Abstract

The spatial filtering applied by the human visual system appears to be low pass for chromatic stimuli and band pass for luminance stimuli. Here we explore whether this observed difference in contrast sensitivity reflects a real difference in the components of chrominance and luminance in natural scenes. For this purpose a digital set of 29 hyperspectral images of natural scenes was acquired and its spatial frequency content analyzed in terms of chrominance and luminance defined according to existing models of the human cone responses and visual signal processing. The statistical 1/f amplitude spatial-frequency distribution is confirmed for a variety of chromatic conditions across the visible spectrum. Our analysis suggests that natural scenes are relatively rich in high-spatial-frequency chrominance information that does not appear to be transmitted by the human visual system. This result is unlikely to have arisen from errors in the original measurements. Several reasons may combine to explain a failure to transmit high-spatial-frequency chrominance: (a) its minor importance for primate visual tasks, (b) its removal by filtering applied to compensate for chromatic aberration of the eye’s optics, and (c) a biological bottleneck blocking its transmission. In addition, we graphically compare the ratios of luminance to chrominance measured by our hyperspectral camera and those measured psychophysically over an equivalent spatial-frequency range.

© 1998 Optical Society of America

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References

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    [CrossRef] [PubMed]
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    [CrossRef] [PubMed]
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    [CrossRef]
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    [CrossRef]
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1997

C. Koch, “Computation and the single neuron,” Nature 385, 207–210 (1997).
[CrossRef] [PubMed]

1995

S. M. Courtney, L. H. Finkel, G. Buchsbaum, “A multistage neural network for colour constancy and color induction,” IEEE Trans. Neural Netw. 6, 972–985 (1995).
[CrossRef]

F. A. A. Kingdom, K. T. Mullen, “Separating color and luminance information in the visual system,” Spatial Vis. 9, 191–219 (1995).
[CrossRef]

1994

1993

R. L. De Valois, K. K. De Valois, “A multi-stage color model,” Vision Res. 33, 1053–1065 (1993).
[CrossRef] [PubMed]

1992

J. J. Atick, “Could information theory provide an ecological theory for sensory processing?” Network 3, 231–251 (1992).
[CrossRef]

D. J. Tolhurst, Y. Tadmor, Tang Chao, “Amplitude spectra of natural images,” Ophthalmic. Physiol. Opt. 12, 229–232 (1992).
[CrossRef] [PubMed]

1991

J. B. Derrico, G. Buchsbaum, “A computational model of spatiochromatic image coding in early vision,” J. Visual Commun. Image Represent. 2, 31–37 (1991).
[CrossRef]

1989

J. D. Mollon, “Tho’ she kneel’d in that place where they grew…. The uses and origins of primate colour vision,” J. Exp. Biol. 146, 21–38 (1989).
[PubMed]

1988

1987

1986

1985

K. T. Mullen, “Contrast sensitivity of human color vision to red–green and blue–yellow chromatic gratings,” J. Physiol. (London) 359, 381–400 (1985).

1984

A. M. Derrington, P. Lennie, “Spatial and temporal contrast sensitivities of neurons in lateral geniculate nucleus of macaque,” J. Physiol. (London) 357, 219–240 (1984).

A. M. Derrington, J. Krauskopf, P. Lennie, “Chromatic mechanisms in lateral geniculate nucleus of macaque,” J. Physiol. (London) 357, 241–265 (1984).

1983

G. Buchsbaum, A. Gottschalk, “Trichomacy, opponent color coding and optimum color information transmission in the retina,” Proc. R. Soc. London, Ser. B 220, 80–113 (1983).
[CrossRef]

1982

M. V. Srinivasan, S. B. Laughlin, A. Dubs, “Predicitive coding: a fresh view of inhibition in the retina,” Proc. R. Soc. London, Ser. B 216, 427–459 (1982).
[CrossRef]

1975

C. Smith, J. Pokorny, “Spectral sensitivity of the foveal cone photopigments between 400 and 500 nm,” Vision Res. 15, 161–171 (1975).
[CrossRef] [PubMed]

1974

R. L. De Valois, H. Morhan, D. M. Snodderly, “Psychophysical studies of monkey vision III. Spatial luminance contrast sensitivity tests of macaque and human observers,” Vision Res. 14, 75–81 (1974).
[CrossRef] [PubMed]

Atick, J. J.

J. J. Atick, “Could information theory provide an ecological theory for sensory processing?” Network 3, 231–251 (1992).
[CrossRef]

Barlow, H. B.

H. B. Barlow, “Possible principles underlying the transformation of sensory messages,” in Sensory Communications, W. A. Rosenblith, ed. (MIT Press, Cambridge, Mass., 1961), pp. 217–234.

Berry, M. V.

Brelstaff, G.

G. Brelstaff, A. Párraga, T. Troscianko, D. Carr, “Hyperspectral camera system: acquisition and analysis,” in Geographic Information Systems, Photogrammetry, and Geological/Geophysical Remote Sensing, J. B. Lurie, J. J. Pearson, E. Zillioli, eds., Proc. SPIE2587, 150–159 (1995).
[CrossRef]

G. Brelstaff, T. Troscianko, “Information content of natural scenes: implications for neural coding of color and luminance,” in Human Visual Processing and Digital Display, B. E. Rogowitz, ed., Proc. SPIE1666, 302–309 (1992).
[CrossRef]

Buchsbaum, G.

S. M. Courtney, L. H. Finkel, G. Buchsbaum, “A multistage neural network for colour constancy and color induction,” IEEE Trans. Neural Netw. 6, 972–985 (1995).
[CrossRef]

J. B. Derrico, G. Buchsbaum, “A computational model of spatiochromatic image coding in early vision,” J. Visual Commun. Image Represent. 2, 31–37 (1991).
[CrossRef]

G. Buchsbaum, A. Gottschalk, “Trichomacy, opponent color coding and optimum color information transmission in the retina,” Proc. R. Soc. London, Ser. B 220, 80–113 (1983).
[CrossRef]

Burton, G. J.

Carr, D.

G. Brelstaff, A. Párraga, T. Troscianko, D. Carr, “Hyperspectral camera system: acquisition and analysis,” in Geographic Information Systems, Photogrammetry, and Geological/Geophysical Remote Sensing, J. B. Lurie, J. J. Pearson, E. Zillioli, eds., Proc. SPIE2587, 150–159 (1995).
[CrossRef]

Chao, Tang

D. J. Tolhurst, Y. Tadmor, Tang Chao, “Amplitude spectra of natural images,” Ophthalmic. Physiol. Opt. 12, 229–232 (1992).
[CrossRef] [PubMed]

Courtney, S. M.

S. M. Courtney, L. H. Finkel, G. Buchsbaum, “A multistage neural network for colour constancy and color induction,” IEEE Trans. Neural Netw. 6, 972–985 (1995).
[CrossRef]

D’Zmura, M.

De Valois, K. K.

R. L. De Valois, K. K. De Valois, “A multi-stage color model,” Vision Res. 33, 1053–1065 (1993).
[CrossRef] [PubMed]

De Valois, R. L.

R. L. De Valois, K. K. De Valois, “A multi-stage color model,” Vision Res. 33, 1053–1065 (1993).
[CrossRef] [PubMed]

R. L. De Valois, H. Morhan, D. M. Snodderly, “Psychophysical studies of monkey vision III. Spatial luminance contrast sensitivity tests of macaque and human observers,” Vision Res. 14, 75–81 (1974).
[CrossRef] [PubMed]

Derrico, J. B.

J. B. Derrico, G. Buchsbaum, “A computational model of spatiochromatic image coding in early vision,” J. Visual Commun. Image Represent. 2, 31–37 (1991).
[CrossRef]

Derrington, A. M.

A. M. Derrington, J. Krauskopf, P. Lennie, “Chromatic mechanisms in lateral geniculate nucleus of macaque,” J. Physiol. (London) 357, 241–265 (1984).

A. M. Derrington, P. Lennie, “Spatial and temporal contrast sensitivities of neurons in lateral geniculate nucleus of macaque,” J. Physiol. (London) 357, 219–240 (1984).

Dubs, A.

M. V. Srinivasan, S. B. Laughlin, A. Dubs, “Predicitive coding: a fresh view of inhibition in the retina,” Proc. R. Soc. London, Ser. B 216, 427–459 (1982).
[CrossRef]

Field, D. J.

Finkel, L. H.

S. M. Courtney, L. H. Finkel, G. Buchsbaum, “A multistage neural network for colour constancy and color induction,” IEEE Trans. Neural Netw. 6, 972–985 (1995).
[CrossRef]

Gottschalk, A.

G. Buchsbaum, A. Gottschalk, “Trichomacy, opponent color coding and optimum color information transmission in the retina,” Proc. R. Soc. London, Ser. B 220, 80–113 (1983).
[CrossRef]

Ingling, C. R.

C. R. Ingling, B. H. Tsou, “Spectral sensitivity for flicker and acuity criteria,” J. Opt. Soc. Am. A 5, 1374–1378 (1988).
[CrossRef] [PubMed]

C. R. Ingling, E. Martinez, “The spatiochromatic signal of the r–g channel,” in Color Vision: Physiology and Psychophysics, J. D. Mollon, L. T. Sharpe, eds. (Academic, London, 1983), pp. 433–444.

Kingdom, F. A. A.

F. A. A. Kingdom, K. T. Mullen, “Separating color and luminance information in the visual system,” Spatial Vis. 9, 191–219 (1995).
[CrossRef]

Koch, C.

C. Koch, “Computation and the single neuron,” Nature 385, 207–210 (1997).
[CrossRef] [PubMed]

Krauskopf, J.

A. M. Derrington, J. Krauskopf, P. Lennie, “Chromatic mechanisms in lateral geniculate nucleus of macaque,” J. Physiol. (London) 357, 241–265 (1984).

Laughlin, S. B.

M. V. Srinivasan, S. B. Laughlin, A. Dubs, “Predicitive coding: a fresh view of inhibition in the retina,” Proc. R. Soc. London, Ser. B 216, 427–459 (1982).
[CrossRef]

Le Grand, Y.

Y. Le Grand, Form and Space Vision (translated by Michel Millodot, Gordon G. Heat, Indiana U. Press, Bloomington and London, 1967), pp. 5–35.

Lennie, P.

M. D’Zmura, P. Lennie, “Mechanisms of color constancy,” J. Opt. Soc. Am. A 3, 1662–1672 (1986).
[CrossRef] [PubMed]

A. M. Derrington, J. Krauskopf, P. Lennie, “Chromatic mechanisms in lateral geniculate nucleus of macaque,” J. Physiol. (London) 357, 241–265 (1984).

A. M. Derrington, P. Lennie, “Spatial and temporal contrast sensitivities of neurons in lateral geniculate nucleus of macaque,” J. Physiol. (London) 357, 219–240 (1984).

Martinez, E.

C. R. Ingling, E. Martinez, “The spatiochromatic signal of the r–g channel,” in Color Vision: Physiology and Psychophysics, J. D. Mollon, L. T. Sharpe, eds. (Academic, London, 1983), pp. 433–444.

Mollon, J. D.

J. D. Mollon, “Tho’ she kneel’d in that place where they grew…. The uses and origins of primate colour vision,” J. Exp. Biol. 146, 21–38 (1989).
[PubMed]

Moorhead, I. R.

Morhan, H.

R. L. De Valois, H. Morhan, D. M. Snodderly, “Psychophysical studies of monkey vision III. Spatial luminance contrast sensitivity tests of macaque and human observers,” Vision Res. 14, 75–81 (1974).
[CrossRef] [PubMed]

Mullen, K. T.

F. A. A. Kingdom, K. T. Mullen, “Separating color and luminance information in the visual system,” Spatial Vis. 9, 191–219 (1995).
[CrossRef]

K. T. Mullen, “Contrast sensitivity of human color vision to red–green and blue–yellow chromatic gratings,” J. Physiol. (London) 359, 381–400 (1985).

Párraga, A.

G. Brelstaff, A. Párraga, T. Troscianko, D. Carr, “Hyperspectral camera system: acquisition and analysis,” in Geographic Information Systems, Photogrammetry, and Geological/Geophysical Remote Sensing, J. B. Lurie, J. J. Pearson, E. Zillioli, eds., Proc. SPIE2587, 150–159 (1995).
[CrossRef]

Pokorny, J.

C. Smith, J. Pokorny, “Spectral sensitivity of the foveal cone photopigments between 400 and 500 nm,” Vision Res. 15, 161–171 (1975).
[CrossRef] [PubMed]

Smith, C.

C. Smith, J. Pokorny, “Spectral sensitivity of the foveal cone photopigments between 400 and 500 nm,” Vision Res. 15, 161–171 (1975).
[CrossRef] [PubMed]

Snodderly, D. M.

R. L. De Valois, H. Morhan, D. M. Snodderly, “Psychophysical studies of monkey vision III. Spatial luminance contrast sensitivity tests of macaque and human observers,” Vision Res. 14, 75–81 (1974).
[CrossRef] [PubMed]

Srinivasan, M. V.

M. V. Srinivasan, S. B. Laughlin, A. Dubs, “Predicitive coding: a fresh view of inhibition in the retina,” Proc. R. Soc. London, Ser. B 216, 427–459 (1982).
[CrossRef]

Tadmor, Y.

D. J. Tolhurst, Y. Tadmor, Tang Chao, “Amplitude spectra of natural images,” Ophthalmic. Physiol. Opt. 12, 229–232 (1992).
[CrossRef] [PubMed]

Tolhurst, D. J.

D. J. Tolhurst, Y. Tadmor, Tang Chao, “Amplitude spectra of natural images,” Ophthalmic. Physiol. Opt. 12, 229–232 (1992).
[CrossRef] [PubMed]

Travis, D.

D. Travis, Effective Color Displays (Academic, London, 1991), App. 4, pp. 271–272.

Troscianko, T.

G. Brelstaff, T. Troscianko, “Information content of natural scenes: implications for neural coding of color and luminance,” in Human Visual Processing and Digital Display, B. E. Rogowitz, ed., Proc. SPIE1666, 302–309 (1992).
[CrossRef]

G. Brelstaff, A. Párraga, T. Troscianko, D. Carr, “Hyperspectral camera system: acquisition and analysis,” in Geographic Information Systems, Photogrammetry, and Geological/Geophysical Remote Sensing, J. B. Lurie, J. J. Pearson, E. Zillioli, eds., Proc. SPIE2587, 150–159 (1995).
[CrossRef]

Tsou, B. H.

Wilson, A. N.

Appl. Opt.

IEEE Trans. Neural Netw.

S. M. Courtney, L. H. Finkel, G. Buchsbaum, “A multistage neural network for colour constancy and color induction,” IEEE Trans. Neural Netw. 6, 972–985 (1995).
[CrossRef]

J. Exp. Biol.

J. D. Mollon, “Tho’ she kneel’d in that place where they grew…. The uses and origins of primate colour vision,” J. Exp. Biol. 146, 21–38 (1989).
[PubMed]

J. Opt. Soc. Am. A

J. Physiol. (London)

K. T. Mullen, “Contrast sensitivity of human color vision to red–green and blue–yellow chromatic gratings,” J. Physiol. (London) 359, 381–400 (1985).

A. M. Derrington, P. Lennie, “Spatial and temporal contrast sensitivities of neurons in lateral geniculate nucleus of macaque,” J. Physiol. (London) 357, 219–240 (1984).

A. M. Derrington, J. Krauskopf, P. Lennie, “Chromatic mechanisms in lateral geniculate nucleus of macaque,” J. Physiol. (London) 357, 241–265 (1984).

J. Visual Commun. Image Represent.

J. B. Derrico, G. Buchsbaum, “A computational model of spatiochromatic image coding in early vision,” J. Visual Commun. Image Represent. 2, 31–37 (1991).
[CrossRef]

Nature

C. Koch, “Computation and the single neuron,” Nature 385, 207–210 (1997).
[CrossRef] [PubMed]

Network

J. J. Atick, “Could information theory provide an ecological theory for sensory processing?” Network 3, 231–251 (1992).
[CrossRef]

Ophthalmic. Physiol. Opt.

D. J. Tolhurst, Y. Tadmor, Tang Chao, “Amplitude spectra of natural images,” Ophthalmic. Physiol. Opt. 12, 229–232 (1992).
[CrossRef] [PubMed]

Proc. R. Soc. London, Ser. B

M. V. Srinivasan, S. B. Laughlin, A. Dubs, “Predicitive coding: a fresh view of inhibition in the retina,” Proc. R. Soc. London, Ser. B 216, 427–459 (1982).
[CrossRef]

G. Buchsbaum, A. Gottschalk, “Trichomacy, opponent color coding and optimum color information transmission in the retina,” Proc. R. Soc. London, Ser. B 220, 80–113 (1983).
[CrossRef]

Spatial Vis.

F. A. A. Kingdom, K. T. Mullen, “Separating color and luminance information in the visual system,” Spatial Vis. 9, 191–219 (1995).
[CrossRef]

Vision Res.

C. Smith, J. Pokorny, “Spectral sensitivity of the foveal cone photopigments between 400 and 500 nm,” Vision Res. 15, 161–171 (1975).
[CrossRef] [PubMed]

R. L. De Valois, H. Morhan, D. M. Snodderly, “Psychophysical studies of monkey vision III. Spatial luminance contrast sensitivity tests of macaque and human observers,” Vision Res. 14, 75–81 (1974).
[CrossRef] [PubMed]

R. L. De Valois, K. K. De Valois, “A multi-stage color model,” Vision Res. 33, 1053–1065 (1993).
[CrossRef] [PubMed]

Other

C. R. Ingling, E. Martinez, “The spatiochromatic signal of the r–g channel,” in Color Vision: Physiology and Psychophysics, J. D. Mollon, L. T. Sharpe, eds. (Academic, London, 1983), pp. 433–444.

H. B. Barlow, “Possible principles underlying the transformation of sensory messages,” in Sensory Communications, W. A. Rosenblith, ed. (MIT Press, Cambridge, Mass., 1961), pp. 217–234.

G. Brelstaff, T. Troscianko, “Information content of natural scenes: implications for neural coding of color and luminance,” in Human Visual Processing and Digital Display, B. E. Rogowitz, ed., Proc. SPIE1666, 302–309 (1992).
[CrossRef]

D. Travis, Effective Color Displays (Academic, London, 1991), App. 4, pp. 271–272.

G. Brelstaff, A. Párraga, T. Troscianko, D. Carr, “Hyperspectral camera system: acquisition and analysis,” in Geographic Information Systems, Photogrammetry, and Geological/Geophysical Remote Sensing, J. B. Lurie, J. J. Pearson, E. Zillioli, eds., Proc. SPIE2587, 150–159 (1995).
[CrossRef]

Y. Le Grand, Form and Space Vision (translated by Michel Millodot, Gordon G. Heat, Indiana U. Press, Bloomington and London, 1967), pp. 5–35.

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Figures (10)

Fig. 1
Fig. 1

Example of typical images from our data set.

Fig. 2
Fig. 2

Mean value of the slope (α) across wavelength. Scenes were converted into radiance, and their Fourier amplitude spectra were normalized to 1. Standard error is shown in the plot.

Fig. 3
Fig. 3

Amplitude spectrum (lum) for some scenes of our data set (simple definition).

Fig. 4
Fig. 4

Amplitude spectrum for lum and chrom for all of the data set (29 scenes) (simple definition).

Fig. 5
Fig. 5

Amplitude spectrum for lum and chrom for all of the data set (29 scenes) (shadow removing).

Fig. 6
Fig. 6

Mean ratio of the lum image to that of the chrom image amplitude for all of the data set. The three definitions are used. Standard error is shown on the plot.

Fig. 7
Fig. 7

Mean ratio of the lum image amplitude to that of the chrom image amplitude with the shadow-removing definition of lum and chrom. This average is done across all of the data set.

Fig. 8
Fig. 8

Mean ratio of the lum image amplitude to that of the chrom image amplitude for the long-distance viewing set (objects in the range 10–4 km and including grass and sky) and the short-distance viewing set (objects up to 10 m away from the camera).

Fig. 9
Fig. 9

Mean ratio of the lum image amplitude to that of the chrom image amplitude for short-distance scenes. The scenes are divided again into different groups (outdoor, indoor, and selected) and plotted along with the average for all groups (total).

Fig. 10
Fig. 10

Plot of the luminance to chrominance ratio obtained from Mullen’s11 measured contrast-sensitivity curves. The total area under each of the contrast-sensitivity curves has been made equal to 1. To match these measurements, the amount of spatial energy for luminance in the high-SF range must exceed that for chrominance, and the opposite must happen for the low-SF range.

Tables (2)

Tables Icon

Table 1 Range and Central Spatial Frequency (in Cycles/Deg) of SF Bands Used to Divide the Fourier Space

Tables Icon

Table 2 Mean Values of the Slope (α) for the Simple and the Shadow-Removing Definitions of Lum and Chrom

Equations (8)

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

lums=L+M,
chroms=L-M.
lumIT=1.02L+M,
chromIT=0.41L-M.
lumBG=0.887L+0.461M,
chromBG=0.46L-0.88M.
lumsr=L+M,
chromsr=L-ML+M=chromslums.

Metrics