Chromatic and achromatic information preserved in natural scenes under illuminant changes (original) (raw)

Surface chromaticity distributions of natural objects under changing illumination

2010

he problem of colour constancy is ill-posed. In order to extract surface reflectance accurately from the received colour signal, the visual system must rely on pre-imposed constraints based on properties of the natural world. Here we investigate the surface chromaticity distributions of 7 natural objects under 3 illuminations (D65, CWF and F), using a characterized Nikon D70 SLR camera. We find that these object surfaces exhibit intrinsic chromatic textures and provide a large number of reflectance samples on their own. The information may thereby be utilized to improve colour constancy over that achievable with artificial surfaces possessing single or limited chromaticities. By analyzing the pattern of the chromaticity distributions under changing illumination, we find that the distributions of within-surface cone contrasts for given objects form distinct signatures in cone-contrast space. These signatures transform predictably under changes in illumination. We suggest that this feature may be utilized to aid colour constancy.

Information limits on identification of natural surfaces by apparent colour

Perception, 2005

By adaptational and other mechanisms, the visual system can compensate for moderate changes in the colour of the illumination on a scene. Although the colours of most surfaces are perceived to be constant ("colour constancy"), some are not. The effect of these residual colour changes on the ability of observers to identify surfaces by their apparent colour was determined theoretically from high-resolution hyperspectral images of natural scenes under different daylights with correlated colour temperatures 4300 K, 6500 K, and 25000 K. Perceived differences between colours were estimated with an approximately uniform colour-distance measure. The information preserved under illuminant changes increased with the number of surfaces in the sample, but was limited to a relatively low asymptotic value, indicating the importance of physical factors in constraining identification by apparent colour.

Number of perceptually distinct surface colors in natural scenes

The ability to perceptually identify distinct surfaces in natural scenes by virtue of their color depends not only on the relative frequency of surface colors but also on the probabilistic nature of observer judgments. Previous methods of estimating the number of discriminable surface colors, whether based on theoretical color gamuts or recorded from real scenes, have taken a deterministic approach. Thus, a three-dimensional representation of the gamut of colors is divided into elementary cells or points which are spaced at one discrimination-threshold unit intervals and which are then counted. In this study, information-theoretic methods were used to take into account both differing surface-color frequencies and observer response uncertainty. Spectral radiances were calculated from 50 hyperspectral images of natural scenes and were represented in a perceptually almost uniform color space. The average number of perceptually distinct surface colors was estimated as 7.3 x 10^3, much smaller than that based on counting methods. This number is also much smaller than the number of distinct points in a scene that are, in principle, available for reliable identification under illuminant changes, suggesting that color constancy, or the lack of it, does not generally determine the limit on the use of color for surface identification.

Chromatic discrimination of natural objects

Journal of Vision, 2008

Studies of chromatic discrimination are typically based on homogeneously colored patches. Surfaces of natural objects, however, cannot be characterized by a single color. Instead, they have a chromatic texture, that is, a distribution of different chromaticities. Here we study chromatic discrimination for natural images and synthetic stimuli with a distribution of different chromaticities under various states of adaptation. Discrimination was measured at the adaptation point, where the mean chromaticity of the test stimuli was the same as the chromaticity of the adapting background, and away from the adaptation point. At the adaptation point, discrimination for natural objects resulted in threshold contours that were selectively elongated in a direction of color space matching the chromatic variation of the colors within the natural object. Similar effects occurred for synthetic stimuli. Away from the adaptation point, discrimination thresholds increased and threshold ellipses were elongated along the contrast axis connecting adapting color and test color. Away from the adaptation point, no significant differences between the different stimulus classes were found. The effect of the chromatic texture on discrimination seemed to be masked by the overall increase in discrimination thresholds. Our results show that discrimination of chromatic textures, either synthetic or natural, differs from that of simple uniform patches when the chromatic variation is centered at the adaptation point.

Fluctuating environmental light limits number of surfaces visually recognizable by colour

Scientific Reports, 2021

Small changes in daylight in the environment can produce large changes in reflected light, even over short intervals of time. Do these changes limit the visual recognition of surfaces by their colour? To address this question, information-theoretic methods were used to estimate computationally the maximum number of surfaces in a sample that can be identified as the same after an interval. Scene data were taken from successive hyperspectral radiance images. With no illumination change, the average number of surfaces distinguishable by colour was of the order of 10,000. But with an illumination change, the average number still identifiable declined rapidly with change duration. In one condition, the number after two minutes was around 600, after 10 min around 200, and after an hour around 70. These limits on identification are much lower than with spectral changes in daylight. No recoding of the colour signal is likely to recover surface identity lost in this uncertain environment.

Color and luminance information in natural scenes

Journal of the Optical Society of America A, 1998

The spatial filtering applied by the human visual system appears to be low-pass for chromatic stimuli and band-pass for luminance stimuli. Here we explore whether this observed difference in contrast sensitivity reflects a real difference in the components of chrominance and luminance in natural scenes. For this purpose a digital set of 29 hyper-spectral images of natural scenes has been acquired and its spatial frequency content analyzed in terms of chrominance and luminance defined according to existing models of the human cone responses and visual signal processing. The statistical 1/f amplitude spatial frequency distribution is confirmed for a variety of chromatic conditions across the visible spectrum. Our analysis suggests that natural scenes are relatively rich in high spatial-frequency chrominance information which does not appear to be transmitted by the human visual system. This result is unlikely to have arisen from errors in the original measurements. Several reasons may combine to explain a failure to transmit high spatial-frequency chrominance: (a) its minor importance for primate visual tasks, (b) its removal by filtering applied to compensate for chromatic aberration of the eye's optics, or (c) a biological bottleneck blocking its transmission. In addition, we graphically compare the ratios of luminance to chrominance measured by our hyperspectral camera and those measured psychophysically over an equivalent spatial frequency range.

Reliable identification by color under natural conditions

Journal of Vision, 2009

In order to recognize objects on the basis of the way in which they reflect different wavelengths of light, the visual system must deal with the different illuminant and background conditions under which the objects are seen. To test this ability under natural conditions, subjects were asked to name 6 uniformly colored papers. The experiment started by showing subjects six papers simultaneously in a normally illuminated room, and instructing them about how to name them. The papers were easy to differentiate when seen together but they were so similar that subjects only identified 87% correctly when they were presented in isolation under otherwise identical conditions to those during the instruction. During the main part of the experiment subjects walked between several indoor and outdoor locations that differed considerably in lighting and background colors. At each location subjects were asked to identify one paper. They correctly identified the paper on 55% of the trials (well above chance level), despite the fact that the variation in the light reaching their eyes from the same paper at different positions was much larger than that from different papers at the same position. We discuss that under natural conditions color constancy is probably as good as it can be considering the theoretical limitations.

The color of night: Surface color perception under dim illuminations

Visual Neuroscience, 2006

Several studies document rudimentary color vision under dim illumination. Here, hue perceptions of paper color samples were determined for a wide range of light levels, including very low light levels where rods alone mediate vision. The appearances of 24 paper color samples from the OSA Uniform Color Scales were gauged under successively dimmer illuminations from 10–0.0003 Lux. Triads of samples were chosen representing each of eight basic color categories; red, pink, orange, yellow, green, blue, purple, and gray. Samples within each triad varied in lightness. Observers sorted samples into groups that they could categorize with specific color names. Above 0.32 Lux, observers sorted the samples into the originally chosen color groups with few exceptions. For 0.1–0.01 Lux, the red and orange samples were usually correctly identified as either red or orange. The remaining samples tended to be grouped into two categories, associated with the scotopic sample reflectance. The lowest refl...

Information limits on neural identification of colored surfaces in natural scenes

Visual neuroscience, 2004

If surfaces in a scene are to be distinguished by their color, their neural representation at some level should ideally vary little with the color of the illumination. Four possible neural codes were considered: von-Kries-scaled cone responses from single points in a scene, spatial ratios of cone responses produced by light reflected from pairs of points, and these quantities obtained with sharpened (opponent-cone) responses. The effectiveness of these codes in identifying surfaces was quantified by information-theoretic measures. Data were drawn from a sample of 25 rural and urban scenes imaged with a hyperspectral camera, which provided estimates of surface reflectance at 10-nm intervals at each of 1344 3 1024 pixels for each scene. In computer simulations, scenes were illuminated separately by daylights of correlated color temperatures 4000 K, 6500 K, and 25,000 K. Points were sampled randomly in each scene and identified according to each of the codes. It was found that the maximum information preserved under illuminant changes varied with the code, but for a particular code it was remarkably stable across the different scenes. The standard deviation over the 25 scenes was, on average, approximately 1 bit, suggesting that the neural coding of surface color can be optimized independent of location for any particular range of illuminants.

How daylight influences high-order chromatic descriptors in natural images

Applied Optics, 2017

Despite the global and local daylight changes naturally occurring in natural scenes, the human visual system usually adapts quite well to those changes, developing a stable color perception. Nevertheless, the influence of daylight in modeling natural image statistics is not fully understood and has received little attention. The aim of this work was to analyze the influence of daylight changes in different high-order chromatic descriptors (i.e., color volume, color gamut, and number of discernible colors) derived from 350 color images, which were rendered under 108 natural illuminants with Correlated Color Temperatures (CCT) from 2735 to 25,889 K. Results suggest that chromatic and luminance information is almost constant and does not depend on the CCT of the illuminant for values above 14,000 K. Nevertheless, differences between the red-green and blue-yellow image components were found below that CCT, with most of the statistical descriptors analyzed showing local extremes in the range 2950 K-6300 K. Uniform regions and areas of the images attracting observers' attention were also considered in this analysis and were characterized by their patchiness index and their saliency maps. Meanwhile, the results of the patchiness index do not show a clear dependence on CCT, and it is remarkable that a significant reduction in the number of discernible colors (58% on average) was found when the images were masked with their corresponding saliency maps. Our results suggest that chromatic diversity, as defined in terms of the discernible colors, can be strongly reduced when an observer scans a natural scene. These findings support the idea that a reduction in the number of discernible colors will guide visual saliency and attention. Whatever the modeling is mediating the neural representation of natural images, natural image statistics, it is clear that natural image statistics should take into account those local maxima and minima depending on the daylight illumination and the reduction of the number of discernible colors when salient regions are considered.