HL subbands have been quantized.
  67. M. Stokes, M. Anderson, S. Chandrasekar, and R. Motta, “A standard default color space for the Internet–sRGB,” November 1996, http://www.w3.org/Graphics/Color/sRGB.html.
  68. M. P. Eckert and A. P. Bradley, “Perceptual quality metrics applied to still image compression,” Signal Process. 70, 177–200 (1998).

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