Role of second-and third-order statistics in the discriminability of natural images

Journal of the Optical Society of America A: Optics and Image Science, and Vision

Volumn 14, Issue 9, 1997, Pages 2081-2090

  Thomson, Mitchell G A ^a   Foster, David H ^a  

^a ASTON UNIVERSITY   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

IMAGE ENHANCEMENT; MATHEMATICAL MODELS; RANDOM PROCESSES; SIGNAL DETECTION; SIGNAL TO NOISE RATIO; STATISTICS; WAVELET TRANSFORMS;

IMAGE LUMINANCE; PHASE SPECTRUM; SECOND ORDER STATISTICS; THIRD ORDER STATISTICS;

COMPUTER VISION;

EID: 0031235286     PISSN: 10847529     EISSN: 15208532     Source Type: Journal    
DOI: 10.1364/JOSAA.14.002081     Document Type: Article

References (40)

1. 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).
2. L. Sirovich and M. Kirby, “Low-dimensional procedure for the characterization of human faces,” J. Opt. Soc. Am. A 4, 519-524 (1987).
3. R. J. Baddeley and P. J. B. Hancock, “A statistical analysis of natural images matches psychophysically derived orientation tuning curves,” Proc. R. Soc. London Ser. B 246, 219-223 (1991).
4. R. L. DeValois, D. G. Albrecht, and L. G. Thorell, “Spatial frequency selectivity of cells in macaque visual cortex,” Vision Res. 22, 545-559 (1982).
5. Y. Tadmor and D. J. Tolhurst, “Both the phase and amplitude spectrum may determine the appearance of natural images,” Vision Res. 33, 141-145 (1993).
6. M. G. A. Thomson and D. H. Foster, “Effect of phase refiltering on visual tuning to second-order image structure,” Perception 22 (Suppl.), 121-122 (1993).
7. Y. Tadmor and D. J. Tolhurst, “Discrimination of changes in the second-order statistics of natural and synthetic images,” Vision Res. 34, 541-554 (1994).
8. A. V. Oppenheim and J. S. Lim, “The importance of phase in signals,” Proc. IEEE 69, 529-541 (1981).
9. L. N. Piotrowski and F. W. Campbell, “A demonstration of the visual importance and flexibility of spatial-frequency amplitude and phase,” Perception 11, 337-346 (1982).
10. D. J. Field, “Scale-invariance and self-similar ‘wavelet’ transforms: an analysis of natural scenes and mammalian visual systems,” in Wavelets, Fractals and Fourier Transforms, M. Farge, J. C. R. Hunt, and J. C. Vassilicos, eds. (Clarendon, Oxford, 1993).
11. M. C. Morrone and D. C. Burr, “Feature detection in human vision: a phase-dependent energy model,” Proc. R. Soc. London Ser. B 235, 221-245 (1988).
12. J. H. Van Hateren, “Theoretical predictions of spatiotemporal receptive fields of fly LMCs, and experimental validation,” J. Comp. Physiol. A 171, 157-170 (1992).
13. D. C. Knill, D. Field, and D. Kersten, “Human discrimination of natural images,” J. Opt. Soc. Am. A 7, 1113-1123 (1990).
14. D. J. Field, “What the statistics of natural images tell us about visual coding,” in Human Vision, Visual Processing, and Digital Display, B. E. Rogowitz, ed., Proc. SPIE 1077, 269-276 (1989).
15. J. I. Yellott Jr., “Implications of triple correlation uniqueness for texture statistics and the Julesz conjecture,” J. Opt. Soc. Am. A 10, 777-793 (1993).
16. G. Julesz, E. N. Gilbert, L. A. Shepp, and H. L. Frisch, “Inability of humans to discriminate between visual textures that agree in second-order statistics-revisited,” Perception 2, 391-405 (1973).
17. S. A. Klein and C. W. Tyler, “Phase discrimination of compound gratings: generalized autocorrelation analysis,” J. Opt. Soc. Am. A 3, 868-879 (1986).
18. M. B. Priestley, Nonlinear and Nonstationary Time-Series Analysis (Academic, London, 1988).
19. P. Brodatz, Textures: A Photographic Album for Artists and Designers (Dover, New York, 1956).
20. K. M. M. Prabhu and K. B. Bagan, “Variable parameter window families for digital spectral analysis,” IEEE Trans. Acoust. Speech Signal Process. 37, 946-949 (1989).
21. D. J. Tolhurst, Y. Tadmor, and Tang Chao, “Amplitude spectra of natural images,” Ophthalmic. Physiol. Opt. 12, 229-232 (1992).
22. D. M. Green and J. A. Swets, Signal Detection Theory (Wiley, New York, 1966).
23. R. D. Sorkin, “Matching procedures in psychoacoustics,” J. Acoust. Soc. Am. 34, 108-113 (1962).
24. D. H. Foster and W. F. Bischof, “Thresholds from psychometric functions: superiority of bootstrap to incremental and probit variance estimators,” Psychol. Bull. 109, 152-159 (1991).
25. W. S. Geisler, “Sequential ideal-observer analysis of visual discriminations,” Psychol. Rev. 96, 267-314 (1989).
26. H. H. Barrett, J. Yao, J. P. Rolland, and K. J. Myers, “Model observers for the assessment of image quality,” Proc. Natl. Acad. Sci. USA 90, 9758-9765 (1993).
27. J. G. Proakis, C. M. Rader, F. Ling, and C. C. Nikias, Advanced Digital Signal Processing (Macmillan, New York, 1992).
28. M. G. A. Thomson and D. H. Foster, “Phase perception and the bispectra of natural images,” Opt. Photon. News 5 (No. 8, Suppl.), 110 (1994).
29. A. K. Nandi, “Robust estimation of third-order cumulants in applications of higher-order statistics,” IEE Proc. F 140, 380-389 (1993).
30. S. Elgar, “Relationships involving third moments and bispectra of a harmonic process,” IEEE Trans. Acoust. Speech Signal Process. ASSP-35, 1725-1726 (1987).
31. K. J. Myers and H. H. Barrett, “Addition of a channel mechanism to the ideal-observer model,” J. Opt. Soc. Am. A 4, 2447-2457 (1987).
32. M. Hubner, M. Caelli, and I. Rentschler, “Visual phase resolution for grayscale textures,” Percept. Psychophys. 43, 319-325 (1988).
33. Y. Tadmor and D. J. Tolhurst, “Is the human visual system optimized for processing natural images?" Perception 19 (Suppl.), A76 (1990).
34. E. Switkes, M. J. Mayer, and J. A. Sloan, “Spatial-frequency analysis of the visual environment: anistropy and the carpentered environment hypothesis,” Vision Res. 18, 1393-1399 (1978).
35. I. R. Paterson, “The information available in natural textures for classification tasks: a computation and psychophysical investigation,” Perception 22 (Suppl.), A68 (1993).
36. F. W. Campbell, R. H. S. Carpenter, and J. Z. Levinson, “Visibility of aperiodic patterns compared with that of sinusoidal gratings,” J. Physiol. (London) 204, 283-298 (1969).
37. D. J. Field and B. Olshausen, “Insights into visual coding gained from an understanding of the statistics of natural scenes,” Invest. Ophthalmol. Visual Sci. 37, 3088 (1996).
38. S. G. Mallat, “A theory for multiresolution signal decomposition: the wavelet representation,” IEEE Trans. Pattern. Anal. Mach. Intell. 11, 674-693 (1989).
39. R. F. Quick, “A vector-magnitude model of contrast detection,” Kybernetik 16, 65-67 (1974).
40. V. Chandran and S. Elgar, “Bispectral analysis of 2-D random processes,” IEEE Trans. Acoust. Speech Signal Process. 35, 2181-2190 (1990).