Color Contrast Detection in Spatial Chromatic Noise

In this report, higher order color mechanisms for the detection of spatial distributions of color are investigated. The objective of this work is to understand which are the visual mechanisms involved in chromatic detection tasks and to dene the properties of such mechanisms. Despite great investigation eorts, human color vision is far from being satisfactorily explained. It is still not clear which mechanisms, at a post-receptoral level, mediate color detection. Recently, psychophysical studies have argued that the cone-opponent signals are further processed by higher order chromatic mechanisms, sort of multiple channels tuned to a variety of directions in the color space. A better understanding of chromatic detection mechanisms could enable the development of perceptual image quality metrics and the evaluation of chromatic noise masking eects. The mechanisms responsible for the detection of monochromatic signals have been described developing a psychophysical experiment. Such mechanisms have been characterized estimating contrast thresholds for the detection of a chromatic signal within a color spatial distribution using a sectored noise masking technique. The experiment was designed in the DKL color space, thus both signal and noise mask were dened in that space. Sectored noise draws samples from a sector of variable width in an equiluminant plane of the DKL color space. Such a sector is oriented along the same chromatic axis of the signal. Sector amplitude and width and test color direction were under experimental control. Observers were asked to detect a signal, a monochromatic Gaussian pulse, within a sectored noise. Contrast thresholds for the detection of red, light reddish, orange and yellow signals were measured. Estimating the potency of noise masking as a function of noise sector width, it is possible to distinguish directly between detection mechanisms that combine the photoreceptoral inputs in a linear or nonlinear fashion. In fact, a mechanism tuned to a certain color direction that combines the cone signals linearly is not inuenced by the noise components orthogonal to such a direction, that is, by the width of the noise sector. On the other hand, nonlinear mechanisms should be aected by the variation of sector width. In this report we carefully detail all the steps followed to develop our psychophysical experience. In our experiment, thresholds were found not to depend on noise sector width, consistently with the hypothesis of linear mechanisms operating for the detection of specic colors.

[1]  P. Lennie,et al.  Chromatic mechanisms in lateral geniculate nucleus of macaque. , 1984, The Journal of physiology.

[2]  A. Stockman,et al.  The spectral sensitivities of the middle- and long-wavelength-sensitive cones derived from measurements in observers of known genotype , 2000, Vision Research.

[3]  W. Dixon,et al.  Introduction to Mathematical Statistics. , 1964 .

[4]  Joe DeMaio,et al.  Introduction to Color , 1997 .

[5]  Angela M. Brown,et al.  Higher order color mechanisms , 1986, Vision Research.

[6]  M. Webster,et al.  The influence of contrast adaptation on color appearance , 1994, Vision Research.

[7]  R. Lakowski THE FARNSWORTH-MUNSELL 100-HUE TEST* , 1971 .

[8]  Daniel C Kiper,et al.  The detection of colored Glass patterns. , 2003, Journal of vision.

[9]  B. Wandell,et al.  Asymmetric color matching: how color appearance depends on the illuminant. , 1992, Journal of the Optical Society of America. A, Optics and image science.

[10]  Karl R. Gegenfurtner,et al.  Color Vision: From Genes to Perception , 1999 .

[11]  Thomas Young,et al.  On the theory of light and colours , 1967 .

[12]  D. W. Heeley,et al.  Cardinal directions of color space , 1982, Vision Research.

[13]  D. Jameson,et al.  Opponent chromatic induction: experimental evaluation and theoretical account. , 1961, Journal of the Optical Society of America.

[14]  Steven K Shevell,et al.  Chromatic induction: border contrast or adaptation to surrounding light? , 1998, Vision Research.

[15]  M. H. Pirenne,et al.  Dark-Adaptation and Night Vision , 1962 .

[16]  W. D. Wright A re-determination of the trichromatic coefficients of the spectral colours , 1929 .

[17]  Steven K. Shevell,et al.  Color appearance with sparse chromatic context , 1995, Vision Research.

[18]  W. Stiles,et al.  N.P.L. Colour-matching Investigation: Final Report (1958) , 1959 .

[19]  D. Kiper,et al.  Chromatic properties of neurons in macaque area V2 , 1997, Visual Neuroscience.

[20]  R. M. Boynton,et al.  Chromaticity diagram showing cone excitation by stimuli of equal luminance. , 1979, Journal of the Optical Society of America.

[21]  Peter G. Engeldrum,et al.  Psychometric Scaling: A Toolkit for Imaging Systems Development , 2000 .

[22]  S S Stevens,et al.  To Honor Fechner and Repeal His Law: A power function, not a log function, describes the operating characteristic of a sensory system. , 1961, Science.

[23]  J. Guild The Colorimetric Properties of the Spectrum , 1932 .

[24]  R T Eskew,et al.  Chromatic masking in the (delta L/L, delta M/M) plane of cone-contrast space reveals only two detection mechanisms. , 1998, Vision research.

[25]  G. Legge,et al.  Contrast discrimination in noise. , 1987, Journal of the Optical Society of America. A, Optics and image science.

[26]  M. Tovée Color Vision: From Genes to Perception , 2000, Trends in Neurosciences.

[27]  Kenneth Knoblauch,et al.  Spectral bandwidths for the detection of color , 1998, Vision Research.

[28]  D. Macleod,et al.  Spectral sensitivities of the human cones. , 1993, Journal of the Optical Society of America. A, Optics, image science, and vision.

[29]  J. Walraven Spatial characteristics of chromatic induction; the segregation of lateral effects from straylight artefacts. , 1973, Vision research.

[30]  J. B. Levitt,et al.  Functional properties of neurons in macaque area V3. , 1997, Journal of neurophysiology.

[31]  D. Jameson,et al.  Some Quantitative Aspects of an Opponent-Colors Theory. I. Chromatic Responses and Spectral Saturation , 1955 .

[32]  D JAMESON,et al.  Some quantitative aspects of an opponent-colors theory. IV. A psychological color specification system. , 1956, Journal of the Optical Society of America.

[33]  A. Stockman,et al.  The spectral sensitivity of the human short-wavelength sensitive cones derived from thresholds and color matches , 1999, Vision Research.

[34]  M. Mcnamee Treatise on Painting , 1958 .

[35]  Leonardo da Vinci,et al.  A Treatise on Painting , 2002 .

[36]  K R Gegenfurtner,et al.  Contrast detection in luminance and chromatic noise. , 1992, Journal of the Optical Society of America. A, Optics and image science.

[37]  J. Albers,et al.  Interaction of Color , 1971 .

[38]  J. Pokorny,et al.  Spectral sensitivity of the foveal cone photopigments between 400 and 500 nm , 1975, Vision Research.

[39]  J. Taylor An Introduction to Error Analysis , 1982 .

[40]  Rhea T. Eskew,et al.  Chromatic detection and discrimination analyzed by a Bayesian classifier , 2001, Vision Research.

[41]  Steven K. Shevell,et al.  Color perception within a chromatic context: changes in red/green equilibria caused by noncontiguous light , 1992, Vision Research.

[42]  Mahito Fujii,et al.  Sensitivity to modulation of color distribution in multicolored textures , 2001, Vision Research.

[43]  J. J. Vos Colorimetric and photometric properties of a 2° fundamental observer , 1978 .

[44]  Michael D'Zmura,et al.  Color in visual search , 1991, Vision Research.

[45]  R. L. Valois,et al.  Analysis of response patterns of LGN cells. , 1966, Journal of the Optical Society of America.

[46]  R. M. Boynton Human color vision , 1979 .

[47]  D. Macleod,et al.  Color appearance depends on the variance of surround colors , 1997, Current Biology.

[48]  Ewald Hering Outlines of a theory of the light sense , 1964 .

[49]  P. Lennie,et al.  Chromatic mechanisms in striate cortex of macaque , 1990, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[50]  S. Shevell,et al.  Chromatic induction with remote chromatic contrast varied in magnitude, spatial frequency, and chromaticity , 1999, Vision Research.

[51]  Leo Maurice Hurvich,et al.  Color vision , 1981 .

[52]  Grassmann XXXVII. On the theory of compound colours , 1854 .

[53]  T. Sejnowski,et al.  Nonlocal interactions in color perception: nonlinear processing of chromatic signals from remote inducers , 2001, Vision Research.

[54]  R. Penrose A Generalized inverse for matrices , 1955 .