Showing papers on "Color constancy published in 1991"

Simultaneous color constancy: papers with diverse Munsell values

Abstract: Arend and Reeves [J. Opt. Soc. Am. A 3, 1743 (1986)] described measurements of color constancy in computer simulations of arrays of colored papers of equal Munsell value under 4000-, 6500-, and 10,000-K daylight illuminants. We report an extension of those experiments to chromatic arrays spanning a wide range of Munsell values. The computer-simulated scene included a standard array of Munsell papers under 6500-K illumination and a test array, an identical array of the same papers under 4000 or 10,000 K. Observers adjusted a patch in the test array in order to match the corresponding patch in the standard array by one of two criteria. They either matched hue and saturation or they made surface-color matches, in which the test patch was made to "look as if it were cut from the same pice of paper as the standard patch." The test and the standard patches were surrounded by a single color (annulus display) or by many colors (Mondrian display). The data agreed with those of our previous equal-value experiment. The paper matches were often approximately color constant. The hue-saturation matches were in the correct direction for constancy but were always closer to a chromaticity match (no constancy) than to the chromaticity required for hue-saturation constancy.

A real-time neural system for color constancy

Abstract: A neural network approach to the problem of color constancy is presented. Various algorithms based on Land's retinex theory are discussed with respect to neurobiological parallels, computational efficiency, and suitability for VLSI implementation. The efficiency of one algorithm is improved by the application of resistive grids and is tested in computer simulations; the simulations make clear the strengths and weaknesses of the algorithm. A novel extension to the algorithm is developed to address its weaknesses. An electronic system that is based on the original algorithm and that operates at video rates was built using subthreshold analog CMOS VLSI resistive grids. The system displays color constancy abilities and qualitatively mimics aspects of human color perception. >

Naming versus matching in color constancy

Abstract: In this paper, a replication of the color-constancy study of Arend and Reeves (1986) is reported, and an alternative method is presented that can be used for the study of higher order aspects of color constancy, such as memory, familiarity, and perceptual organization. Besides a simultaneous presentation of standard and test illuminants, we also carried out an experiment in which the illuminants were presented successively. The results were similar to Arend and Reeves's; however, in the object-matching condition of the successive experiment, we found an overestimation, instead of an underestimation, of the illuminant component. Because the results of matching experiments are difficult to interpret, mainly due to their sensitivity to instruction effects, we introduced another type of color-constancy task. In this task, subjects simply named the color of a simulated patch. It was found that, by applying such a task, a reliable measure of the degree of identification of object color can be obtained.

Color constancy from mutual reflection

Abstract: Mutual reflection occurs when light reflected from one surface illuminates a second surface. In this situation, the color of one or both surfaces can be modified by a color-bleeding effect. In this article we examine how sensor values (e.g., RGB values) are modified in the mutual reflection region and show that a good approximation of the surface spectral reflectance function for each surface can be recovered by using the extra information from mutual reflection. Thus color constancy results from an examination of mutual reflection. Use is made of finite dimensional linear models for ambient illumination and for surface spectral reflectance. If m and n are the number of basis functions required to model illumination and surface spectral reflectance respectively, then we find that the number of different sensor classes p must satisfy the condition p≥(2 n+m)/3. If we use three basis functions to model illumination and three basis functions to model surface spectral reflectance, then only three classes of sensors are required to carry out the algorithm. Results are presented showing a small increase in error over the error inherent in the underlying finite dimension models.

Color categorization and color constancy in a neural network model of V4

Abstract: We develop a neural network model that instantiates color constancy and color categorization in a single unified framework. Previous models achieve similar effects but ignore important biological constraints. Color constancy in this model is achieved by a new application of the double opponent cells found in the "blobs" of the visual cortex. Color categorization emerges naturally, as a consequence of processing chromatic stimuli as vectors in a four-dimensional color space. A computer simulation of this model is subjected to the classic psychophysical tests that first uncovered these phenomena, and its response matches psychophysical results very closely.

Supervised color constancy for machine vision

Abstract: In machine vision, color constancy is the ability to match object colors in images taken under different colors of illumination. This is a difficult problem because the image color will depend upon the spectral reflectance function of the object and the spectral distribution function of the incident light, both of which are generally unknown. Previous methods to solve this problem have represented these functions with a small number of basis functions and used some sort of reference knowledge to calculate the coefficients. Most of these methods have the weakness that the reference property may not actually hold for all images, or that it provides too few constraints to allow an adequate recovery of the functions. We present here a method for color constancy that uses a color chart of known spectral characteristics to give stronger reference criteria, and with a large number of colors to give enough constraints to calculate the illuminant to the desired degree of accuracy. We call this approach 'supervised color constancy' since the process is supervised by a picture of a reference color chart. We demonstrate two methods for computing supervised color constancy, one using least squares estimation, the other using a neural network. We present results for simulated experiment of the calculation of the spectral power distribution of an unknown illuminant.

Adaptation Mechanisms in Color and Brightness

Abstract: In order for color to be a useful property for segmenting and identifying objects in a scene it must remain constant in spite of variations in intensity and color of the ambient light, and we know that the visual system achieves an elegant deconfounding of incident light and the reflectance of objects. The last decade has seen considerable advances in the formal analysis of color constancy. These advances have not been matched, however, by advances in understanding whether or how the nervous system carries out these computations. Models of constancy generally require some sort of ‘knowledge’ or computation of the illuminant (see review by Lennie & D’Zmura, 1988). This knowledge may be realized in the visual system to a large extent by mechanisms of light adaptation which can compensate for the changes in the illuminant so that objects of constant reflectance will have a constant effect following adaptational transformations (D’Zmura & Lennie, 1986). Light adaptation is generally acknowledged to play a major role in both color and brightness constancy, but the nature of the adaptational transformations and how they contribute to constancy are poorly understood. In this chapter we will report on preliminary experiments which attempt to specify how light adaptation mechanisms operate to determine the color and brightness of lights. First, we will describe what we know about light adaptation from measurements of sensitivity and then describe how this might be extended to account for color appearance and brightness.

Testing the Contrast Explanation of Color Constancy

Abstract: The light that an object reflects towards the eye is the product of surface reflectance and incident illumination. The problem how to decompose that product, and thus separate light from matter, is one of the central issues in the study of the visual system. Research in this area has been boosted by its obvious relevance for machine vision (e.g. Horn, 1985; Hurlbert and Poggio, 1988), but as yet, with only limited success.

3D grating optics of human vision.

Abstract: The approximately 6-7 layers of closestpacked photoreceptor cell bodies in the outer nuclear layer of the human retina are interpreted as hexagonal multilayer phase or three-dimensional gratings with refractive index differences between the cell nucleus and the cytoplasm. A multilayer 3D grating of this type allows incident light to be processed by Fresnel interference in the plane of focus of the geometrical-optical system of the human eye, forming triplets of chromatic interference maxima made available, at discrete concentric locations, to the outer segments of the cones and rods for further processing. Transformation of the 3D grating spacing (in the sense of a stimulus-adaptive optic) into the dimensional periodicity of the spectral stimulus which is processed with maximum amplitude in the 111 color channel gives three chromatic signals at 559/537/447 nm in the visible 'spectral window', i.e. at spectral locations which match the 3 wavelengths of (photochemically determined) maximum spectral sensitivity in photopic vision. Variation of the cell geometry in the 3D grating gives rise to the Purkinje shift with fusion of the RED-GREEN diffraction orders at 512 nm. Color proves mathematically to be the product (varied by the diffraction order triplets) of the speed of light and the three-dimensional geometry. The chemistry of the photoreceptors, i.e. the programming of the visual pigments, would consequently be based on 3D grating optics. The human eye would process trichromatic Fourier signals, not geometrical-optical images. The first stage of color vision would be based on 3D grating optics, without the involvement of neuronal networks. New interpretations ensue for color constancy, color adaptation, color visual field, inter alia. The eye, as a trichromatic Fresneloptical modulator of the information present in the amplitude, phase and frequency of the processed light, receives considerably more information on perceived objects than it passes on to the brain. Cellular 3D gratings may also be models for the interference of acoustic, chemical and other waves in cortical processing centers.

Stimulus determinants of achromatic constancy.

Abstract: Achromatic constancy refers to the invariance of either lightness or brightness despite changes in illumination intensity. Previous results disagree as to the extent to which constancy occurs with fixed luminance ratio conditions. This may reflect a lack of distinction between lightness and brightness. We measured both lightness and brightness constancy with fixed luminance ratios between test and annular fields under conditions varying in stimulus duration and adaptation. Lightness constancy occurred for all ratios under sustained viewing conditions and irrespective of adaptation level. Brightness constancy occurred for high-contrast stimuli and under sustained viewing conditions. These results support a bidimensional description of achromatic stimuli and suggest that lightness and brightness are the outcomes of two functionally distinct processes.

Surface reflectances and human color constancy: comment on Dannemiller (1989)

Abstract: Dannemiller's (1989) computational approach to color constancy is discussed in relation to human color constancy. A reflectance channel that requires a priori information is shown to be less plausible for the human visual system than Dannemiller argued. The resemblance of Dannemiller's hypothetical visual system to the human visual system is misleading because it implies that surface reflectance is the illuminant-invariant object color descriptor that the human visual system uses to achieve color constancy. However, an alternative type of descriptor is available that is not used to recover reflectance spectra. It has the advantage of allowing an interpretation that is preferable from a human perceptual point of view.

Photometric models in multispectral machine vision

Abstract: The performance of several tasks in multispectral computer vision involves assumptions about the reflection of light from surfaces. These tasks include color constancy (visual representation of spectral reflectances independent of the illuminant spectrum), object-based image segmentation, and deduction of the shape of a surface from its shading. Most color-constancy theories implicitly assume Lambertian, coplanar reflecting surfaces, a distant viewer, and a distant light source that may have many components that are spatially and spectrally distinct. Object-based-segmentation theories allow curved surfaces, each of whose scattering kernels is the sum of a few separable terms (each of which is the product of a wavelength-dependent part and a geometry-dependent part). There is no restriction on the distances of light sources or observer. However, for these theories the illuminant angular/spectral distribution must consist of only one or two separable terms. Finally, A. Petrov's shape-from-shading theory allows the light source to have nearly arbitrary spectral and spatial composition, but requires the surface scattering kernels to have Lambertian dependence on the surface normal. The present paper compares these photometric models.© (1991) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.