Abstract

We investigate the ability of humans to perceive changes in the appearance of images of surface texture caused by the variation of their higher order statistics. We incrementally randomize their phase spectra while holding their first and second order statistics constant in order to ensure that the change in the appearance is due solely to changes in third and other higher order statistics. Stimuli comprise both natural and synthetically generated naturalistic images, with the latter being used to prevent observers from making pixel-wise comparisons. A difference scaling method is used to derive the perceptual scales for each observer, which show a sigmoidal relationship with the degree of randomization. Observers were maximally sensitive to changes within the 20%–60% randomization range. In order to account for this behavior we propose a biologically plausible model that computes the variance of local measurements of phase congruency.

© 2010 Optical Society of America

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2009

O. R. Joubert, G. A. Rousselet, M. Fabre-Thorpe, and D. Fize, “Rapid visual categorization of natural scene contexts with equalized amplitude spectrum and increasing phase noise,” J. Vision 9, 1–16 (2009).
[CrossRef]

2008

S. Padilla, O. Drbohlav, P. R. Green, A. D. Spence, and M. J. Chantler, “Perceived roughness of 1/fbeta noise surfaces,” Vision Res. 48, 1791–1797 (2008).
[CrossRef] [PubMed]

J. T. Lindgren, J. Hurri, and A. Hyvärinen, “Spatial dependencies between local luminance and contrast in natural images,” J. Vision 8, 1–13 (2008).
[CrossRef]

C. Baker, A. Yoonessi, and E. O. Arsenault, “Texture segmentation in natural images: contribution of higher-order image statistics to psychophysical performance,” J. Vision 8, 350 (2008).
[CrossRef]

K. Knoblauch and L. T. Maloney, “MLDS: maximum likelihood difference scaling in R,” J. Stat. Software 25, 1–26 (2008).

A. Yoonessi and F. A. A. Kingdom, “Comparison of sensitivity to color changes in natural and phase-scrambled scenes,” Vision Res. 25, 676–684 (2008).

2007

A. Perna and M. Morrone, “The lowest spatial frequency channel determines brightness perception,” Vision Res. 47, 1282–1291 (2007).
[CrossRef] [PubMed]

C. Charrier, L. Maloney, H. Cherifi, and K. Knoblauch, “Maximum likelihood difference scaling of image quality in compression-degraded images,” J. Opt. Soc. Am. A 24, 3418–3426 (2007).
[CrossRef]

B. C. Hansen and R. F. Hess, “Structural sparseness and spatial phase alignment in natural scenes,” J. Opt. Soc. Am. A 24, 1873–1885 (2007).
[CrossRef]

E. J. Kelman, R. J. Baddeley, A. J. Shohet, and D. Osorio, “Perception of visual texture and the expression of disruptive camouflage by the cuttlefish, sepia officinalis,” Proc. R. Soc. London, Ser. B 274, 1369–1375 (2007).
[CrossRef]

2006

W. Einhäuser, U. Rutishauser, E. P. Frady, S. Nadler, P. Kőnig, and C. Koch, “The relation of phase noise and luminance contrast to overt attention in complex visual stimuli,” J. Vision 6, 1148–1158 (2006).
[CrossRef]

F. A. Wichmann, D. I. Braun, and K. R. Gegenfurtner, “Phase noise and the classification of natural images,” Vision Res. 46, 1520–1529 (2006).
[CrossRef]

2005

V. Mante, R. A. Frazor, V. Bonin, W. S. Geisler, and M. Carandini, “Independence of luminance and contrast in natural scenes and in the early visual system,” Nat. Neurosci. 8, 1690–1697 (2005).
[CrossRef] [PubMed]

G. S. Hesse and M. A. Georgeson, “Edges and bars: where do people see features in 1-D images?” Vision Res. 45, 507–525 (2005).
[CrossRef]

M. J. Chantler, M. Petrou, A. Penirschke, M. Schmidt, and G. McGunnigle, “Classifying surface texture while simultaneously estimating illumination,” Int. J. Comput. Vis. 62, 83–96 (2005).

M. O. Franz and B. Schőlkopf, “Implicit Wiener series for higher-order image analysis,” in Advances in Neural Information Processing Systems, L.K.Saul, Y.Weiss, and L.Bottou, eds. (MIT, 2005), Vol. 17, pp. 465–472.

2004

C. W. Tyler, “Theory of texture discrimination of based on higher-order perturbations in individual texture samples,” Vision Res. 44, 2179–2186 (2004).
[CrossRef] [PubMed]

C. W. Tyler, “Beyond fourth-order texture discrimination: generation of extreme-order and statistically-balanced textures,” Vision Res. 44, 2187–2199 (2004).
[CrossRef] [PubMed]

M. S. Landy and N. Graham, “Visual perception of texture,” in The Visual Neurosciences, L.M.Chalupa and J.S.Werner, eds. (MIT, 2004), pp. 1106–1118.

A. P. Johnson and C. L. Baker, Jr., “First- and second-order information in natural images: a filter-based approach to image statistics,” J. Opt. Soc. Am. A 21, 913–925 (2004).
[CrossRef]

G. Obein, K. Knoblauch, and F. Viénot, “Difference scaling of gloss: nonlinearity, binocularity, and constancy,” J. Vision 4, 711–720 (2004).
[CrossRef]

C. Chubb, M. S. Landy, and J. Econopouly, “A visual mechanism tuned to black,” Vision Res. 44, 3223–3232 (2004).
[CrossRef] [PubMed]

2003

L. T. Maloney and J. N. Yang, “Maximum likelihood difference scaling,” J. Vision 3, 573–585 (2003).
[CrossRef]

2002

P. Kovesi, “Edges are not just steps,” in Proceedings of the ACCV2002 (2002), pp. 822–827.

2000

C. Chubb and J. I. Yellott, “Every discrete, finite image is uniquely determined by its dipole histogram,” Vision Res. 40, 485–492 (2000).
[CrossRef] [PubMed]

P. Kovesi, “Phase congruency: a low-level image invariant,” Psychol. Res. 64, 136–148 (2000).
[CrossRef]

M. 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).
[CrossRef]

1999

T. Randen and J. H. Husøy, “Filtering for texture classification: a comparative study,” IEEE Trans. Pattern Anal. Mach. Intell. 21, 291–310 (1999).
[CrossRef]

I. Mareschal and C. L. Baker, “Cortical processing of second-order motion,” Visual Neurosci. 16, 527–540 (1999).
[CrossRef]

1998

I. Mareschal and C. L. Baker, “A cortical locus for the processing of contrast-defined contours,” Nat. Neurosci. 1, 150–154 (1998).
[CrossRef]

1997

1996

J. D. Victor and M. M. Conte, “The role of high-order phase correlations in texture processing,” Vision Res. 36, 1615–1631 (1996).
[CrossRef] [PubMed]

1995

T. E. Hall and G. B. Giannakis, “Bispectral analysis and model validation of texture images,” IEEE Trans. Image Process. 4, 996–1009 (1995).
[CrossRef] [PubMed]

1994

1993

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).
[CrossRef]

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).
[CrossRef] [PubMed]

1992

M. K. Tsatsanis and G. B. Giannakis, “Object and texture classification using higher order statistics,” IEEE Trans. Pattern Anal. Mach. Intell. 14, 733–750 (1992).
[CrossRef]

1990

1989

D. J. Field, “What the statistics of natural images tell us about visual coding,” in Human Vision, Visual Processing and Digital Display, Proc. SPIE 1077, 269–276 (1989).

1988

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).
[CrossRef]

1987

1982

L. N. Piotrowski and F. Campbell, “A demonstration of the visual importance and flexibility of spatial-frequency amplitude and phase,” Perception 11, 337–346 (1982).
[CrossRef] [PubMed]

1981

A. V. Oppenheim and J. Lim, “The importance of phase in signals,” Proc. IEEE 69, 529–541(1981).
[CrossRef]

B. Julesz, “A theory of preattentive texture discrimination based on first-order statistics of textons,” Biol. Cybern. 41, 131–138 (1981).
[CrossRef] [PubMed]

1980

B. Julesz, “Spatial nonlinearities in the instantaneous perception of textures with identical power spectra,” Philos. Trans. R. Soc. London, Ser. B 290, 83–94 (1980).
[CrossRef] [PubMed]

1979

1978

B. Julesz, “Visual discrimination of textures with identical third-order statistics,” Biol. Cybern. 31, 137–140 (1978).
[CrossRef] [PubMed]

1974

D. M. Green and J. A. Swets, Signal Detection Theory and Psychophysics (Wiley, 1974).

Arsenault, E. O.

C. Baker, A. Yoonessi, and E. O. Arsenault, “Texture segmentation in natural images: contribution of higher-order image statistics to psychophysical performance,” J. Vision 8, 350 (2008).
[CrossRef]

Baddeley, R. J.

E. J. Kelman, R. J. Baddeley, A. J. Shohet, and D. Osorio, “Perception of visual texture and the expression of disruptive camouflage by the cuttlefish, sepia officinalis,” Proc. R. Soc. London, Ser. B 274, 1369–1375 (2007).
[CrossRef]

Baker, C.

C. Baker, A. Yoonessi, and E. O. Arsenault, “Texture segmentation in natural images: contribution of higher-order image statistics to psychophysical performance,” J. Vision 8, 350 (2008).
[CrossRef]

Baker, C. L.

A. P. Johnson and C. L. Baker, Jr., “First- and second-order information in natural images: a filter-based approach to image statistics,” J. Opt. Soc. Am. A 21, 913–925 (2004).
[CrossRef]

I. Mareschal and C. L. Baker, “Cortical processing of second-order motion,” Visual Neurosci. 16, 527–540 (1999).
[CrossRef]

I. Mareschal and C. L. Baker, “A cortical locus for the processing of contrast-defined contours,” Nat. Neurosci. 1, 150–154 (1998).
[CrossRef]

Bonin, V.

V. Mante, R. A. Frazor, V. Bonin, W. S. Geisler, and M. Carandini, “Independence of luminance and contrast in natural scenes and in the early visual system,” Nat. Neurosci. 8, 1690–1697 (2005).
[CrossRef] [PubMed]

Braun, D. I.

F. A. Wichmann, D. I. Braun, and K. R. Gegenfurtner, “Phase noise and the classification of natural images,” Vision Res. 46, 1520–1529 (2006).
[CrossRef]

Burr, D. C.

M. C. Morrone and D. C. Burr, “Capture and transparency in coarse quantized images,” Vision Res. 37, 2609–2629 (1997).
[CrossRef] [PubMed]

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).
[CrossRef]

Caelli, T.

Campbell, F.

L. N. Piotrowski and F. Campbell, “A demonstration of the visual importance and flexibility of spatial-frequency amplitude and phase,” Perception 11, 337–346 (1982).
[CrossRef] [PubMed]

Carandini, M.

V. Mante, R. A. Frazor, V. Bonin, W. S. Geisler, and M. Carandini, “Independence of luminance and contrast in natural scenes and in the early visual system,” Nat. Neurosci. 8, 1690–1697 (2005).
[CrossRef] [PubMed]

Chantler, M. J.

S. Padilla, O. Drbohlav, P. R. Green, A. D. Spence, and M. J. Chantler, “Perceived roughness of 1/fbeta noise surfaces,” Vision Res. 48, 1791–1797 (2008).
[CrossRef] [PubMed]

M. J. Chantler, M. Petrou, A. Penirschke, M. Schmidt, and G. McGunnigle, “Classifying surface texture while simultaneously estimating illumination,” Int. J. Comput. Vis. 62, 83–96 (2005).

Charrier, C.

Cherifi, H.

Chubb, C.

C. Chubb, M. S. Landy, and J. Econopouly, “A visual mechanism tuned to black,” Vision Res. 44, 3223–3232 (2004).
[CrossRef] [PubMed]

C. Chubb and J. I. Yellott, “Every discrete, finite image is uniquely determined by its dipole histogram,” Vision Res. 40, 485–492 (2000).
[CrossRef] [PubMed]

C. Chubb, J. Econopouly, and M. S. Landy, “Histogram contrast analysis and the visual segregation of IID textures,” J. Opt. Soc. Am. A 11, 2350–2374 (1994).
[CrossRef]

Conte, M. M.

J. D. Victor and M. M. Conte, “The role of high-order phase correlations in texture processing,” Vision Res. 36, 1615–1631 (1996).
[CrossRef] [PubMed]

Drbohlav, O.

S. Padilla, O. Drbohlav, P. R. Green, A. D. Spence, and M. J. Chantler, “Perceived roughness of 1/fbeta noise surfaces,” Vision Res. 48, 1791–1797 (2008).
[CrossRef] [PubMed]

Econopouly, J.

Einhäuser, W.

W. Einhäuser, U. Rutishauser, E. P. Frady, S. Nadler, P. Kőnig, and C. Koch, “The relation of phase noise and luminance contrast to overt attention in complex visual stimuli,” J. Vision 6, 1148–1158 (2006).
[CrossRef]

Fabre-Thorpe, M.

O. R. Joubert, G. A. Rousselet, M. Fabre-Thorpe, and D. Fize, “Rapid visual categorization of natural scene contexts with equalized amplitude spectrum and increasing phase noise,” J. Vision 9, 1–16 (2009).
[CrossRef]

Field, D.

Field, D. J.

D. J. Field, “What the statistics of natural images tell us about visual coding,” in Human Vision, Visual Processing and Digital Display, Proc. SPIE 1077, 269–276 (1989).

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]

Fize, D.

O. R. Joubert, G. A. Rousselet, M. Fabre-Thorpe, and D. Fize, “Rapid visual categorization of natural scene contexts with equalized amplitude spectrum and increasing phase noise,” J. Vision 9, 1–16 (2009).
[CrossRef]

Foster, D. H.

M. 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).
[CrossRef]

M. A. Thomson and D. H. Foster, “Role of second- and third-order statistics in the discriminability of natural images,” J. Opt. Soc. Am. A 14, 2081–2090 (1997).
[CrossRef]

Frady, E. P.

W. Einhäuser, U. Rutishauser, E. P. Frady, S. Nadler, P. Kőnig, and C. Koch, “The relation of phase noise and luminance contrast to overt attention in complex visual stimuli,” J. Vision 6, 1148–1158 (2006).
[CrossRef]

Franz, M. O.

M. O. Franz and B. Schőlkopf, “Implicit Wiener series for higher-order image analysis,” in Advances in Neural Information Processing Systems, L.K.Saul, Y.Weiss, and L.Bottou, eds. (MIT, 2005), Vol. 17, pp. 465–472.

Frazor, R. A.

V. Mante, R. A. Frazor, V. Bonin, W. S. Geisler, and M. Carandini, “Independence of luminance and contrast in natural scenes and in the early visual system,” Nat. Neurosci. 8, 1690–1697 (2005).
[CrossRef] [PubMed]

Gegenfurtner, K. R.

F. A. Wichmann, D. I. Braun, and K. R. Gegenfurtner, “Phase noise and the classification of natural images,” Vision Res. 46, 1520–1529 (2006).
[CrossRef]

Geisler, W. S.

V. Mante, R. A. Frazor, V. Bonin, W. S. Geisler, and M. Carandini, “Independence of luminance and contrast in natural scenes and in the early visual system,” Nat. Neurosci. 8, 1690–1697 (2005).
[CrossRef] [PubMed]

Georgeson, M. A.

G. S. Hesse and M. A. Georgeson, “Edges and bars: where do people see features in 1-D images?” Vision Res. 45, 507–525 (2005).
[CrossRef]

Giannakis, G. B.

T. E. Hall and G. B. Giannakis, “Bispectral analysis and model validation of texture images,” IEEE Trans. Image Process. 4, 996–1009 (1995).
[CrossRef] [PubMed]

M. K. Tsatsanis and G. B. Giannakis, “Object and texture classification using higher order statistics,” IEEE Trans. Pattern Anal. Mach. Intell. 14, 733–750 (1992).
[CrossRef]

Graham, N.

M. S. Landy and N. Graham, “Visual perception of texture,” in The Visual Neurosciences, L.M.Chalupa and J.S.Werner, eds. (MIT, 2004), pp. 1106–1118.

Green, D. M.

D. M. Green and J. A. Swets, Signal Detection Theory and Psychophysics (Wiley, 1974).

Green, P. R.

S. Padilla, O. Drbohlav, P. R. Green, A. D. Spence, and M. J. Chantler, “Perceived roughness of 1/fbeta noise surfaces,” Vision Res. 48, 1791–1797 (2008).
[CrossRef] [PubMed]

Hall, T. E.

T. E. Hall and G. B. Giannakis, “Bispectral analysis and model validation of texture images,” IEEE Trans. Image Process. 4, 996–1009 (1995).
[CrossRef] [PubMed]

Hansen, B. C.

Hess, R. F.

Hesse, G. S.

G. S. Hesse and M. A. Georgeson, “Edges and bars: where do people see features in 1-D images?” Vision Res. 45, 507–525 (2005).
[CrossRef]

Hurri, J.

J. T. Lindgren, J. Hurri, and A. Hyvärinen, “Spatial dependencies between local luminance and contrast in natural images,” J. Vision 8, 1–13 (2008).
[CrossRef]

Husøy, J. H.

T. Randen and J. H. Husøy, “Filtering for texture classification: a comparative study,” IEEE Trans. Pattern Anal. Mach. Intell. 21, 291–310 (1999).
[CrossRef]

Hyvärinen, A.

J. T. Lindgren, J. Hurri, and A. Hyvärinen, “Spatial dependencies between local luminance and contrast in natural images,” J. Vision 8, 1–13 (2008).
[CrossRef]

Johnson, A. P.

Joubert, O. R.

O. R. Joubert, G. A. Rousselet, M. Fabre-Thorpe, and D. Fize, “Rapid visual categorization of natural scene contexts with equalized amplitude spectrum and increasing phase noise,” J. Vision 9, 1–16 (2009).
[CrossRef]

Julesz, B.

B. Julesz, “A theory of preattentive texture discrimination based on first-order statistics of textons,” Biol. Cybern. 41, 131–138 (1981).
[CrossRef] [PubMed]

B. Julesz, “Spatial nonlinearities in the instantaneous perception of textures with identical power spectra,” Philos. Trans. R. Soc. London, Ser. B 290, 83–94 (1980).
[CrossRef] [PubMed]

T. Caelli and B. Julesz, “Psychophysical evidence for global feature processing in visual texture discrimination,” J. Opt. Soc. Am. 69, 675–678 (1979).
[CrossRef] [PubMed]

B. Julesz, “Visual discrimination of textures with identical third-order statistics,” Biol. Cybern. 31, 137–140 (1978).
[CrossRef] [PubMed]

Kelman, E. J.

E. J. Kelman, R. J. Baddeley, A. J. Shohet, and D. Osorio, “Perception of visual texture and the expression of disruptive camouflage by the cuttlefish, sepia officinalis,” Proc. R. Soc. London, Ser. B 274, 1369–1375 (2007).
[CrossRef]

Kersten, D.

Kingdom, F. A. A.

A. Yoonessi and F. A. A. Kingdom, “Comparison of sensitivity to color changes in natural and phase-scrambled scenes,” Vision Res. 25, 676–684 (2008).

Knill, D. C.

Knoblauch, K.

K. Knoblauch and L. T. Maloney, “MLDS: maximum likelihood difference scaling in R,” J. Stat. Software 25, 1–26 (2008).

C. Charrier, L. Maloney, H. Cherifi, and K. Knoblauch, “Maximum likelihood difference scaling of image quality in compression-degraded images,” J. Opt. Soc. Am. A 24, 3418–3426 (2007).
[CrossRef]

G. Obein, K. Knoblauch, and F. Viénot, “Difference scaling of gloss: nonlinearity, binocularity, and constancy,” J. Vision 4, 711–720 (2004).
[CrossRef]

Koch, C.

W. Einhäuser, U. Rutishauser, E. P. Frady, S. Nadler, P. Kőnig, and C. Koch, “The relation of phase noise and luminance contrast to overt attention in complex visual stimuli,” J. Vision 6, 1148–1158 (2006).
[CrossRef]

Konig, P.

W. Einhäuser, U. Rutishauser, E. P. Frady, S. Nadler, P. Kőnig, and C. Koch, “The relation of phase noise and luminance contrast to overt attention in complex visual stimuli,” J. Vision 6, 1148–1158 (2006).
[CrossRef]

Kovesi, P.

P. Kovesi, “Edges are not just steps,” in Proceedings of the ACCV2002 (2002), pp. 822–827.

P. Kovesi, “Phase congruency: a low-level image invariant,” Psychol. Res. 64, 136–148 (2000).
[CrossRef]

Landy, M. S.

M. S. Landy and N. Graham, “Visual perception of texture,” in The Visual Neurosciences, L.M.Chalupa and J.S.Werner, eds. (MIT, 2004), pp. 1106–1118.

C. Chubb, M. S. Landy, and J. Econopouly, “A visual mechanism tuned to black,” Vision Res. 44, 3223–3232 (2004).
[CrossRef] [PubMed]

C. Chubb, J. Econopouly, and M. S. Landy, “Histogram contrast analysis and the visual segregation of IID textures,” J. Opt. Soc. Am. A 11, 2350–2374 (1994).
[CrossRef]

Lim, J.

A. V. Oppenheim and J. Lim, “The importance of phase in signals,” Proc. IEEE 69, 529–541(1981).
[CrossRef]

Lindgren, J. T.

J. T. Lindgren, J. Hurri, and A. Hyvärinen, “Spatial dependencies between local luminance and contrast in natural images,” J. Vision 8, 1–13 (2008).
[CrossRef]

Malik, J.

J. Malik and P. Perona, “Preattentive texture discrimination with early vision mechanisms,” J. Opt. Soc. Am. A 7, 923–932 (1990).
[CrossRef] [PubMed]

P. Perona and J. Malik, “Detecting and localizing edges composed of steps, peaks and roofs,” in Proceedings of the ICCV (1990), pp. 52–57.

Maloney, L.

Maloney, L. T.

K. Knoblauch and L. T. Maloney, “MLDS: maximum likelihood difference scaling in R,” J. Stat. Software 25, 1–26 (2008).

L. T. Maloney and J. N. Yang, “Maximum likelihood difference scaling,” J. Vision 3, 573–585 (2003).
[CrossRef]

Mante, V.

V. Mante, R. A. Frazor, V. Bonin, W. S. Geisler, and M. Carandini, “Independence of luminance and contrast in natural scenes and in the early visual system,” Nat. Neurosci. 8, 1690–1697 (2005).
[CrossRef] [PubMed]

Mareschal, I.

I. Mareschal and C. L. Baker, “Cortical processing of second-order motion,” Visual Neurosci. 16, 527–540 (1999).
[CrossRef]

I. Mareschal and C. L. Baker, “A cortical locus for the processing of contrast-defined contours,” Nat. Neurosci. 1, 150–154 (1998).
[CrossRef]

McGunnigle, G.

M. J. Chantler, M. Petrou, A. Penirschke, M. Schmidt, and G. McGunnigle, “Classifying surface texture while simultaneously estimating illumination,” Int. J. Comput. Vis. 62, 83–96 (2005).

Morrone, M.

A. Perna and M. Morrone, “The lowest spatial frequency channel determines brightness perception,” Vision Res. 47, 1282–1291 (2007).
[CrossRef] [PubMed]

Morrone, M. C.

M. C. Morrone and D. C. Burr, “Capture and transparency in coarse quantized images,” Vision Res. 37, 2609–2629 (1997).
[CrossRef] [PubMed]

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).
[CrossRef]

Nadler, S.

W. Einhäuser, U. Rutishauser, E. P. Frady, S. Nadler, P. Kőnig, and C. Koch, “The relation of phase noise and luminance contrast to overt attention in complex visual stimuli,” J. Vision 6, 1148–1158 (2006).
[CrossRef]

Obein, G.

G. Obein, K. Knoblauch, and F. Viénot, “Difference scaling of gloss: nonlinearity, binocularity, and constancy,” J. Vision 4, 711–720 (2004).
[CrossRef]

Oppenheim, A. V.

A. V. Oppenheim and J. Lim, “The importance of phase in signals,” Proc. IEEE 69, 529–541(1981).
[CrossRef]

Osorio, D.

E. J. Kelman, R. J. Baddeley, A. J. Shohet, and D. Osorio, “Perception of visual texture and the expression of disruptive camouflage by the cuttlefish, sepia officinalis,” Proc. R. Soc. London, Ser. B 274, 1369–1375 (2007).
[CrossRef]

Padilla, S.

S. Padilla, O. Drbohlav, P. R. Green, A. D. Spence, and M. J. Chantler, “Perceived roughness of 1/fbeta noise surfaces,” Vision Res. 48, 1791–1797 (2008).
[CrossRef] [PubMed]

Penirschke, A.

M. J. Chantler, M. Petrou, A. Penirschke, M. Schmidt, and G. McGunnigle, “Classifying surface texture while simultaneously estimating illumination,” Int. J. Comput. Vis. 62, 83–96 (2005).

Perna, A.

A. Perna and M. Morrone, “The lowest spatial frequency channel determines brightness perception,” Vision Res. 47, 1282–1291 (2007).
[CrossRef] [PubMed]

Perona, P.

P. Perona and J. Malik, “Detecting and localizing edges composed of steps, peaks and roofs,” in Proceedings of the ICCV (1990), pp. 52–57.

J. Malik and P. Perona, “Preattentive texture discrimination with early vision mechanisms,” J. Opt. Soc. Am. A 7, 923–932 (1990).
[CrossRef] [PubMed]

Petrou, M.

M. J. Chantler, M. Petrou, A. Penirschke, M. Schmidt, and G. McGunnigle, “Classifying surface texture while simultaneously estimating illumination,” Int. J. Comput. Vis. 62, 83–96 (2005).

Piotrowski, L. N.

L. N. Piotrowski and F. Campbell, “A demonstration of the visual importance and flexibility of spatial-frequency amplitude and phase,” Perception 11, 337–346 (1982).
[CrossRef] [PubMed]

Randen, T.

T. Randen and J. H. Husøy, “Filtering for texture classification: a comparative study,” IEEE Trans. Pattern Anal. Mach. Intell. 21, 291–310 (1999).
[CrossRef]

Rousselet, G. A.

O. R. Joubert, G. A. Rousselet, M. Fabre-Thorpe, and D. Fize, “Rapid visual categorization of natural scene contexts with equalized amplitude spectrum and increasing phase noise,” J. Vision 9, 1–16 (2009).
[CrossRef]

Rutishauser, U.

W. Einhäuser, U. Rutishauser, E. P. Frady, S. Nadler, P. Kőnig, and C. Koch, “The relation of phase noise and luminance contrast to overt attention in complex visual stimuli,” J. Vision 6, 1148–1158 (2006).
[CrossRef]

Schmidt, M.

M. J. Chantler, M. Petrou, A. Penirschke, M. Schmidt, and G. McGunnigle, “Classifying surface texture while simultaneously estimating illumination,” Int. J. Comput. Vis. 62, 83–96 (2005).

Scholkopf, B.

M. O. Franz and B. Schőlkopf, “Implicit Wiener series for higher-order image analysis,” in Advances in Neural Information Processing Systems, L.K.Saul, Y.Weiss, and L.Bottou, eds. (MIT, 2005), Vol. 17, pp. 465–472.

Shohet, A. J.

E. J. Kelman, R. J. Baddeley, A. J. Shohet, and D. Osorio, “Perception of visual texture and the expression of disruptive camouflage by the cuttlefish, sepia officinalis,” Proc. R. Soc. London, Ser. B 274, 1369–1375 (2007).
[CrossRef]

Spence, A. D.

S. Padilla, O. Drbohlav, P. R. Green, A. D. Spence, and M. J. Chantler, “Perceived roughness of 1/fbeta noise surfaces,” Vision Res. 48, 1791–1797 (2008).
[CrossRef] [PubMed]

Summers, R. J.

M. 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).
[CrossRef]

Swets, J. A.

D. M. Green and J. A. Swets, Signal Detection Theory and Psychophysics (Wiley, 1974).

Tadmor, Y.

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).
[CrossRef] [PubMed]

Thomson, M. A.

M. 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).
[CrossRef]

M. A. Thomson and D. H. Foster, “Role of second- and third-order statistics in the discriminability of natural images,” J. Opt. Soc. Am. A 14, 2081–2090 (1997).
[CrossRef]

Tolhurst, D. J.

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).
[CrossRef] [PubMed]

Tsatsanis, M. K.

M. K. Tsatsanis and G. B. Giannakis, “Object and texture classification using higher order statistics,” IEEE Trans. Pattern Anal. Mach. Intell. 14, 733–750 (1992).
[CrossRef]

Tyler, C. W.

C. W. Tyler, “Theory of texture discrimination of based on higher-order perturbations in individual texture samples,” Vision Res. 44, 2179–2186 (2004).
[CrossRef] [PubMed]

C. W. Tyler, “Beyond fourth-order texture discrimination: generation of extreme-order and statistically-balanced textures,” Vision Res. 44, 2187–2199 (2004).
[CrossRef] [PubMed]

Victor, J. D.

Viénot, F.

G. Obein, K. Knoblauch, and F. Viénot, “Difference scaling of gloss: nonlinearity, binocularity, and constancy,” J. Vision 4, 711–720 (2004).
[CrossRef]

Wichmann, F. A.

F. A. Wichmann, D. I. Braun, and K. R. Gegenfurtner, “Phase noise and the classification of natural images,” Vision Res. 46, 1520–1529 (2006).
[CrossRef]

Yang, J. N.

L. T. Maloney and J. N. Yang, “Maximum likelihood difference scaling,” J. Vision 3, 573–585 (2003).
[CrossRef]

Yellott, J. I.

C. Chubb and J. I. Yellott, “Every discrete, finite image is uniquely determined by its dipole histogram,” Vision Res. 40, 485–492 (2000).
[CrossRef] [PubMed]

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).
[CrossRef]

Yoonessi, A.

A. Yoonessi and F. A. A. Kingdom, “Comparison of sensitivity to color changes in natural and phase-scrambled scenes,” Vision Res. 25, 676–684 (2008).

C. Baker, A. Yoonessi, and E. O. Arsenault, “Texture segmentation in natural images: contribution of higher-order image statistics to psychophysical performance,” J. Vision 8, 350 (2008).
[CrossRef]

Biol. Cybern.

B. Julesz, “Visual discrimination of textures with identical third-order statistics,” Biol. Cybern. 31, 137–140 (1978).
[CrossRef] [PubMed]

B. Julesz, “A theory of preattentive texture discrimination based on first-order statistics of textons,” Biol. Cybern. 41, 131–138 (1981).
[CrossRef] [PubMed]

IEEE Trans. Image Process.

T. E. Hall and G. B. Giannakis, “Bispectral analysis and model validation of texture images,” IEEE Trans. Image Process. 4, 996–1009 (1995).
[CrossRef] [PubMed]

IEEE Trans. Pattern Anal. Mach. Intell.

M. K. Tsatsanis and G. B. Giannakis, “Object and texture classification using higher order statistics,” IEEE Trans. Pattern Anal. Mach. Intell. 14, 733–750 (1992).
[CrossRef]

T. Randen and J. H. Husøy, “Filtering for texture classification: a comparative study,” IEEE Trans. Pattern Anal. Mach. Intell. 21, 291–310 (1999).
[CrossRef]

Int. J. Comput. Vis.

M. J. Chantler, M. Petrou, A. Penirschke, M. Schmidt, and G. McGunnigle, “Classifying surface texture while simultaneously estimating illumination,” Int. J. Comput. Vis. 62, 83–96 (2005).

J. Opt. Soc. Am.

J. Opt. Soc. Am. A

J. Malik and P. Perona, “Preattentive texture discrimination with early vision mechanisms,” J. Opt. Soc. Am. A 7, 923–932 (1990).
[CrossRef] [PubMed]

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).
[CrossRef]

C. Chubb, J. Econopouly, and M. S. Landy, “Histogram contrast analysis and the visual segregation of IID textures,” J. Opt. Soc. Am. A 11, 2350–2374 (1994).
[CrossRef]

J. D. Victor, “Images, statistics and textures: implications of triple correlation uniqueness for texture statistics and the Julesz conjecture: comment,” J. Opt. Soc. Am. A 11, 1680–1684 (1994).
[CrossRef]

A. P. Johnson and C. L. Baker, Jr., “First- and second-order information in natural images: a filter-based approach to image statistics,” J. Opt. Soc. Am. A 21, 913–925 (2004).
[CrossRef]

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]

D. C. Knill, D. Field, and D. Kersten, “Human discrimination of fractal images,” J. Opt. Soc. Am. A 7, 1113–1123 (1990).
[CrossRef] [PubMed]

M. A. Thomson and D. H. Foster, “Role of second- and third-order statistics in the discriminability of natural images,” J. Opt. Soc. Am. A 14, 2081–2090 (1997).
[CrossRef]

B. C. Hansen and R. F. Hess, “Structural sparseness and spatial phase alignment in natural scenes,” J. Opt. Soc. Am. A 24, 1873–1885 (2007).
[CrossRef]

C. Charrier, L. Maloney, H. Cherifi, and K. Knoblauch, “Maximum likelihood difference scaling of image quality in compression-degraded images,” J. Opt. Soc. Am. A 24, 3418–3426 (2007).
[CrossRef]

J. Stat. Software

K. Knoblauch and L. T. Maloney, “MLDS: maximum likelihood difference scaling in R,” J. Stat. Software 25, 1–26 (2008).

J. Vision

G. Obein, K. Knoblauch, and F. Viénot, “Difference scaling of gloss: nonlinearity, binocularity, and constancy,” J. Vision 4, 711–720 (2004).
[CrossRef]

L. T. Maloney and J. N. Yang, “Maximum likelihood difference scaling,” J. Vision 3, 573–585 (2003).
[CrossRef]

O. R. Joubert, G. A. Rousselet, M. Fabre-Thorpe, and D. Fize, “Rapid visual categorization of natural scene contexts with equalized amplitude spectrum and increasing phase noise,” J. Vision 9, 1–16 (2009).
[CrossRef]

J. T. Lindgren, J. Hurri, and A. Hyvärinen, “Spatial dependencies between local luminance and contrast in natural images,” J. Vision 8, 1–13 (2008).
[CrossRef]

C. Baker, A. Yoonessi, and E. O. Arsenault, “Texture segmentation in natural images: contribution of higher-order image statistics to psychophysical performance,” J. Vision 8, 350 (2008).
[CrossRef]

W. Einhäuser, U. Rutishauser, E. P. Frady, S. Nadler, P. Kőnig, and C. Koch, “The relation of phase noise and luminance contrast to overt attention in complex visual stimuli,” J. Vision 6, 1148–1158 (2006).
[CrossRef]

Nat. Neurosci.

I. Mareschal and C. L. Baker, “A cortical locus for the processing of contrast-defined contours,” Nat. Neurosci. 1, 150–154 (1998).
[CrossRef]

V. Mante, R. A. Frazor, V. Bonin, W. S. Geisler, and M. Carandini, “Independence of luminance and contrast in natural scenes and in the early visual system,” Nat. Neurosci. 8, 1690–1697 (2005).
[CrossRef] [PubMed]

Perception

M. 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).
[CrossRef]

L. N. Piotrowski and F. Campbell, “A demonstration of the visual importance and flexibility of spatial-frequency amplitude and phase,” Perception 11, 337–346 (1982).
[CrossRef] [PubMed]

Philos. Trans. R. Soc. London, Ser. B

B. Julesz, “Spatial nonlinearities in the instantaneous perception of textures with identical power spectra,” Philos. Trans. R. Soc. London, Ser. B 290, 83–94 (1980).
[CrossRef] [PubMed]

Proc. IEEE

A. V. Oppenheim and J. Lim, “The importance of phase in signals,” Proc. IEEE 69, 529–541(1981).
[CrossRef]

Proc. R. Soc. London, Ser. B

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).
[CrossRef]

E. J. Kelman, R. J. Baddeley, A. J. Shohet, and D. Osorio, “Perception of visual texture and the expression of disruptive camouflage by the cuttlefish, sepia officinalis,” Proc. R. Soc. London, Ser. B 274, 1369–1375 (2007).
[CrossRef]

Proc. SPIE

D. J. Field, “What the statistics of natural images tell us about visual coding,” in Human Vision, Visual Processing and Digital Display, Proc. SPIE 1077, 269–276 (1989).

Psychol. Res.

P. Kovesi, “Phase congruency: a low-level image invariant,” Psychol. Res. 64, 136–148 (2000).
[CrossRef]

Vision Res.

F. A. Wichmann, D. I. Braun, and K. R. Gegenfurtner, “Phase noise and the classification of natural images,” Vision Res. 46, 1520–1529 (2006).
[CrossRef]

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).
[CrossRef] [PubMed]

J. D. Victor and M. M. Conte, “The role of high-order phase correlations in texture processing,” Vision Res. 36, 1615–1631 (1996).
[CrossRef] [PubMed]

C. Chubb and J. I. Yellott, “Every discrete, finite image is uniquely determined by its dipole histogram,” Vision Res. 40, 485–492 (2000).
[CrossRef] [PubMed]

C. W. Tyler, “Theory of texture discrimination of based on higher-order perturbations in individual texture samples,” Vision Res. 44, 2179–2186 (2004).
[CrossRef] [PubMed]

C. W. Tyler, “Beyond fourth-order texture discrimination: generation of extreme-order and statistically-balanced textures,” Vision Res. 44, 2187–2199 (2004).
[CrossRef] [PubMed]

C. Chubb, M. S. Landy, and J. Econopouly, “A visual mechanism tuned to black,” Vision Res. 44, 3223–3232 (2004).
[CrossRef] [PubMed]

G. S. Hesse and M. A. Georgeson, “Edges and bars: where do people see features in 1-D images?” Vision Res. 45, 507–525 (2005).
[CrossRef]

M. C. Morrone and D. C. Burr, “Capture and transparency in coarse quantized images,” Vision Res. 37, 2609–2629 (1997).
[CrossRef] [PubMed]

A. Perna and M. Morrone, “The lowest spatial frequency channel determines brightness perception,” Vision Res. 47, 1282–1291 (2007).
[CrossRef] [PubMed]

S. Padilla, O. Drbohlav, P. R. Green, A. D. Spence, and M. J. Chantler, “Perceived roughness of 1/fbeta noise surfaces,” Vision Res. 48, 1791–1797 (2008).
[CrossRef] [PubMed]

A. Yoonessi and F. A. A. Kingdom, “Comparison of sensitivity to color changes in natural and phase-scrambled scenes,” Vision Res. 25, 676–684 (2008).

Visual Neurosci.

I. Mareschal and C. L. Baker, “Cortical processing of second-order motion,” Visual Neurosci. 16, 527–540 (1999).
[CrossRef]

Other

M. S. Landy and N. Graham, “Visual perception of texture,” in The Visual Neurosciences, L.M.Chalupa and J.S.Werner, eds. (MIT, 2004), pp. 1106–1118.

P. Perona and J. Malik, “Detecting and localizing edges composed of steps, peaks and roofs,” in Proceedings of the ICCV (1990), pp. 52–57.

M. O. Franz and B. Schőlkopf, “Implicit Wiener series for higher-order image analysis,” in Advances in Neural Information Processing Systems, L.K.Saul, Y.Weiss, and L.Bottou, eds. (MIT, 2005), Vol. 17, pp. 465–472.

P. Kovesi, “Edges are not just steps,” in Proceedings of the ACCV2002 (2002), pp. 822–827.

http://www.csse.uwa.edu.au/~pk/Research/MatlabFns/.

D. M. Green and J. A. Swets, Signal Detection Theory and Psychophysics (Wiley, 1974).

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Figures (12)

Fig. 1
Fig. 1

Images used in the psychophysical experiments. Top two rows show the six natural images and the bottom two rows show the six computer synthesized textures.  

Fig. 2
Fig. 2

Example of a natural image whose intensity distribution is mapped to a normal one.

Fig. 3
Fig. 3

Reference textures at different levels of randomization: Blood (top) and seeds (bottom).

Fig. 4
Fig. 4

Effect of full phase randomization on the appearance of a highly periodic texture (left, original; right, randomized).

Fig. 5
Fig. 5

Plots showing the behavior of individual observers’ difference scales with changing amount of phase randomization for synthetic textures blood and RanFrac.

Fig. 6
Fig. 6

Six plots showing the behavior of difference scales with changing amount of phase randomization for natural textures gravel and seeds.

Fig. 7
Fig. 7

Plots showing the behavior of difference scales for a set of four synthetic and four natural textures using only nine randomization levels (0%–80%). Column 1 shows the plots for all textures and column 2 shows the average behavior for four subjects.

Fig. 8
Fig. 8

Phase congruency maps (middle row) for different levels (0%, 30%, 60%, and 100%) of phase randomized blood images (top row) obtained after applying Kovesi’s phase congruency model [30]. Bottom row shows how the edge intensity histogram of each map changes shape when the image is randomized.

Fig. 9
Fig. 9

Behavior of the mean, variance, skewness, and kurtosis of the phase congruency distribution for textures blood, RanFrac, and seeds across the different levels of randomization.

Fig. 10
Fig. 10

Variation in phase congruency variance with changing levels of phase randomization for (a) a texture image generated using random placement of textons at different seeds, (b) six different synthetic textures generated using the same seed, and (c) six different natural textures.

Fig. 11
Fig. 11

Model: A two stage process for computing the higher order statistics measure to account for change in appearance.

Fig. 12
Fig. 12

Linear relationship between perceptual difference and phase congruency variance in a log-log space for (a) synthesized textures blood and RanFrac, and (b) gravel and seeds.

Equations (5)

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

P C o ( x , y ) = W o ( x ) E o ( x , y ) T n A n o ( x , y ) + ϵ ,
δ ( a , b ; c , d ) = | ψ d ψ c | | ψ b ψ a | .
Δ ( a , b ; c , d ) = δ ( a , b ; c , d ) + ϵ = L c d L a b + ϵ ,
Δ ( a , b ; c , d ) > 0.
L ( Ψ , σ ) = k = 1 n Φ ( δ ( q k ) σ ) 1 R k ( 1 Φ ( δ ( q k ) σ ) ) R k ,

Metrics