Illumination discrimination in real and simulated scenes

Lightness constancy in reality, in virtual reality, and on flat-panel displays

Virtual reality (VR) displays are being used in an increasingly wide range of applications. However, previous work shows that viewers often perceive scene properties very differently in real and virtual environments and so realistic perception of virtual stimuli should always be a carefully tested conclusion, not an assumption. One important property for realistic scene perception is surface color. To evaluate how well virtual platforms support realistic perception of achromatic surface color, we assessed lightness constancy in a physical apparatus with real lights and surfaces, in a commercial VR headset, and on a traditional flat-panel display. We found that lightness constancy was good in all three environments, though significantly better in the real environment than on the flat-panel display. We also found that variability across observers was significantly greater in VR and on the flat-panel display than in the physical environment. We conclude that these discrepancies should be taken into account in applications where realistic perception is critical but also that in many cases VR can be used as a flexible alternative to flat-panel displays and a reasonable proxy for real environments.

A Bayesian observer model reveals a prior for natural daylights in hue perception

Incorporating statistical characteristics of stimuli in perceptual processing can be highly beneficial for reliable estimation from noisy sensory measurements but may generate perceptual bias. According to Bayesian inference, perceptual biases arise from the integration of internal priors with noisy sensory inputs. In this study, we used a Bayesian observer model to derive biases and priors in hue perception based on discrimination data for hue ensembles with varying levels of chromatic noise. Our results showed that discrimination thresholds for isoluminant stimuli with hue defined by azimuth angle in cone-opponent color space exhibited a bimodal pattern, with lowest thresholds near a non-cardinal blue-yellow axis that aligns closely with the variation of natural daylights. Perceptual biases showed zero crossings around this axis, indicating repulsion away from yellow and attraction towards blue. These biases could be explained by the Bayesian observer model through a non-uniform prior with a preference for blue. Our findings suggest that visual processing takes advantage of knowledge of the distribution of colors in natural environments for hue perception.

Color constancy for daylight illumination changes in anomalous trichromats and dichromats

Color constancy is the perceptual stability of surface colors under temporal changes in the illumination spectrum. The illumination discrimination task (IDT) reveals worse discrimination for "bluer" illumination changes in normal-trichromatic observers (changes towards cooler color temperatures on the daylight chromaticity locus), indicating greater stability of scene colors or better color constancy, compared with illumination changes in other chromatic directions. Here, we compare the performance of individuals with X-linked color-vision deficiencies (CVDs) to normal trichromats on the IDT performed in an immersive setting with a real scene illuminated by spectrally tunable LED lamps. We determine discrimination thresholds for illumination changes relative to a reference illumination (D65) in four chromatic directions, roughly parallel and orthogonal to the daylight locus. We find, using both a standard CIELUV metric and a cone-contrast metric tailored to distinct CVD types, that discrimination thresholds for daylight changes do not differ between normal trichromats and CVD types, including dichromats and anomalous trichromats, but thresholds for atypical illuminations do differ. This result extends a previous report of illumination discrimination ability in dichromats for simulated daylight changes in images. In addition, using the cone-contrast metric to compare thresholds for bluer and yellower daylight changes with those for unnatural redder and greener changes, we suggest that reduced sensitivity to daylight changes is weakly preserved in X-linked CVDs.

Equivalent noise characterization of human lightness constancy

A goal of visual perception is to provide stable representations of task-relevant scene properties (e.g. object reflectance) despite variation in task-irrelevant scene properties (e.g. illumination and reflectance of other nearby objects). To study such stability in the context of the perceptual representation of lightness, we introduce a threshold-based psychophysical paradigm. We measure how thresholds for discriminating the achromatic reflectance of a target object (task-relevant property) in rendered naturalistic scenes are impacted by variation in the reflectance functions of background objects (task-irrelevant property), using a two-alternative forced-choice paradigm in which the reflectance of the background objects is randomized across the two intervals of each trial. We control the amount of background reflectance variation by manipulating a statistical model of naturally occurring surface reflectances. For low background object reflectance variation, discrimination thresholds were nearly constant, indicating that observers’ internal noise determines threshold in this regime. As background object reflectance variation increases, its effects start to dominate performance. A model based on signal detection theory allows us to express the effects of task-irrelevant variation in terms of the equivalent noise, that is relative to the intrinsic precision of the task-relevant perceptual representation. The results indicate that although naturally occurring background object reflectance variation does intrude on the perceptual representation of target object lightness, the effect is modest – within a factor of two of the equivalent noise level set by internal noise.

Lightness Perception in Complex Scenes

Lightness perception is the perception of achromatic surface colors: black, white, and shades of grey. Lightness has long been a central research topic in experimental psychology, as perceiving surface color is an important visual task but also a difficult one due to the deep ambiguity of retinal images. In this article, I review psychophysical work on lightness perception in complex scenes over the past 20 years, with an emphasis on work that supports the development of computational models. I discuss Bayesian models, equivalent illumination models, multidimensional scaling, anchoring theory, spatial filtering models, natural scene statistics, and related work in computer vision. I review open topics in lightness perception that seem ready for progress, including the relationship between lightness and brightness, and developing more sophisticated computational models of lightness in complex scenes. Expected final online publication date for the Annual Review of Vision Science, Volume 7 is September 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Fluctuating environmental light limits number of surfaces visually recognizable by colour

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.

Temporal dynamics of daylight perception: Detection thresholds

Temporal changes in illumination are ubiquitous; natural light, for example, varies in color temperature and irradiance throughout the day. Yet little is known about human sensitivity to temporal changes in illumination spectra. Here, we aimed to determine the minimum detectable velocity of chromaticity change of daylight metamers in an immersive environment. The main stimulus was a continuous, monotonic change in global illumination chromaticity along the daylight locus in warmer (toward lower correlated color temperatures [CCTs]) or cooler directions, away from an adapting base light (CCT: 13,000 K, 6500 K, 4160 K, or 2000 K). All lights were generated by spectrally tunable overhead lamps as smoothest-possible metamers of the desired chromaticities. Mean detection thresholds (for 22 participants) for a fixed duration of 10 seconds ranged from 15 to 2 CIELUV ΔE units, depending significantly on base light CCT and with a significant interaction between CCT and direction of change. Cool changes become less noticeable for progressively warmer base lights and vice versa. For the two extreme base lights, sensitivity to changes toward neutral is significantly lower than for the opposite direction. The results suggest a “neutral bias” in illumination change discriminability, and that typical temporal changes in daylight chromaticity are likely to be below threshold detectability, at least where there are no concomitant overall illuminance changes. These factors may contribute to perceptual stability of natural scenes and color constancy.

A model of lightness perception guided by probabilistic assumptions about lighting and reflectance

Lightness perception is the ability to perceive black, white, and gray surface colors in a wide range of lighting conditions and contexts. This ability is fundamental for any biological or artificial visual system, but it poses a difficult computational problem, and how the human visual system computes lightness is not well understood. Here I show that several key phenomena in lightness perception can be explained by a probabilistic graphical model that makes a few simple assumptions about local patterns of lighting and reflectance, and infers globally optimal interpretations of stimulus images. Like human observers, the model exhibits partial lightness constancy, codetermination, contrast, glow, and articulation effects. It also arrives at human-like interpretations of strong lightness illusions that have challenged previous models. The model's assumptions are reasonable and generic, including, for example, that lighting intensity spans a much wider range than surface reflectance and that shadow boundaries tend to be straighter than reflectance edges. Thus, a probabilistic model based on simple assumptions about lighting and reflectance gives a good computational account of lightness perception over a wide range of conditions. This work also shows how graphical models can be extended to develop more powerful models of constancy that incorporate features such color and depth.

Computational-observer analysis of illumination discrimination

The spectral properties of the ambient illumination provide useful information about time of day and weather. We study the perceptual representation of illumination by analyzing measurements of how well people discriminate between illuminations across scene configurations. More specifically, we compare human performance to a computational-observer analysis that evaluates the information available in the isomerizations of cone photopigment in a model human photoreceptor mosaic. The performance of such an observer is limited by the Poisson variability of the number of isomerizations in each cone. The overall level of Poisson-limited computational-observer sensitivity exceeded that of human observers. This was modeled by increasing the amount of noise in the number of isomerizations of each cone. The additional noise brought the overall level of performance of the computational observer into the same range as that of human observers, allowing us to compare the pattern of sensitivity across stimulus manipulations. Key patterns of human performance were not accounted for by the computational observer. In particular, neither the elevation of illumination-discrimination thresholds for illuminant changes in a blue color direction (when thresholds are expressed in CIELUV ΔE units), nor the effects of varying the ensemble of surfaces in the scenes being viewed, could be accounted for by variation in the information available in the cone isomerizations.

Illumination discrimination for chromatically biased illuminations: Implications for color constancy

We measured discrimination thresholds for illumination changes along different chromatic directions starting from chromatically biased reference illuminations. Participants viewed a Mondrian-papered scene illuminated by LED lamps. The scene was first illuminated by a reference illumination, followed by two comparisons. One comparison matched the reference (the target); the other (the test) varied from the reference, nominally either bluer, yellower, redder, or greener. The participant's task was to correctly select the target. A staircase procedure found thresholds for discrimination of an illumination change along each axis of chromatic change. Nine participants completed the task for five different reference illumination conditions (neutral, blue, yellow, red, and green). We find that relative discrimination thresholds for different chromatic directions of illumination change vary with the reference illumination. For the neutral reference, there is a trend for thresholds to be highest in the bluer illumination-change direction, replicating our previous reports of a "blue bias" for neutral reference illuminations. For the four chromatic references (blue, yellow, red, and green), the change in illumination toward the neutral reference is less well discriminated than changes in the other directions: a "neutral bias." The results have implications for color constancy: In considering the stability of surface appearance under changes in illumination, both the starting chromaticity of the illumination and direction of change must be considered, as well as the chromatic characteristics of the surface reflectance ensemble. They also suggest it will be worthwhile to explore whether and how the human visual system has internalized the statistics of natural illumination changes.

Color Perception: Objects, Constancy, and Categories

Color has been scientifically investigated by linking color appearance to colorimetric measurements of the light that enters the eye. However, the main purpose of color perception is not to determine the properties of incident light, but to aid the visual perception of objects and materials in our environment. We review the state of the art on object colors, color constancy, and color categories to gain insight into the functional aspects of color perception. The common ground between these areas of research is that color appearance is tightly linked to the identification of objects and materials and the communication across observers. In conclusion, we argue that research should focus on how color processing is adapted to the surface properties of objects in the natural environment in order to bridge the gap between the known early stages of color perception and the subjective appearance of color.

The perception of colour and material in naturalistic tasks

Perceived object colour and material help us to select and interact with objects. Because there is no simple mapping between the pattern of an object's image on the retina and its physical reflectance, our perceptions of colour and material are the result of sophisticated visual computations. A long-standing goal in vision science is to describe how these computations work, particularly as they act to stabilize perceived colour and material against variation in scene factors extrinsic to object surface properties, such as the illumination. If we take seriously the notion that perceived colour and material are useful because they help guide behaviour in natural tasks, then we need experiments that measure and models that describe how they are used in such tasks. To this end, we have developed selection-based methods and accompanying perceptual models for studying perceived object colour and material. This focused review highlights key aspects of our work. It includes a discussion of future directions and challenges, as well as an outline of a computational observer model that incorporates early, known, stages of visual processing and that clarifies how early vision shapes selection performance.

Illumination discrimination in the absence of a fixed surface-reflectance layout

Previous studies have shown that humans can discriminate spectral changes in illumination and that this sensitivity depends both on the chromatic direction of the illumination change and on the ensemble of surfaces in the scene. These studies, however, always used stimulus scenes with a fixed surface-reflectance layout. Here we compared illumination discrimination for scenes in which the surface reflectance layout remains fixed (fixed-surfaces condition) to those in which surface reflectances were shuffled randomly across scenes, but with the mean scene reflectance held approximately constant (shuffled-surfaces condition). Illumination discrimination thresholds in the fixed-surfaces condition were commensurate with previous reports. Thresholds in the shuffled-surfaces condition, however, were considerably elevated. Nonetheless, performance in the shuffled-surfaces condition exceeded that attainable through random guessing. Analysis of eye fixations revealed that in the fixed-surfaces condition, low illumination discrimination thresholds (across observers) were predicted by low overall fixation spread and high consistency of fixation location and fixated surface reflectances across trial intervals. Performance in the shuffled-surfaces condition was not systematically related to any of the eye-fixation characteristics we examined for that condition, but was correlated with performance in the fixed-surfaces condition.

Lightness matching and perceptual similarity

Lightness constancy is the ability to perceive surface reflectance correctly despite substantial changes in lighting intensity. A classic view is that lightness constancy is the result of a "discounting" of lighting intensity, and this continues to be a prominent view today. Logvinenko and Maloney (2006) have proposed an alternative approach to understanding lightness constancy, in which observers do not make explicit estimates of reflectance, and lightness constancy is instead based on a perceptual similarity metric that depends on both the reflectance and the illuminance of surfaces viewed under different lighting conditions. Here we compare these two views using a novel, free-adjustment reflectance-matching task. We test whether observers can match reflectance in a task where they are free to adjust both the illuminance and the reflectance of the match stimulus over a wide range. We find that observers can match reflectance under these conditions, which supports the view that observers make explicit estimates of reflectance. We also compare performance in this free adjustment task using physical objects and computer-rendered images as stimuli. We find that lightness constancy is good in both cases, but with some evidence of a glow-related artifact with computer-rendered stimuli.

Discrimination of spectral reflectance under environmental illumination

Color constancy is the ability to recover a stable perceptual estimate of surface reflectance, regardless of the lighting environment. However, we know little about how observers make judgments of the surface color of glossy objects, particularly in complex lighting environments that introduce complex spatial patterns of chromatic variation across an object's surface. To address this question, we measured thresholds for reflectance discrimination using computer-rendered stimuli under environmental illumination. In Experiment 1, we found that glossiness and shape had small effects on discrimination thresholds. Importantly, discrimination ellipses extended along the direction in which the chromaticities in the environmental illumination spread. In Experiment 2, we also found that the observers' abilities to judge surface colors were worse in lighting environments with an atypical chromatic distribution.

Determinants of Colour Constancy and the Blue Bias

We investigated several sensory and cognitive determinants of colour constancy across 40 illumination hues. In the first experiment, we measured colour naming for the illumination and for the colour induced by the illumination on the colorimetric grey. Results confirmed that the induced colours are approximately complementary to the colour of the illumination. In the second experiment, we measured colour constancy using achromatic adjustments. Average colour constancy was perfect under the blue daylight illumination and decreased in colour directions away from the blue daylight illumination due to undershooting and a strong blue bias. Apart from this blue bias, colour constancy was not related to illumination discrimination and to chromatic detection measured previously with the same setup and stimuli. We also observed a strong negative relationship between the degree of colour constancy and the consensus of naming the illumination colour. Constancy coincided with a low naming consensus, in particular because bluish illumination colours were sometimes seen as achromatic. Blue bias and category consensus alone explained >68%, and all determinants together explained >94% of the variance of achromatic adjustments. These findings suggest that colour constancy is optimised for blue daylight.

What #theDress reveals about the role of illumination priors in color perception and color constancy

The disagreement between people who named #theDress (the Internet phenomenon of 2015) "blue and black" versus "white and gold" is thought to be caused by individual differences in color constancy. It is hypothesized that observers infer different incident illuminations, relying on illumination "priors" to overcome the ambiguity of the image. Different experiences may drive the formation of different illumination priors, and these may be indicated by differences in chronotype. We assess this hypothesis, asking whether matches to perceived illumination in the image and/or perceived dress colors relate to scores on the morningness-eveningness questionnaire (a measure of chronotype). We find moderate correlations between chronotype and illumination matches (morning types giving bluer illumination matches than evening types) and chronotype and dress body matches, but these are significant only at the 10% level. Further, although inferred illumination chromaticity in the image explains variation in the color matches to the dress (confirming the color constancy hypothesis), color constancy thresholds obtained using an established illumination discrimination task are not related to dress color perception. We also find achromatic settings depend on luminance, suggesting that subjective white point differences may explain the variation in dress color perception only if settings are made at individually tailored luminance levels. The results of such achromatic settings are inconsistent with their assumed correspondence to perceived illumination. Finally, our results suggest that perception and naming are disconnected, with observers reporting different color names for the dress photograph and their isolated color matches, the latter best capturing the variation in the matches.

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.