Limitations of color constancy

Worthey, James A.

doi:10.1364/josaa.2.001014

Cited by 114 publications

(49 citation statements)

References 15 publications

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“…We are sometimes aware of violations of the invariance of cone-excitation ratios in the phenomenon of metamerism: two surfaces may match under one illuminant but not under another. 5 The analysis by Worthey (1985) suggests that metameric surfaces are in fact rare, but Foster & Nascimento (1994) show other violations of the invariance of coneexcitation ratios (for example, with some Munsell surfaces of extreme chroma). For two extreme illuminants, Nascimento et al (2002) found mean relative deviations of cone-excitation ratios of around 4% for distributions of reflectances encountered in natural scenes, and deviations of around 9% for random sampling of the Munsell set.…”

Section: (Iv) Coding Colour Relations By Ratiosmentioning

confidence: 99%

Sensory, computational and cognitive components of human colour constancy

Smithson

2005

Phil. Trans. R. Soc. B

184

139

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When the illumination on a scene changes, so do the visual signals elicited by that scene. In spite of these changes, the objects within a scene tend to remain constant in their apparent colour. We start this review by discussing the psychophysical procedures that have been used to quantify colour constancy. The transformation imposed on the visual signals by a change in illumination dictates what the visual system must 'undo' to achieve constancy. The problem is mathematically underdetermined, and can be solved only by exploiting regularities of the visual world. The last decade has seen a substantial increase in our knowledge of such regularities as technical advances have made it possible to make empirical measurements of large numbers of environmental scenes and illuminants. This review provides a taxonomy of models of human colour constancy based first on the assumptions they make about how the inverse transformation might be simplified, and second, on how the parameters of the inverse transformation might be set by elements of a complex scene. Candidate algorithms for human colour constancy are represented graphically and pictorially, and the availability and utility of an accurate estimate of the illuminant is discussed. Throughout this review, we consider both the information that is, in principle, available and empirical assessments of what information the visual system actually uses. In the final section we discuss where in our visual systems these computations might be implemented.

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Section: (Iv) Coding Colour Relations By Ratiosmentioning

confidence: 99%

Sensory, computational and cognitive components of human colour constancy

Smithson

2005

Phil. Trans. R. Soc. B

184

139

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“…As originally conceived by von Kries [1], [2], the eponymous scaling assumes that the spectral effects of the prevailing light on the sensitivity of long-, medium-, and short-wavelength-sensitive cone photoreceptors of the eye are contingent only on the response of each photoreceptor class and in a linear way. But von Kries' rule leaves unspecified precisely how the prevailing light determines the coefficients that describe the adjustment of each photoreceptor sensitivity (see, e.g., [38], [39]). …”

Section: Estimates Of Information Retrievedmentioning

confidence: 99%

Estimating Information from Image Colors: An Application to Digital Cameras and Natural Scenes

Marín-Franch

Foster

2013

IEEE Trans. Pattern Anal. Mach. Intell.

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Abstract-The colors present in an image of a scene provide information about its constituent elements. But the amount of information depends on the imaging conditions and on how information is calculated. This work had two aims. The first was to derive explicitly estimators of the information available and the information retrieved from the color values at each point in images of a scene under different illuminations. The second was to apply these estimators to simulations of images obtained with five sets of sensors used in digital cameras and with the cone photoreceptors of the human eye. Estimates were obtained for 50 hyperspectral images of natural scenes under daylight illuminants with correlated color temperatures 4,000, 6,500, and 25,000 K. Depending on the sensor set, the mean estimated information available across images with the largest illumination difference varied from 15.5 to 18.0 bits and the mean estimated information retrieved after optimal linear processing varied from 13.2 to 15.5 bits (each about 85 percent of the corresponding information available). With the best sensor set, 390 percent more points could be identified per scene than with the worst. Capturing scene information from image colors depends crucially on the choice of camera sensors.

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“…8 and Thornton and Chen 6 have called attention to another type of source that sharply reduces color contrast, that is the two-narrow-bands light 9 . A white such as 4002 K blackbody radiation [(x, y) = (0.3804, 0.3767)] can be metameric to a mixture of a narrow band in the blue (446 nm), plus a narrow band in the yellow (574 nm).…”

Section: Ivesmentioning

confidence: 99%

Color rendering: Asking the question

Worthey¹

2003

Color Research & Application

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Two white lights may have the same chromaticity, and yet when used to light an array of objects may differ in their ability to reveal colors. For example, any white light can be matched by a mixture of two narrow-band lights, a yellow plus a blue. In this extreme case, reds and greens become black or brown and the red-green dimension is lost. At the other extreme, a light with three narrow bands, at the proper wavelengths, can brighten reds and greens and increase redgreen contrast, relative to a broad-band light such as daylight. Many commercial lights tend to dull reds and greens, relative to broad-band sources, a central reason that color rendering is a practical concern. A telling example is neodymium glass, a yellow-absorbing filter that is sometimes used to improve color rendering. This article seeks to bring these ideas to life through detailed graphical examples.

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Limitations of color constancy

Cited by 114 publications

References 15 publications

Sensory, computational and cognitive components of human colour constancy

Sensory, computational and cognitive components of human colour constancy

Estimating Information from Image Colors: An Application to Digital Cameras and Natural Scenes

Color rendering: Asking the question

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