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.

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.

Some familiar objects have a typical color, such as the yellow of a banana. The presence of such objects in a scene is a potential cue to the scene illumination, since the light reflected from them should on average be consistent with their typical surface reflectance. Although there are many studies on how the identity of an object affects how its color is perceived, little is known about whether the presence of a familiar object in a scene helps the visual system stabilize the color appearance of other objects with respect to changes in illumination. We used a successive color matching procedure in three experiments designed to address this question. Across the experiments we studied a total of 6 subjects (2 in Experiment 1, 3 in Experiment 2, and 4 in Experiment 3) with partial overlap of subjects between experiments. We compared measured color constancy across conditions in which a familiar object cue to the illuminant was available with conditions in which such a cue was not present. Overall, our results do not reveal a reliable improvement in color constancy with the addition of a familiar object to a scene. An analysis of the experimental power of our data suggests that if there is such an effect, it is small: less than approximately a change of 0.09 in a constancy index where an absence of constancy corresponds to an index value of 0 and perfect constancy corresponds to an index value of 1.

The purposes of this study were to measure areas of complete spatial summation (i.e., Ricco's area) for S- and L-cone mechanisms and to evaluate whether the sizes of Ricco's area could be explained in terms of either the densities of photoreceptors or ganglion cells. Increment thresholds were measured at the fovea and at 1.5°, 4°, 8°, and 20° in the superior retina using a temporal two-alternative forced-choice procedure. Test stimuli ranging from -0.36 to 4.61 log area (min(2)) were presented on concentric 12.3° adapting and auxiliary fields, which isolated either an S- or L-cone mechanism on the plateau of the respective threshold vs. intensity function. The data indicate that from 0-20° retinal eccentricity, the size of Ricco's area is larger for the S-cone mechanism than the L-cone mechanism, increases monotonically for the L-cone mechanism, and, for both cone mechanisms, increases between 8-20° retinal eccentricity. This latter finding suggests that ganglion cell density rather than cone density defines the size of Ricco's area in the parafoveal and peripheral retina.

Threshold vs. intensity (tvi) functions were measured under conditions in which the slope of the rising branch approximated the deVries-Rose law in order to evaluate the contribution of intrinsic visual noise (dark light, Eigengrau) to age-related elevations in threshold under photopic conditions. Data were obtained from 48 observers (20-88 years) using a temporal 2AFC procedure. The stimulus was centered at 8° nasal retinal eccentricity and consisted of a 560 nm, 14.4' test flash (10 ms) concentric with a steady 500 nm (12.9°) adapting field (13 intensity levels ranging from 0-9 log quanta · sec(-1) · deg(-2)), which resulted in clear scotopic and photopic branches. Photopic thresholds increased linearly with age at a rate of 0.08 log unit per decade at the cornea. The mean slope of the rising portion of the tvi functions (in log-log coordinates) was 0.62, and not correlated with age. Dark light values increased with age, but not significantly. Dark light was a statistically significant predictor of individual differences in absolute photopic threshold, but it is not responsible for age-related increases in threshold under photopic conditions.

Colour constancy assessed by asymmetric simultaneous colour matching usually reveals limited levels of performance in the unadapted eye. Yet observers can readily discriminate illuminant changes on a scene from changes in the spectral reflectances of the surfaces making up the scene. This ability is probably based on judgements of relational colour constancy, in turn based on the physical stability of spatial ratios of cone excitations under illuminant changes. Evidence is presented suggesting that the ability to detect violations in relational colour constancy depends on temporal transient cues. Because colour constancy and relational colour constancy are closely connected, it should be possible to improve estimates of colour constancy by introducing similar transient cues into the matching task. To test this hypothesis, an experiment was performed in which observers made surface-colour matches between patterns presented in the same position in an alternating sequence with period 2 s or, as a control, presented simultaneously, side-by-side. The degree of constancy was significantly higher for sequential presentation, reaching 87% for matches averaged over 20 observers. Temporal cues may offer a useful source of information for making colour-constancy judgements.

The goal of our study was to evaluate colour vision during high-altitude mountain climbing without supplemental oxygen. Two Himalayan expeditions were invited to test their colour perception at both the highest possible altitude and on the largest possible number of subjects. The panel desaturated D15 was used, because only a simple test could be transported to those altitudes. There were 2 evaluations (i.e., 4 eyes) at 7,000 m during the first expedition in 1997, and 3 evaluations (i.e., 6 eyes) at 6,500 m during the second expedition in 1998. The results were in perfect agreement and can be considered practically normal for all 5 mountain climbers.

Object recognition by natural and artificial visual systems benefits from the identification of object boundaries. A useful cue for the detection of object boundaries is the superposition of luminance and color edges. To gain insight into the suitability of this cue for object recognition, we examined convolutional neural network models that had been trained to recognize objects in natural images. We focused specifically on units in the second convolutional layer whose activations are invariant to the spatial phase of a sinusoidal grating. Some of these units were tuned for a nonlinear combination of color and luminance, which is broadly consistent with a role in object boundary detection. Others were tuned for luminance alone, but very few were tuned for color alone. A literature review reveals that V1 complex cells have a similar distribution of tuning. We speculate that this pattern of sensitivity provides an efficient basis for object recognition, perhaps by mitigating the effects of lighting on luminance contrast polarity. The absence of a contrast polarity-invariant representation of chromaticity alone suggests that it is redundant with other representations.

Normal color perception is complicated. But at its initial stage it is relatively simple, since at photopic levels it depends on the activations of just three photoreceptor types: the long- (L-), middle- (M-) and short- (S-) wavelength-sensitive cones. Knowledge of how each type responds to different wavelengths-the three cone spectral sensitivities-can be used to model human color vision and in practical applications to specify color and predict color matches. The CIE has sanctioned the cone spectral sensitivity estimates of Stockman and Sharpe (Stockman and Sharpe, 2000, Vision Res) and their associated measures of luminous efficiency as "physiologically-relevant" standards for color vision (CIE, 2006; 2015). These LMS cone spectral sensitivities are specified at 5- and 1-nm steps for mean "standard" observers with normal cone photopigments and average ocular transparencies, both of which can vary in the population. Here, we provide formulae for the three cone spectral sensitivities as well as for macular and lens pigment density spectra, all as continuous functions of wavelength from 360 to 850 nm. These functions reproduce the tabulated discrete CIE LMS cone spectral sensitivities for 2-deg and 10-deg with little error in both linear and logarithmic units. Furthermore, these formulae allow the easy computation of non-standard cone spectral sensitivities (and other color matching functions) with individual differences in macular, lens and photopigment optical densities, and with spectrally shifted hybrid or polymorphic L- and M-cone photopigments appropriate for either normal or red-green color vision deficient observers.

When participants sort color samples into piles, Boster showed that their color groupings can resemble the "stages" of Kay & McDaniel's model of color term evolution. Boster concluded that both the unfolding of color piles in a sequential color sorting task and the unfolding of color terms according to Kay & McDaniel's model reveal how human beings understand color. If this is correct, then: (1) pile sorts should be reasonably robust across variations in the palette of colors to be sorted, as long as the palette contains good examples of Berlin & Kay's universal color categories, and (2) pile-sorting should be more related to lexical effects and less related to perceptual processes governed by similarity judgments alone. We report three studies on English speakers and Somali speakers (Study 1 only), where participants sorted colors into 2…6 piles. The three studies used varying numbers of palette colors (25, 30, or 145 colors) and varying chromaticity schemes (mainly hue, widely-separated in hue and lightness, or densely distributed at high chroma). We compared human sorting behavior to Kay & McDaniel's model and to the "optimal" patterns of color sorting predicted by Regier's well-formedness statistic, which quantifies the perceived similarity between colors. Neither hypothesis is confirmed by the results of our studies. Thus, we propose that color sorts are determined by pragmatic influences based on heuristics that are inspired by the palette of colors that are available and the task that the viewer is asked to perform.