How the orientation of the color gamut of natural scenes influences color discrimination in red-green dichromacy.

In natural scenes, visual discrimination of colored surfaces by individuals with X-linked dichromacy is known to be only a little poorer than in normal trichromacy. This surprising result may be related to the properties of the colors of these scenes, like the shape and orientation of the color gamut, uneven frequency, and a considerable variation in lightness. It is unclear, however, how much each of these factors contributes to the small impairment in discrimination, in particular, what is the contribution of the orientation of the gamut. We measured the discrimination of colors from natural scenes by six normal trichromats and six dichromats. Colors were drawn either from the original color gamut of the scenes or from gamut-rotated versions of the scenes. Pairs of colors were randomly drawn from hyperspectral images of one rural and one urban environment and presented on a screen. As expected, dichromats were only a little poorer than normal trichromats at discrimination but the disadvantage varied systematically with the orientation of the color gamut by a factor of about three with a minimum around a yellow-green axis. Dichromats also took longer to respond, and the response times were modulated with the orientation of the color gamut in a similar way as the loss in discrimination. For the scenes tested here, these results imply an important impact of the orientation of the gamut on discrimination. They also indicate that the predominantly yellow-blue orientation of the gamut of natural scene might not be optimal for discrimination in dichromacy.

Misidentifying illuminant changes in natural scenes due to failures in relational colour constancy.

The colours of surfaces in a scene may not appear constant with a change in the colour of the illumination. Yet even when colour constancy fails, human observers can usually discriminate changes in lighting from changes in surface reflecting properties. This operational ability has been attributed to the constancy of perceived colour relations between surfaces under illuminant changes, in turn based on approximately invariant spatial ratios of cone photoreceptor excitations. Natural deviations in these ratios may, however, lead to illuminant changes being misidentified. The aim of this work was to test whether such misidentifications occur with natural scenes and whether they are due to failures in relational colour constancy. Pairs of scene images from hyperspectral data were presented side-by-side on a computer-controlled display. On one side, the scene underwent illuminant changes and on the other side, it underwent the same changes but with images corrected for any residual deviations in spatial ratios. Observers systematically misidentified the corrected images as being due to illuminant changes. The frequency of errors increased with the size of the deviations, which were closely correlated with the estimated failures in relational colour constancy.

Little information loss with red-green color deficient vision in natural environments.

Inherited color vision deficiency affects red-green discrimination in about one in twelve men from European populations. Its effects have been studied mainly in primitive foraging but also in detecting blushing and breaking camouflage. Yet there is no obvious relationship between these specific tasks and vision in the real world. The aim here was to quantify the impact of color vision deficiency by estimating computationally the information available to observers about colored surfaces in natural scenes. With representative independent sets of 50 and 100 hyperspectral images, estimated information was found to be only a little less in red-green color vision deficiency than in normal trichromacy. Colorimetric analyses revealed the importance of large lightness variations within scenes, small redness-greenness variations, and uneven frequencies of different colored surfaces. While red-green color vision deficiency poses challenges in some tasks, it has much less effect on gaining information from natural environments.

Discrimination of natural colors in anomalous trichromacy and the effects of EnChroma and Vino filters.

It is still unclear how well anomalous trichromats discriminate natural colors and whether commercial spectral filters improve performance in these conditions. We show that anomalous trichromats have good color discrimination with colors drawn from natural environments. It is only about 14% poorer, on average, than normal trichromats in our sample of thirteen anomalous trichromats. No measurable effect of the filters on discrimination was found, even after 8 hours of continuous use. Computations of cone and post-receptoral signals show only a modest increase in medium-to-long-wavelength difference signals, which may explain the absent effect of the filters.

Information gains from commercial spectral filters in anomalous trichromacy.

Red-green color discrimination is compromised in anomalous trichromacy, the most common inherited color vision deficiency. This computational analysis tested whether three commercial optical filters with medium-to-long-wavelength stop bands increased information about colored surfaces. The surfaces were sampled from 50 hyperspectral images of outdoor scenes. At best, potential gains in the effective number of surfaces discriminable solely by color reached 9% in protanomaly and 15% in deuteranomaly, much less than with normal trichromacy. Gains were still less with lower scene illumination and more severe color vision deficiency. Stop-band filters may offer little improvement in objective real-world color discrimination.

Universality and superiority in preference for chromatic composition of art paintings.

Color composition in paintings is a critical factor affecting observers' aesthetic judgments. We examined observers' preferences for the color composition of Japanese and Occidental paintings when their color gamut was rotated. In the experiment, observers were asked to select their preferred image from original and three hue-rotated images in a four-alternative forced choice paradigm. Despite observers' being unfamiliar with the presented artwork, the original paintings (0 degrees) were preferred more frequently than the hue-rotated ones. Furthermore, the original paintings' superiority was observed when the images were divided into small square pieces and their positions randomized (Scrambled condition), and when the images were composed of square pieces collected from different art paintings and composed as patchwork images (Patchwork condition). Therefore, the original paintings' superiority regarding preference was quite robust, and the specific objects in the paintings associated with a particular color played only a limited role. Rather, the original paintings' general trend in color statistics influenced hue-angle preference. Art paintings likely share common statistical regulations in color distributions, which may be the basis for the universality and superiority of the preference for original paintings.

Naturalness and aesthetics of colors - Preference for color compositions perceived as natural.

What makes a colored image, e.g. an abstract painting or a landscape, look pleasing? We hypothesized that a preference for complex color compositions, such as paintings and images of natural scenes, might be related to how natural the colors are perceived. We tested this possibility with two experiments in which the degree of naturalness of images was manipulated by rotating their color gamut rigidly in the color space CIELAB. This changed just the hue composition, but preserved saturation and lightness. In the first experiment we obtained individual scaling curves for perceived naturalness and for preference as a function of the angle of gamut rotation for a small set of images. The naturalness and preference scaling curves were found to be largely similar and their maxima were close to the original image. In the second experiment, we tested whether this effect generalized to a larger set of images. We used a simultaneous 5AFC procedure where in each trial participants had to select the most natural or the most preferred image from five different rotations of the color gamut. The results confirmed the first experiment and showed that, in general, the images perceived as the more natural tend to be the ones that are preferred. Together these results show that perceived naturalness and preference are indeed perceptually closely related and may be driven by related mechanisms.

An independent contribution of colour to the aesthetic preference for paintings.

Walking around an art museum we can see how colours influence our aesthetic preferences: many great works of art would not be as impressive in grey scales. Is the beauty of colours in abstract paintings anchored to the spatial composition of the paintings, or can it be preserved even with random spatial arrangements? To test whether colour can have an independent contribution to aesthetic appreciation, we asked participants to select the preferred image among pairs of colour-manipulated versions of the same painting. We changed hue, but preserved lightness and saturation, by rotating the colour volume around the L* axis in CIELAB space. To test the influence of the spatial structure, the images of the paintings were presented: (1) in their original format, (2) spatially scrambled but preserving the colour composition, and (3) in a control condition with both colour and spatial scrambling. Relative preference as a function of hue angle was obtained for the four paintings in their original and modified forms. For the original paintings, we found that participants generally preferred the colour angles that matched the original version of the paintings. Crucially, participants preferred the same colour distributions for spatially scrambled paintings as for the original paintings. For the control condition, there were no preferred colour configurations. This suggests that the aesthetic preference of colours in our abstract paintings is not anchored to particular spatial compositions, but is at least partly preserved even when the spatial composition is destroyed. Paintings thus can contain an aesthetic component that is exclusively related to colour.

Art through the Colors of Graffiti: From the Perspective of the Chromatic Structure.

Graffiti is a general term that describes inscriptions on a wall, a practice with ancient origins, ranging from simple drawings and writings to elaborate pictorial representations. Nowadays, the term graffiti commonly describes the street art dedicated to wall paintings, which raises complex questions, including sociological, legal, political and aesthetic issues. Here we examine the aesthetics of graffiti colors by quantitatively characterizing and comparing their chromatic structure to that of traditional paintings in museums and natural scenes obtained by hyperspectral imaging. Two hundred twenty-eight photos of graffiti were taken in the city of São Paulo, Brazil. The colors of graffiti were represented in a color space and characterized by several statistical parameters. We found that graffiti have chromatic structures similar to those of traditional paintings, namely their preferred colors, distribution, and balance. In particular, they have color gamuts with the same degree of elongation, revealing a tendency for combining similar colors in the same proportions. Like more traditional artists, the preferred colors are close to the yellow-blue axis of color space, suggesting that graffiti artists' color choices also mimic those of the natural world. Even so, graffiti tend to have larger color gamuts due to the availability of a new generation of synthetic pigments, resulting in a greater freedom in color choice. A complementary analysis of graffiti from other countries supports the global generalization of these findings. By sharing their color structures with those of paintings, graffiti contribute to bringing art to the cities.

Hyperspectral environmental illumination maps: characterizing directional spectral variation in natural environments.

Objects placed in real-world scenes receive incident light from every direction, and the spectral content of this light may vary from one direction to another. In computer graphics, environmental illumination is approximated using maps that specify illumination at a point as a function of incident angle. However, to-date, existing public databases of environmental illumination specify only three colour channels (RGB). We have captured a new set of 12 environmental illumination maps (eight outdoor scenes; four indoor scenes) using a hyperspectral imaging system with 33 spectral channels. The data reveal a striking directional variation of spectral distribution of lighting in natural environments. We discuss limitations of using daylight models to describe natural environmental illumination.

Neighboring chromaticity influences how white a surface looks.

To identify surface properties independently of the illumination the visual system must make assumptions about the statistics of scenes and their illumination. Are assumptions about the intensity of the illumination independent of assumptions about its chromaticity? To find out, we asked participants to judge whether test patches within three different sets of surrounding surfaces were white or grey. Two sets were matched in terms of their maximal luminance, their mean luminance and chromaticity, and the variability in their luminance and chromaticity, but differed in how luminance and chromaticity were associated: the highest luminance was either associated with colorful surfaces or with achromatic ones. We found that test patches had to have a higher luminance to appear white when the highest luminance in the surrounding was associated with colorful surfaces. This makes sense if one considers that being colorful implies that a surface only reflects part of the light that falls on it, meaning that the illumination must have a higher luminance (a perfectly white surface reflects all of the light falling on it). In the third set, the colorful surfaces had the same luminance as in the set in which they were associated with the highest luminance, but the achromatic surfaces had a lower luminance so that the overall mean luminance was lower. Despite the constraints on the illumination being identical, test patches did not have to have as high luminance to appear white for the third set. Considering the layout of the surfaces in the surrounding revealed that test patches did have to have the same high luminance if the high luminance colorful surfaces were adjacent to the target patch. Thus, the assumptions about the possible illumination are applied locally. A possible mechanism is relying on the contrast within each type of cone: for a surface to appear white it must stimulate each of the three kinds of cones substantially more than do any neighboring surfaces.

The colors of natural scenes benefit dichromats.

Dichromacy impairs color vision and impoverishes the discrimination of surface colors in natural scenes. Computational estimates based on hyperspectral imaging data from natural scenes suggest that dichromats can discriminate only about 10% of the colors discriminated by normal trichromats. These estimates, however, assume that the colors are equally frequent. Yet, pairs of colors confused by dichromats may be rare and thus have small impact on overall perceived chromatic diversity. This study estimated, empirically, how much dichromats are disadvantaged in discriminating surface colors drawn from natural scenes. The stimulus for the experiment was a scene made of real three-dimensional objects painted with matte white paint and illuminated by a spectrally tunable light source. In each trial the observers saw the scene illuminated by two spectra in two successive time intervals and had to indicate whether the colors perceived in the objects in the two intervals were the same or different. The spectra were drawn randomly from hyperspectral data of natural scenes and therefore represented natural spectral statistics. Four normal trichromats and four dichromats carried out the experiment. It was found that the number of pairs that could be discriminated by dichromats was almost 70% of those discriminated by normal trichromats, a proportion much higher than anticipated from estimates of discernible colors. Moreover, data from model simulations show that normal trichromats and dichromats use lightness differences for discrimination in about 40% and 50% of the discriminable pairs, respectively. Together these results suggest that the color distributions of natural scenes benefit the color vision of dichromats.

Color Vision 2018: Introduction by the feature editors.

This feature issue of the Journal of the Optical Society of America A (JOSA A) reflects the basic and applied research interests of members of the color vision community. Most of the articles stem from presentations at the 24th Biennial Symposium of the International Colour Vision Society (ICVS).

Color constancy of color reproductions in art paintings.

Popular color reproductions of art paintings such as postcards are intended to remind viewers of the original works. It is, however, unclear how well the quality of the reproductions is preserved under various illuminations. Color constancy of the reproductions in relation to colors in the original paintings was estimated computationally with hyperspectral images of 15th-century Flemish paintings, 20th-century modern abstract paintings, and their corresponding postcards with a series of illuminants: the CIE daylight D65 with correlated color temperature (CCT) 6500 K, daylight D40, fluorescent lamps F2 and F11, and a LED lamp designed for museums with CCT approximately 3500-4000 K. Despite large colorimetric differences between the types of art paintings and between the illuminants simulated, local areas showed good color constancy: skin areas in the Flemish paintings ranged from 0.76 to 0.81, whereas nonskin areas ranged from 0.19 to 0.68. This result suggests that viewers may be able to achieve color constancy with the reproduction postcards by disregarding inconsistent colors representations from the original paintings caused by changes in illumination conditions.

Robust colour constancy in red-green dichromats.

Colour discrimination has been widely studied in red-green (R-G) dichromats but the extent to which their colour constancy is affected remains unclear. This work estimated the extent of colour constancy for four normal trichromatic observers and seven R-G dichromats when viewing natural scenes under simulated daylight illuminants. Hyperspectral imaging data from natural scenes were used to generate the stimuli on a calibrated CRT display. In experiment 1, observers viewed a reference scene illuminated by daylight with a correlated colour temperature (CCT) of 6700K; observers then viewed sequentially two versions of the same scene, one illuminated by either a higher or lower CCT (condition 1, pure CCT change with constant luminance) or a higher or lower average luminance (condition 2, pure luminance change with a constant CCT). The observers' task was to identify the version of the scene that looked different from the reference scene. Thresholds for detecting a pure CCT change or a pure luminance change were estimated, and it was found that those for R-G dichromats were marginally higher than for normal trichromats regarding CCT. In experiment 2, observers viewed sequentially a reference scene and a comparison scene with a CCT change or a luminance change above threshold for each observer. The observers' task was to identify whether or not the change was an intensity change. No significant differences were found between the responses of normal trichromats and dichromats. These data suggest robust colour constancy mechanisms along daylight locus in R-G dichromacy.

The colors of paintings and viewers' preferences.

One hypothesis to explain the aesthetics of paintings is that it depends on the extent to which they mimic natural image statistics. In fact, paintings and natural scenes share several statistical image regularities but the colors of paintings seem generally more biased towards red than natural scenes. Is the particular option for colors in each painting, even if less naturalistic, critical for perceived beauty? Here we show that it is. In the experiments, 50 naïve observers, unfamiliar with the 10 paintings tested, could rotate the color gamut of the paintings and select the one producing the best subjective impression. The distributions of angles obtained are described by normal distributions with maxima deviating, on average, only 7 degrees from the original gamut orientation and full width at half maximum just above the threshold to perceive a chromatic change in the paintings. Crucially, for data pooled across observers and abstract paintings the maximum of the distribution was at zero degrees, i.e., the same as the original. This demonstrates that artists know what chromatic compositions match viewers' preferences and that the option for less naturalistic colors does not constrain the aesthetic value of paintings.

Statistics of colors in paintings and natural scenes.

Painters reproduce some spatial statistical regularities of natural scenes. To what extent they replicate their color statistics is an open question. We investigated this question by analyzing the colors of 50 natural scenes of rural and urban environments and 44 paintings with abstract and figurative compositions. The analysis was carried out using hyperspectral imaging data from both sets and focused on the gamut and distribution of colors in the CIELAB space. The results showed that paintings, like natural scenes, have gamuts with elongated shapes in the yellow-blue direction but more tilted to the red direction. It was also found that the fraction of discernible colors, expressed as a function of the number of occurrences in the scene or painting, is well described by power laws. These have similar distribution of slopes in a log-log scale for paintings and natural scenes. These features are observed in both abstract and figurative compositions. These results suggest that the underlying chromatic structure of artistic compositions generally follows the main statistical features of the natural environment.

Assessing the effects of dynamic luminance contrast noise masking on a color discrimination task.

The aim of this work was to assess the influence of dynamic luminance contrast noise masking (LCNM) on color discrimination for color normal and anomalous trichromats. The stimulus was a colored target on a background presented on a calibrated CRT display. In the static LCNM condition, the background and target consisted of packed circles with variable size and static random luminance. In the dynamic LCNM condition, a 10 Hz square luminance signal was added to each circle. The phase of this signal was randomized across circles. Discrimination thresholds were estimated along 20 hue directions concurrent at the color of the background. Six observers with normal color vision, six deuteranomalous observers, and three protanomalous observers performed the test in both conditions. With dynamic LCNM, thresholds were significantly lower for anomalous observers but not for normal observers, suggesting a facilitation effect of the masking for anomalous trichromats.

Spatial distributions of local illumination color in natural scenes.

In natural complex environments, the elevation of the sun and the presence of occluding objects and mutual reflections cause variations in the spectral composition of the local illumination across time and location. Unlike the changes in time and their consequences for color appearance and constancy, the spatial variations of local illumination color in natural scenes have received relatively little attention. The aim of the present work was to characterize these spatial variations by spectral imaging. Hyperspectral radiance images were obtained from 30 rural and urban scenes in which neutral probe spheres were embedded. The spectra of the local illumination at 17 sample points on each sphere in each scene were extracted and a total of 1904 chromaticity coordinates and correlated color temperatures (CCTs) derived. Maximum differences in chromaticities over spheres and over scenes were similar. When data were pooled over scenes, CCTs ranged from 3000 K to 20,000 K, a variation of the same order of magnitude as that occurring over the day. Any mechanisms that underlie stable surface color perception in natural scenes need to accommodate these large spatial variations in local illumination color.

Time-lapse ratios of cone excitations in natural scenes.

The illumination in natural environments varies through the day. Stable inferences about surface color might be supported by spatial ratios of cone excitations from the reflected light, but their invariance has been quantified only for global changes in illuminant spectrum. The aim here was to test their invariance under natural changes in both illumination spectrum and geometry, especially in the distribution of shadows. Time-lapse hyperspectral radiance images were acquired from five outdoor vegetated and nonvegetated scenes. From each scene, 10,000 pairs of points were sampled randomly and ratios measured across time. Mean relative deviations in ratios were generally large, but when sampling was limited to short distances or moderate time intervals, they fell below the level for detecting violations in ratio invariance. When illumination changes with uneven geometry were excluded, they fell further, to levels obtained with global changes in illuminant spectrum alone. Within sampling constraints, ratios of cone excitations, and also of opponent-color combinations, provide an approximately invariant signal for stable surface-color inferences, despite spectral and geometric variations in scene illumination.