Adaptation under dichromatic illumination.

Over the years, many CATs (chromatic adaptation transforms) have been developed, such as CMCCAT97, CAT02 and CAT16, to predict the corresponding colors under different illuminants. These CATs were derived from uniform simple stimuli surrounded by a uniform background with a single illuminant. Although some mixed adaptation models have been proposed in literature to predict the adaptation under more than one illuminant, these models are typically limited to a certain scene and exclude the impact of spatial complexity. To investigate chromatic adaptation under more complex conditions, an achromatic matching experiment was conducted with (simultaneously) spatially dichromatic illumination for three illumination color pairs and various spatial configurations. Spatial configuration was found to have an impact on both the degree of adaptation and the equivalent illuminant chromaticity, which is the chromaticity of a single uniform adapting illumination that results in the same corresponding colors as for the dichromatic lighting condition. A preliminary CAT model is proposed that considers the spatial and colorimetric complexity of the illumination.

Road marking BRDF model applicable for a wide range of incident illumination conditions.

To drive safely and comfortably, an adequate contrast between the road surface and road markings is needed. This contrast can be improved by using optimized road illumination designs and luminaires with dedicated luminous intensity distributions, taking advantage of the (retro)reflective characteristics of the road surface and road markings. Since little is known about road markings' (retro)reflective characteristics for the incident and viewing angles relevant for street luminaires, bidirectional reflectance distribution function (BRDF)-values of some retroreflective materials are measured for a wide range of illumination and viewing angles using a luminance camera in a commercial near-field goniophotometer setup. The experimental data are fitted to a new and optimized "RetroPhong" model, which shows good agreement with the data [root mean squared error (R M S E)<0.13, normalized root mean squared error (N R M S E)<0.04, and the normalized cross correlation ratio (N C C)>0.8]. The RetroPhong model is benchmarked with other relevant (retro)reflective BRDF models, and the results suggest that the RetroPhong model is most suitable for the current set of samples and measurement conditions.

Point-by-point visual enhancement with spatially and spectrally tunable laser illumination.

Vision is responsible for most of the information that humans perceive of the surrounding world. Many studies attempt to enhance the visualization of the entire scene by optimizing and tuning the overall illumination spectrum. However, by using a spatially uniform illumination spectrum for the entire scene, only certain global color shifts with respect to a reference illumination spectrum can be realized, resulting in moderate visual enhancement. In this paper, a new visual enhancement method is presented that relies on a spatially variable illumination spectrum. Such an approach can target much more dedicated visual enhancements by optimizing the incident illumination spectrum to the surface reflectance at each position. First, a geometric calibration of the projector-camera system is carried out for determining the spatial mapping from the projected pixel grid to the imaged pixel grid. Secondly, the scene is segmented for implementing the visual enhancement approach. And finally, one of three visual enhancement scenarios is applied by projecting the required color image onto the considered segmented scene. The experimental results show that the visual salience of the scene or region of interest can be efficiently enhanced when our proposed method is applied to achieve colorfulness enhancement, hue tuning, and background lightness reduction.

Predictive performance of the standard and the modified von Kries chromatic adaptation transforms.

To investigate chromatic adaptation and develop chromatic adaptation transforms (CATs), many psychophysical experiments have been conducted to collect corresponding colors (CC) under various illumination conditions. Most modern CATs have been developed based on a database of CC sets collected in the 20th century. More recently, several additional CC sets have been collected by Smet et al., Wei et al., and Ma et al. using memory color matching or achromatic matching methods. The analysis of these CC data indicates that for yellowish (located on or close to the Planckian locus) and greenish illuminations, the short-wave (S) sensitive cones show a lower degree of adaptation compared to the long-wave (L) and medium-wave (M) sensitive cones. This can result in a large prediction error of the standard von Kries CAT, which adopts a single degree of adaptation value for all three cone types. A modified von Kries CAT is proposed that accounts for these differences between the L-, M- and S-cone signals by applying a compression to the rescaling factor for the S-cones. It outperforms the standard von Kries CAT for the Breneman-C, Smet, Wei, and Ma data, while for other data sources the two CATs have similar performance.

Using Smooth Metamers to Estimate Color Appearance Metrics for Diverse Color-Normal Observers.

Color-normal subjects sometimes disagree about metameric matches involving highly structured SPDs, because their cone fundamentals differ slightly, but non-negligibly. This has significant implications for the design of light sources and displays, so it should be estimated. We propose a broadly applicable estimation method based on a simple adaptive "front-end" interface that can be used with any selected standard color appearance model. The interface accepts, as input, any set of color matching functions for the individual subject (for example, these could be that person's cone response functions) and also the associated tristimulus values for the test stimulus and also for the reference stimulus (i.e. reference white). The interface converts this data into tristimulus values of the form used by the selected color appearance model (which could, for example, be X, Y, Z), while also carrying out the needed transform, which is based on an estimate of the subject's likely previous long-term adaptations to their unique cone fundamentals. The selected standard color appearance model then provides color appearance data that is an estimate of the color appearance of the test stimulus, for that individual subject. This information has the advantage of being interpretable within that model's well-known color space. The adaptive front end is based on the fact that, for any selected input SPD and the subject's unique color matching functions, there can be many different SPDs that are metameric for that individual. Since observer-to-observer color perception differences are minimized for spectrally smooth SPDs, smooth metamers predict color appearances reasonably accurately.

CAM18sl brightness prediction for unrelated saturated stimuli including age effects.

Modelling the influence of age on the perception of brightness of visual stimuli is an important topic for indoor and outdoor lighting. As people get older, the transmittance of the ocular media becomes lower, especially in the blue wavelength region. This paper reports on an experimental study aiming to evaluate how the brightness perception of red and blue stimuli is affected by the age of the observer. A matching experiment has been set up in which both young (25 years old on average) and older (70 years old on average) adult observers had to match the brightness of a blue stimulus with the brightness of a red stimulus, both surrounded by a dark background (unrelated stimuli). A significant difference in brightness perception between the two groups of observers was found. In particular, older people report a decrease in brightness perception for the blue stimuli compared to younger people. The results show that the brightness correlate of the colour appearance model CAM18sl (applied with zero luminance background) adequately predicts the matching results of young observers, but failed to predict the results obtained by the older observers. As CAM18sl is built on cone fundamentals which include the transmittance of the ocular media and consider the age of the observer as an input parameter, the authors developed the idea to substitute the cone fundamentals for a young observer by the cone fundamentals for a 70 years old observer. This updated CAM18sl performed very well for the older observer as well, on condition that the transmittance of the ocular media is isolated and kept out of the normalization of the cone fundamentals.

Color appearance model incorporating contrast adaptation - implications for individual differences in color vision.

Color appearance models use standard color matching functions to derive colorimetric information from spectral radiometric measurements of a visual environment, and they process that information to predict color perceptual attributes such as hue, chroma and lightness. That processing is usually done by equations with fixed numerical coefficients that were predetermined to yield optimal agreement for a given standard observer. Here we address the well-known fact that, among color-normal observers, there are significant differences of color matching functions. These cause disagreements between individuals as to whether certain colors match, an important effect that is often called observer metamerism. Yet how these individual sensitivity differences translate into differences in perceptual metrics is not fully addressed by many appearance models. It might seem that appearance could be predicted by substituting an individual's color matching functions into an otherwise-unchanged color appearance model, but this is problematic because the model's coefficients were not optimized for the new observer. Here we explore a solution guided by the idea that processes of adaptation in the visual system tend to compensate color perception for differences in cone responses and consequent color matching functions. For this purpose, we developed a simple color appearance model that uses only a few numerical coefficients, yet accurately predicts the perceptual attributes of Munsell samples under a selected standard lighting condition. We then added a feedback loop to automatically adjust the model coefficients, in response to switching between cone fundamentals simulating different observers and color matching functions. This adjustment is intended to model long term contrast adaptation in the vision system by maintaining average overall color contrast levels. Incorporating this adaptation principle into color appearance models could allow better assessments of displays and illumination systems, to help improve color appearances for most observers.

Effect of adapting field size on chromatic adaptation.

The human visual system adapts to changes in white tone of the illumination to maintain approximately the same object color appearance. Chromatic adaptation transforms (CAT) were developed to predict corresponding colors, which are colors that look the same under a wide range of illuminants. However, existing CATs fail to accurately predict corresponding colors, particularly under colored illumination, because of an inaccurate estimation of the degree of adaptation. In this study, the impact of the adapting field size on the degree of adaptation was investigated. A memory color matching experiment was conducted, in a real scene, with the background adapting field varying in the field of view, luminance and chromaticity to provide data for the development of a more comprehensive CAT. Results show that a larger field of view leads to a more complete adaptation, despite a much lower background luminance.

Impact of the starting point chromaticity on memory color matching accuracy.

In this study, the impact of starting point chromaticity and number of observers on memory color matching results was investigated. Matching data were obtained for 3 objects (neutral grey cube, yellow lemon and green apple) under a neutral white and a yellow background illumination. Memory color matchings were made for ten starting points of which eight chromaticities were symmetrically distributed along the hue circle and centered at the equal energy white (EEW) chromaticity of the neutral white background illumination; one starting point at the EEW chromaticity and one with the same chromaticity as the background. The matching track from starting point to the memory matched chromaticity was also recorded. It did not tend to cross over the central region towards the complementary hue, especially for experienced observers. The results also demonstrated a significant starting point bias, whereby the matched chromaticities were biased towards the chromaticity of the starting point. Starting point bias can be minimized by selecting three starting points symmetrically distributed around the expected memory color chromaticity. Furthermore, at least, ten observers are needed to achieve stable results for the grey cube and yellow lemon. For the green apple, the results are less conclusive and around 40 observers would be needed to obtain a stable average estimate for the chromaticity of the memory color. The large inter-observer variation may result from cultural differences or from natural variations in the "green" apple appearance. This study provides a well-founded guidance for future application of the memory color matching method.

Tuning color and saving energy with spatially variable laser illumination.

Previous studies have shown that the radiant flux that needs to be emitted by an illumination system, can be significantly reduced by optimizing its spectral power distribution to the object reflectance spectra, without inducing perceptible chroma or hue shifts of the illuminated objects. In this paper, the idea is explored to vary the spectral power distribution at different positions in the illuminated scene, in order to tailor the color appearance of objects. For this, a spatially variable, laser diode based illumination system is considered with three primaries and large color gamut. The color rendering performance of the illumination system is quantified via the IES TM-30-2018 method. It is shown that it is possible to reach the maximal color gamut score that is theoretically allowed by the corresponding color fidelity score. This is a unique property of an illumination system with a spatially variable spectral power distribution. The radiant flux requirements of this laser diode based illumination system are theoretically investigated for various color rendering settings, showing reduced power requirements for higher color gamut. The possibility to tune color rendering is also experimentally demonstrated with a set-up that consists of a commercially available laser projector with a hyperspectral camera. By including a feedback optimization algorithm, it is possible to reach the targeted color rendering performance.

Methods for Assessing Quantity and Quality of Illumination.

Human vision provides useful information about the shape and color of the objects around us. It works well in many, but not all, lighting conditions. Since the advent of human-made light sources, it has been important to understand how illumination affects vision quality, but this has been surprisingly difficult. The widespread introduction of solid-state light emitters has increased the urgency of this problem. Experts still debate how lighting can best enable high-quality vision-a key issue since about one-fifth of global electrical power production is used to make light. Photometry, the measurement of the visual quantity of light, is well established, yet significant uncertainties remain. Colorimetry, the measurement of color, has achieved good reproducibility, but researchers still struggle to understand how illumination can best enable high-quality color vision. Fortunately, in recent years, considerable progress has been made. Here, we summarize the current understanding and discuss key areas for future study.

Study of chromatic adaptation using memory color matches, Part I: neutral illuminants.

Twelve corresponding color data sets have been obtained using the long-term memory colors of familiar objects as target stimuli. Data were collected for familiar objects with neutral, red, yellow, green and blue hues under 4 approximately neutral illumination conditions on or near the blackbody locus. The advantages of the memory color matching method are discussed in light of other more traditional asymmetric matching techniques. Results were compared to eight corresponding color data sets available in literature. The corresponding color data was used to test several linear (von Kries, RLAB, etc.) and nonlinear (Hunt & Nayatani) chromatic adaptation transforms (CAT). It was found that a simple two-step von Kries, whereby the degree of adaptation D is optimized to minimize the DEu'v' prediction errors, outperformed all other tested models for both memory color and literature corresponding color sets, whereby prediction errors were lower for the memory color sets. The predictive errors were substantially smaller than the standard uncertainty on the average observer and were comparable to what are considered just-noticeable-differences in the CIE u'v' chromaticity diagram, supporting the use of memory color based internal references to study chromatic adaptation mechanisms.

Study of chromatic adaptation using memory color matches, Part II: colored illuminants.

In a previous paper, 12 corresponding color data sets were derived for 4 neutral illuminants using the long-term memory colours of five familiar objects. The data were used to test several linear (one-step and two-step von Kries, RLAB) and nonlinear (Hunt and Nayatani) chromatic adaptation transforms (CAT). This paper extends that study to a total of 156 corresponding color sets by including 9 more colored illuminants: 2 with low and 2 with high correlated color temperatures as well as 5 representing high chroma adaptive conditions. As in the previous study, a two-step von Kries transform whereby the degree of adaptation D is optimized to minimize the DEu'v' prediction errors outperformed all other tested models for both memory color and literature corresponding color sets, whereby prediction errors were lower for the memory color set. Most of the transforms tested, except the two- and one-step von Kries models with optimized D, showed large errors for corresponding color subsets that contained non-neutral adaptive conditions as all of them tended to overestimate the effective degree of adaptation in this study. An analysis of the impact of the sensor space primaries in which the adaptation is performed was found to have little impact compared to that of model choice. Finally, the effective degree of adaptation for the 13 illumination conditions (4 neutral + 9 colored) was successfully modelled using a bivariate Gaussian in a Macleod-Boyton like chromaticity diagram.

A simple principled approach for modeling and understanding uniform color metrics.

An important goal in characterizing human color vision is to order color percepts in a way that captures their similarities and differences. This has resulted in the continuing evolution of "uniform color spaces," in which the distances within the space represent the perceptual differences between the stimuli. While these metrics are now very successful in predicting how color percepts are scaled, they do so in largely empirical, ad hoc ways, with limited reference to actual mechanisms of color vision. In this article our aim is to instead begin with general and plausible assumptions about color coding, and then develop a model of color appearance that explicitly incorporates them. We show that many of the features of empirically defined color order systems (those of Munsell, Pantone, NCS, and others) as well as many of the basic phenomena of color perception, emerge naturally from fairly simple principles of color information encoding in the visual system and how it can be optimized for the spectral characteristics of the environment.

Impact of cross-regional differences on color rendition evaluation of white light sources.

In a study, involving laboratories from seven geographic regions, the memory colors of eleven familiar objects were investigated. Based on that study, one global and seven regional memory color rendition indices (MCRIs) are created and the impact of cross-regional differences on the evaluation of color rendition was investigated. A first analysis focuses on the impact on MCRI index values by comparing the regional index values, calculated for 401 light sources, with those of the global index. A second analysis examines the impact on predictive performance in terms of the visual appreciation and naturalness of rendered objects colors as evaluated in respectively twenty-one and fifteen experiments published in literature. Both analyses show that, although there are small differences in absolute level of color rendition, the regional metrics are generally comparable in terms of predicting light source rank order and correlation with visual data. Therefore, ànd considering between-region variability to be smaller than or of the same size as the within-region variability, a globally valid memory color rendition metric can be proposed without introducing substantial errors. Finally, Smet's Rm index, obtained using real objects, is suggested as a good approximation to that globally valid metric.

Development of the IES method for evaluating the color rendition of light sources.

We have developed a two-measure system for evaluating light sources' color rendition that builds upon conceptual progress of numerous researchers over the last two decades. The system quantifies the color fidelity and color gamut (change in object chroma) of a light source in comparison to a reference illuminant. The calculations are based on a newly developed set of reflectance data from real samples uniformly distributed in color space (thereby fairly representing all colors) and in wavelength space (thereby precluding artificial optimization of the color rendition scores by spectral engineering). The color fidelity score R(f) is an improved version of the CIE color rendering index. The color gamut score R(g) is an improved version of the Gamut Area Index. In combination, they provide two complementary assessments to guide the optimization of future light sources. This method summarizes the findings of the Color Metric Task Group of the Illuminating Engineering Society of North America (IES). It is adopted in the upcoming IES TM-30-2015, and is proposed for consideration with the International Commission on Illumination (CIE).

Chromaticity of unique white in illumination mode.

The chromaticity of unique white viewed in illumination mode and under dark adapted conditions was investigated for 3 luminance levels (200, 1000 and 2000 cd/m2) using a unique white setting method. Unique white was found to encompass a rather large region in color space located slightly below the blackbody locus and centered around a CCT of 6600 K. Luminance level was found to have no significant effect on the mean unique white chromaticity. The high and low end points of the CIE class A and B white regions respectively under- and overestimate the chromaticity region perceived as white. Agreement along the Duv direction was quite good. However, another Duv related limit associated with white lighting (|Duv|≤5.4e-3) was found to be on the small side, especially for chromaticity values below the blackbody locus. The results for unique white viewed in illumination mode were compared to those reported for object mode presentation. Overall they were very comparable, although a statistical analysis does show a (just) significant effect of stimulus presentation mode for high (il)luminance levels. However, no such effect could be established at the individual observer level. Therefore, it was concluded that unique white chromaticity is essentially the same for both illumination and object mode stimulus presentation, at least under dark adapted viewing conditions.

Brightness prediction of different sized unrelated self-luminous stimuli.

In a series of magnitude estimation experiments, the effect of the size of a circular stimulus varying from 1° to 30° field of view on the perception of brightness has been investigated for unrelated self-luminous stimuli. A clear, hue independent, size effect on brightness was found. Based on a simple modification of the recently developed Color Appearance Model CAM15u, the brightness of different sized unrelated self-luminous stimuli was adequately predicted. The modified brightness prediction performs much better than existing predictions and has been validated by a separate validation experiment.

Experimental driven modelling of the color appearance of unrelated self-luminous stimuli: CAM15u.

Based on an extensive magnitude estimation experiment, a new color appearance model for unrelated self-luminous stimuli, CAM15u, has been designed. With the spectral radiance of the stimulus as unique input, the model predicts the brightness, hue, colorfulness, saturation and amount of white. The main features of the model are the use of the CIE 2006 cone fundamentals, the inclusion of an absolute brightness scale and a very simple calculation procedure. The CAM15u model performs much better than existing models and has been validated by a validation experiment. The model is applicable to unrelated self-luminous stimuli with an angular extent of 10° and a photopic, but non-glare-inducing, luminance level.

Predicting the brightness of unrelated self-luminous stimuli.

In a magnitude estimation experiment, twenty observers rated the brightness of several unrelated, self-luminous stimuli surrounded by a dark background. The performance of a number of existing vision models, color appearance models and models based on the concept of equivalent luminance in predicting brightness has been investigated. Due to a severe underestimation of the Helmholtz-Kohlrausch effect, none of the models performed acceptable. Increasing the weight of the colorfulness contribution to the brightness attribute in the CAM97u model results in a very good correlation between the model predictions and the visually perceived brightness. Finally the experimental results and the brightness prediction from the modified model CAM97u,m are verified through a matching experiment and a validation magnitude estimation experiment.