Color-contrast and color-constancy.

1935 ◽  
Vol 18 (1) ◽  
pp. 49-63 ◽  
Author(s):  
G. Katona
Keyword(s):  
Color Constancy ◽  
Color Contrast

The cone/horizontal cell network: A possible site for color constancy

1998 ◽  
Vol 15 (5) ◽  
pp. 787-797 ◽  
Author(s):  
M. KAMERMANS ◽  
D.A. KRAAIJ ◽  
H. SPEKREIJSE
Keyword(s):  
Horizontal Cell ◽  
Color Constancy ◽  
Spectral Composition ◽  
Color Discrimination ◽  
Cell System ◽  
Horizontal Cells ◽  
Feedback Signal ◽  
Color Contrast ◽  
Cell Network ◽  
Simultaneous Color Contrast

Color vision is spectrally opponent, suggesting that spectrally opponent neurons, such as the horizontal cells in fish and turtle retinae, play a prominent role in color discrimination. In the accompanying paper (Kraaij et al., 1998), it was shown that the output signal of the horizontal cell system to the cones is not at all spectrally opponent. Therefore, a role for the spectrally opponent horizontal cells in color discrimination seems unlikely. In this paper, we propose that the horizontal cells play a prominent role in color constancy and simultaneous color contrast instead of in color discrimination. We have formulated a model of the cone/horizontal cell network based on measurements of the action spectra of the cones and of the feedback signal of the horizontal cell system to the various cone types. The key feature of the model is (1) that feedback is spectrally and spatially very broad and (2) that the gain of the cone synapse strongly depends on the feedback strength. This makes the synaptic gain of the cones strongly dependent on the spectral composition of the surround. Our model, which incorporates many physiological details of the outer retina, displays a behavior that can be interpreted as color constancy and simultaneous color contrast. We propose that the horizontal cell network modulates the cone synaptic gains such that the ratios of the cone outputs become almost invariant with the spectral composition of the global illumination. Therefore, color constancy appears to be coded in the retina.

Insect Color Vision

2021 ◽  
Author(s):  
Natalie Hempel de Ibarra ◽  
Misha Vorobyev
Keyword(s):  
Color Vision ◽  
Spatial Resolution ◽  
Compound Eye ◽  
Color Constancy ◽  
Spectral Composition ◽  
Polarization Sensitivity ◽  
Color Contrast ◽  
Human Beings ◽  
In The Beginning ◽  
Polarization Of Light

Color plays an important role in insect life—many insects forage on colorful flowers and/or have colorful bodies. Accordingly, most insects have multiple spectral types of photoreceptors in their eyes, which gives them the capability to see colors. However, insects cannot perceive colors in the same way as human beings do because their eyes and brains differ substantially. An insect was the first nonhuman animal whose ability to discriminate colors has been demonstrated - in the beginning of the 20th century, von Frisch showed that the honeybee, Apis mellifera, can discriminate blue from any shade of gray. This method, called the gray-card experiment, is an accepted “gold standard” for the proof of color vision in animals. Insect species differ in the combinations of photoreceptors in their eyes, with peak sensitivities in ultraviolet (UV) and/or blue, green, and sometimes red parts of the spectrum. The number of photoreceptor spectral types can be as little as one or two, as in the grasshopper Phlaeoba and the beetle Tribolium, and as many as 10 and more in some species of butterflies and dragonflies. However, not all spectral receptor types are necessarily used for color vison. For example, the butterfly Papilio xuthus uses only four of its eight photoreceptors for color vision. Some insects have separate channels for processing chromatic and achromatic (lightness) information. In the honeybee, the achromatic channel has high spatial resolution and is mediated only by long-wavelength sensitive, or “green,” photoreceptors alone, whereas the spatial resolution of chromatic vision is low and mediated by all three spectral types of photoreceptors. Whether other insects have a similar separation of chromatic and achromatic vision remains uncertain. In contrast to vertebrates, insects do not use distinct sets of photoreceptors for nocturnal vision, and some nocturnal insects can see color at night. Insect photoreceptors are inherently polarization sensitive because of their microvillar organization. Therefore, some insects cannot discriminate changes in polarization of light from changes in its spectral composition. However, many insects sacrifice polarization sensitivity to retain reliable color vision. For example, in the honeybee, polarization sensitivity is eliminated by twisting the rhabdom in most parts of its compound eye except for the dorsal rim area that is specialized in polarization vision. Insects experience color constancy and color-contrast phenomena. Although in humans these aspects of vision are often attributed to cortical processing of color, simple models based on photoreceptor adaptation may explain color constancy and color induction in insects. Color discriminations can be evaluated using a simple model, which assumes that it is limited by photoreceptor noise. This model can help to predict discrimination of colors that are ecologically relevant, such as flower colors for pollinating insects. However, despite the fact that many insects forage on flowers, there is no evidence that insect pollinator vision coevolved with flower colors. The diverse color vision in butterflies appears to adaptively facilitate the recognition of their wing colors.

The contribution of the outer retina to color constancy: A general model for color constancy synthesized from primate and fish data

2007 ◽  
Vol 24 (3) ◽  
pp. 277-290 ◽  
Author(s):  
M.T. VANLEEUWEN ◽  
C. JOSELEVITCH ◽  
I. FAHRENFORT ◽  
M. KAMERMANS
Keyword(s):  
Color Vision ◽  
Horizontal Cell ◽  
Logical Consequence ◽  
Color Constancy ◽  
Cell System ◽  
Current Evidence ◽  
Color Contrast ◽  
Spatial Integration ◽  
Direct Measurements ◽  
White Point

Color constancy is one of the most impressive features of color vision systems. Although the phenomenon has been studied for decades, its underlying neuronal mechanism remains unresolved. Literature indicates an early, possibly retinal mechanism and a late, possibly cortical mechanism. The early mechanism seems to involve chromatic spatial integration and performs the critical calculations for color constancy. The late mechanism seems to make the color manifest. We briefly review the current evidence for each mechanism. We discuss in more detail a model for the early mechanism that is based on direct measurements of goldfish outer retinal processing and induces color constancy and color contrast. In this study we extrapolate this model to primate retina, illustrating that it is highly likely that a similar mechanism is also present in primates. The logical consequence of our experimental work in goldfish and our model is that the wiring of the cone/horizontal cell system sets the reference point for color vision (i.e., it sets the white point for that animal).

Expressions of color contrast as equivalent achromatic contrast

1982 ◽  
Author(s):  
David L. Post ◽  
Edward B. Costanza ◽  
Thomas M. Lippert
Keyword(s):  
Color Contrast ◽  
Achromatic Contrast

A Flying Gray Ball Multi-illuminant Image Dataset for Color Research

2020 ◽  
Vol 64 (5) ◽  
pp. 50411-1-50411-8
Author(s):  
Hoda Aghaei ◽  
Brian Funt
Keyword(s):  
Machine Vision ◽  
Spectral Reflectance ◽  
Color Constancy ◽  
Ground Truth ◽  
Practical Approach ◽  
Post Processing ◽  
Illumination Estimation ◽  
Processing Step ◽  
Image Dataset

Abstract For research in the field of illumination estimation and color constancy, there is a need for ground-truth measurement of the illumination color at many locations within multi-illuminant scenes. A practical approach to obtaining such ground-truth illumination data is presented here. The proposed method involves using a drone to carry a gray ball of known percent surface spectral reflectance throughout a scene while photographing it frequently during the flight using a calibrated camera. The captured images are then post-processed. In the post-processing step, machine vision techniques are used to detect the gray ball within each frame. The camera RGB of light reflected from the gray ball provides a measure of the illumination color at that location. In total, the dataset contains 30 scenes with 100 illumination measurements on average per scene. The dataset is available for download free of charge.

EFFECT OF COLOR CONTRAST ON VISUAL LOBE SHAPE CHARACTERISTICS1,2

2013 ◽  
pp. 130628095601001
Author(s):  
Steve N. H. Tsang ◽  
Alan H. S. Chan ◽  
R. F. Yu
Keyword(s):  
Color Contrast
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