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Past studies investigating the unique hues only used samples with a relatively high saturation levels under standard illuminants. In this study, 10 observers selected the four samples with unique hues from 40 V6C8 (Value 6 Chroma 8) and 40 V8C4 (Value 8 Chroma 4) Munsell samples under six light sources, comprising three levels of Duv (i.e., 0, −0.02, and −0.04) and two levels of correlated color temperature (i.e., 2700 and 3500 K). Significant differences were found between the two chroma levels for unique blue and yellow, with the hue angles of unique yellow and blue judged using the desaturated samples being significantly different from those defined in CIECAM02. The iso‐lines of unique yellow, blue, and green did not always go through the origin of the a*‐b* or a′‐b′ planes in CIELAB and CAM02‐UCS. Thus, the problems of CIECAM02, CIELAB, and CAM02‐UCS identified in this study need further investigations.

The aim of the research reported by this study was on the one hand to identify what colors were associated with particular words in relation to a specific language (Italian), by portraying them in color stimuli on the screen of a monitor; and on the other hand to verify whether some words of that language denoted colors that were either particularly well defined or confused with others. In an experiment using special software, the subjects were asked to produce colors directly, instead of choosing among a number of colors presented on the screen. The results showed that (i) it is possible to identify the color-stimuli to which the terms of a language refer; that (ii) the “best” colors Giallo (Yellow), Rosso (Red), Blu (Blue), and Verde (Green) which the subjects were requested to produce were very similar to the corresponding unique hues; that (iii) among the mixed hues there were perceptually intermediate colors, that is, ones exactly midway between two consecutive unique colors: Arancione (Orange) and Viola (bluish Purple); that (iv) Turquoise and Lime were clearly positioned in the mental space of color of the participants; and that (v) for Italian speakers some hues coincide: Azzurro (Azure) and Celeste (Cerulean); Arancione (Orange), RossoGiallo (RedYellow) and Carota (Carrot); Lime and GialloVerde (YellowGreen), so that their color terms can be considered synonyms. Our most interesting finding, however, is that for Italian speakers these four mixed colors with their specific names (Lime, Turchese (Turquoise), Viola (bluish Purple) and Arancione (Orange) fall perceptually in the middle of each of the four quadrants formed in the hue circle by the four unique hues. The resulting circle is therefore characterized by eight colors of which four are unique and four are intermediate mixed. It would be advisable to repeat the study cross-culturally to test for possible similarities and differences in color meanings with speakers of different languages. © 2016 Wiley Periodicals, Inc. Col Res Appl, 42, 89–101, 2017

Eight panels were prepared using the most highly chromatic Natural Colour System (NCS) samples for each hue. Each panel consisted of a test hue and two reference hues, the samples representing either mean unique hues (uH) R, Y, B, or G as determined in earlier experiments or intermediate hues half way between them, (iHs) Or, Pp, YG, and BG. Subjects were asked to determine whether they considered it possible to match the test hue with the reference hues. A total of 45 color-normal subjects participated in the study in three separate trials with at least 24 h gap between consecutive trials. The results, with very few exceptions, showed that a match was considered possible for the four iHs based on a mixture of adjacent pairs of uHs, while the majority did not believe uHs could be matched based on amounts of adjacent iHs. Statistical analysis of the test results indicates that responses for the two sets of panels were significantly different (P ∼ 0, df = 539). The results provide support for Hering's uHs concept. However, a number of subjects believed that a mixture of adjacent iHs can result in a match of the reference uHs. Potential causes may include the use of experimental mean unique and intermediate hues and learned facts of colorant mixture. © 2014 Wiley Periodicals, Inc. Col Res Appl, 40, 264–269, 2015

Recently, a line of minimum tint in chromaticity space for sources of illumination of different correlated color temperatures (CCTs) from 2700 K to 6500 K has been reported. This line of minimum tint did not correspond to the line of blackbody radiation implicitly associated with sources of white illumination used in architectural applications. It was noted that chromaticities along the line of minimum tint were not metamers but, rather, should represent, for a given CCT, chromaticities where the neural signals from the two spectral opponent channels were minimized. Earlier work provided a theoretical framework for representing the four unique hues where the neural signals from one spectral opponent channel are minimized. This framework was used here to quantitatively represent the line of minimum tint and then to empirically test whether this representation could predict the amount of tint perceived in six different sources of “white” Illumination.” Based on these results, a provisional model is proposed for describing the tint and the amount of tint perceived in “white” Illumination used in architectural applications. © 2013 Wiley Periodicals, Inc. Col Res Appl, 39, 466–479, 2014

The relationship between the information the visual system gathers at its interface with the outside world and the perceptual reality of four primary hues and the resulting hue circle has been and remains of interest since the second half of the 19th century. Considerable effort has been expended over many decades in determining statistical mean choices of color stimuli that for individuals represent unique hues in given conditions of viewing. In this article, historical and recent data are used to show the present state of knowledge. To have a means of comparison, in this article spectral and display unit stimuli are converted to Munsell hues on basis of dominant or complementary wavelengths of highest chroma data. Relatively good agreement was found between spectral and color sample data, with display data being significantly different in case of unique green. The issue of significant interobserver variability found in all data and its implications are highlighted. Problems with generating simple psychophysical models, particularly related to unique red, are discussed and a brief survey of the current knowledge on neural processing that may lead to unique hue perception is presented. Data still required for a meaningful definition of mean unique hue stimulus data are listed. © 2013 Wiley Periodicals, Inc. Col Res Appl, 39, 279–287, 2014; Published Online 20 March 2013 in Wiley Online Library (wileyonlinelibrary.com). DOI 10.1002/col.21793

I describe complementary colors' physiology and functional roles in color vision, in a three-stage theory (receptor, opponent color, and complementary color stages). 40 specific roles include the complementary structuring of: S and L cones, opponent single cells, cardinal directions, hue cycle structure, hue constancy, trichromatic color mixture, additive/subtractive primaries, two unique hues, color mixture space, uniform hue difference, lightness-, saturation-, and wavelength/hue-discrimination, spectral sensitivity, chromatic adaptation, metamerism, chromatic induction, Helson-Judd effect, colored shadows, color rendering, warm-cool colors, brilliance, color harmony, Aristotle's flight of colors, white-black responsivity, Helmholtz-Kohlrausch effect, rainbows/halos/glories, dichromatism, spectral-sharpening, and trimodality of functions (RGB peaks, CMY troughs whose complementarism adapts functions to illuminant). The 40 specific roles fall into 3 general roles: color mixture, color constancy, and color perception. Complementarism evidently structures much of the visual process. Its physiology is evident in complementarism of cones, and opponent single cells in retina, LGN, and cortex. Genetics show our first cones were S and L, which are complementary in daylight D65, giving a standard white to aid chromatic adaptation. M cone later split from L to oppose the nonspectral (red and purple) hues mixed from S+L. Response curves and wavelength peaks of cones L, S, and (S+L), M, closely resemble, and lead to, those of opponent-color chromatic responses y, b, and r, g, a bimodal system whose summation gives spectral-sharpened trimodal complementarism (RGB peaks, CMY troughs). Spectral sharpening demands a post-receptoral, post-opponent-colors location, hence a third stage. © 2011 Wiley Periodicals, Inc. Col Res Appl, 2011

A novel approach to assessing colour appearance is described. It is based on a new technique—partial hue-match- ing—which allows for measuring colour in terms of compo- nent hues objectively, without resorting to verbal definitions. The new method is believed to have a potential to be as exact as colorimetric techniques. In contrast to classical colour matching, which implies visual equivalence of lights, partial hue-matching is based on judgements of whether two lights that are different in colour have some hue in common. The major difference between classical colour matching and partial hue- matching is that the latter is intransitive, whereas the former is generally believed to be transitive (though see Logvinenko, Symposium on 75 years of the CIE Standard Colorimetric Observer, Vienna, Austria, 2006). Formally, partial hue-match- ing can be described as a reflexive and symmetric binary rela- tion (i.e., tolerance). The theoretical framework of tolerance spaces is used for developing a theory of partial hue- matching. 2011 Wiley Periodicals, Inc. Col Res Appl, 00, 000 - 000, 2011; Published online in Wiley Online Library (wileyonlinelibrary.com). DOI

Background: Studies investigating the effect of rods on unique hue loci in the peripheral retina generally obtain measures at two time points associated with the dark adaptation function ― the cone plateau and the rod plateau. In comparison, this study used a color-naming procedure to identify the loci of unique green and unique yellow as a function of time associated with the entire dark adaptation function. The unique hue loci derived by this procedure were then compared to those obtained directly with a staircase procedure. Method: Hue-scaling functions were obtained for monochromatic stimuli for four observers using the '4 + 1' procedure. Data were collected every 4 min following extinction of a bleaching stimulus. These hue-scaling functions were then converted to uniform appearance diagrams (UADs) to derive unique green and unique yellow loci. Unique green and unique yellow loci were also obtained from the same observers via a staircase procedure at 4―9 min post-bleach (minimal rod input) and after 28 min dark adaptation (maximal rod input). Measurements were made in the peripheral retina at 10° temporal retinal eccentricity and at the fovea. Results: Unique green loci derived from UADs are at longer wavelengths compared to those measured directly with the staircase procedure. In addition, unique green loci derived from UADs show a progressive shift to longer wavelengths as time post-bleach increases; whereas, unique green loci obtained from the staircase procedure differ little between the rod-bleach and no-bleach conditions. Unique yellow loci are similar across both experimental procedures. Conclusion: Unique green loci derived from UADs are not the same as those measured with traditional psychophysical procedures. These differences may be due to the different response criteria used by observers in the color-naming and staircase procedures. The unique green loci obtained from UADs indicate that rod signals shift unique green loci to longer wavelengths as time post-bleach increases. More direct methods need to be employed to determine if this rod effect is valid.

The purpose of this study was to assess whether age-related chromatic sensitivity changes are associated with corresponding changes in hue perception in a large sample of colour-normal observers over a wide age range (n = 185; age range: 18―75 years). In these observers we determined both the sensitivity along the protan, deutan and tritan line; and settings for the four unique hues, from which the characteristics of the higher-order colour mechanisms can be derived. We found a significant decrease in chromatic sensitivity due to ageing, in particular along the tritan line. From the unique hue settings we derived the cone weightings associated with the colour mechanisms that are at equilibrium for the four unique hues. We found that the relative cone weightings (w L /w M and w L /w S ) associated with the unique hues were independent of age. Our results are consistent with previous findings that the unique hues are rather constant with age while chromatic sensitivity declines. They also provide evidence in favour of the hypothesis that higher-order colour mechanisms are equipped with flexible cone weightings, as opposed to fixed weights. The mechanism underlying this compensation is still poorly understood.

It is known that there is a distortion of hue and saturation in the peripheral visual field. In a previous study, when an asymmetric matching paradigm was used, four hues in the blue, red, yellow and green regions of colour space were unchanged and these were referred to as peripherally invariant (Parry et al., J Opt Soc Am A, 23, 2006, 1586). Three of these invariant hues were similar to unique blue, red and yellow. However, for most observers there was a marked difference between unique and invariant green. To investigate this apparent paradox, we have measured unique hues using a range of eccentricities and colourimetric purities. An asymmetric matching and a 4-AFC paradigm were used to establish peripherally invariant and unique hues, respectively. In the asymmetric matching task the observer matched a peripheral spot with a para-foveal spot, for 24 different hues at 18° eccentricity. In the 4-AFC paradigm, 41 hues were presented 20 times at three purities (0.5, 0.75 and 1.0) and three eccentricities (18°, 10° and 1°). The observer had to name the hues as red, blue, green or yellow. Unique hues were found to be constant with eccentricity and purity. The unique green, established with 4-AFC, was found to differ from the invariant green, determined using the matching task. However, red, blue and yellow invariant hues correspond well with unique hues. The data suggest that different mechanisms mediate the matching of green compared with the identification of unique hues. This is similar to the difference between detection and discrimination of spectral stimuli: the detection process is dominated by the cone opponent mechanisms and is most sensitive, whereas more central processes, serving unique hues, influence discrimination.

Unique hue stimuli were determined by male and female observers using two different visual experimental procedures involving Munsell color chips of varying hue but identical chroma and value. The hypothesis was that unique hues can be more reliably established by explicit selection from a series of ordered stimuli than implicitly by hue scaling a series of stimuli in terms of neighboring UHs and this was statistically confirmed. The implicit selections based on long term memory of UHs appears to have been more challenging to observers since variability was increased by nearly 50% compared to when UHs were explicitly selected. The ranges of unique hues selected in the two methods were, however, comparable and no statistically significant difference was found between the results of females and males. The intra-observer variability in picking a stimulus to represent a unique hue, for all observers and averaged for all hues, was approximately 12% of the mean spread of unique hues, confirming that the large inter-observer variability is driven by differences in color vision and perhaps cognitive processes. © 2010 Wiley Periodicals, Inc. Col Res Appl, 2010

Data from ten different experiments involving nearly 600 observers of determination of unique hues are compared. Six experiments involve determination using spectral lights; two use desaturated monitor colors, and the remaining two use color chip sets. Except for unique green, color chips result in narrower ranges of results than spectral lights. Unique green has a surprisingly large range of variation in both spectral light and color chip experiments, followed by red. Comparison of spectral light data indicates that one observer's unique blue can be another's unique green and vice versa, and the same for yellow and green. This finding raises significant questions for color appearance and color space/difference models, as well as philosophy of color. © 2004 Wiley Periodicals, Inc. Col Res Appl, 29, 158–162, 2004;Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.10237

Loci of the four unique hues (red, green, blue, and yellow) on the equiluminant plane on the color display and three preferred colors were obtained from 115 normal trichromats. We sought possible correlations between these measures. Different unique hue loci were not correlated with each other. The three preferred colors were not correlated with each other. We found five combinations of significant correlation between a preferred color and unique hue settings, yet the overall tendency is not very clear. We conclude that individual differences in color appearance measured by unique hues and color preferences measured by asking for favorite colors may not be predicted from each other or even within a category because the differences in the earlier visual mechanisms can be compensated for and these high-level measures can be influenced by learning and experience. © 2004 Wiley Periodicals, Inc. Col Res Appl, 29, 285–291, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20023

General hypothesis for the definition of chromatic-opponency functions are given in a black-box approach to the problem. It is supposed that the color signals in the visual color processing can be factorized into the product of the lightness times a pair of chromatic opponency functions and the whole chromatic processing consists of three independent processes: a linear transformation, a logarithmic compression, and a chromatic opponency actuation. The main chromatic opponency functions, obtainable by very general hypothesis on the symmetry and on the homogeneity degree, are supposed equal to the logarithms of tristimulus-value ratios in a proper reference frame of the tristimulus space. The perceptual chromatic functions, individually with uniform scales, are a linear mixing of the main chromatic opponency functions. The Bezold–Brucke hue shift is not considered. A performance of these hypothesis is successfully realized on the OSA-UCS system, for extra macula vision, and on the chromatic discrimination ellipses, for macular vision. Unique hues are derived from the main chromatic opponency functions of spectral lights. © 2004 Wiley Periodicals, Inc. Col Res Appl, 30, 31–41, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20072

The perception of ten different colors on a CRT display presented across the horizontal meridian of the visual field were measured to determine the range of relevant test stimuli for color zone map measurement. Hue and saturation judgments were used based on the opponent-colors theory. The changes of the unique hue components for eccentric displays of red, yellow, green, and blue fall within the distribution range of previous results obtained using monochromatic lights. Chromatic displays of nearly unique hues with high saturation would be significant as test colors for measurement for a color zone map. © 2003 Wiley Periodicals, Inc. Col Res Appl, 28, 413–424, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.10194

Forty observers determined their unique hues from arrays of Munsell chips in a standard surround under artificial daylight. There was some discrepancy in the results of males and females. Essentially no variability due to age of observer was found. The standard deviation around the total mean was less than 1 Munsell 40 hue step. Simple linear opponent-color a and b values were calculated. The ranges were found to straddle in all but the red color the system axes for the CIE 2°observer, but not for the 10°observer. NCS unique hues determined at similar chroma and lightness values fell in all cases within the ranges. The shifts in cross-over wavelengths of the color-matching functions necessary to match the extreme range values were determined to be between 6–11 nm. The results provide support for an opponent-color system based on subtractions of color-matching functions. They also point to significant variation in color normal observers. © 2001 John Wiley & Sons, Inc. Col Res Appl, 26, 61–66, 2001

Color appearance models, among other things, predict the hue of a stimulus when compared with defined stimuli that represent the four unique hues. Recent studies have indicated that the stimuli representing with high reliability unique hue (UH) percepts vary widely for different color-normal observers. The average yellow and blue UH stimuli for 102 observers, as determined in a recent experiment at medium chroma, differ considerably from the CIECAM02 defined unique hues, based on the Swedish NCS. Wide inter-observer variability precludes color appearance models from accurately predicting, for individual observers, all four unique hue stimuli. However, models should predict accurately those of a well-defined average observer. © 2008 Wiley Periodicals, Inc. Col Res Appl, 33, 505–506, 2008

It is generally thought that Ewald Hering (19th century), or possibly Leonardo da Vinci (16th century), first recognized the concept of four unique hues (blue, green, yellow, red). However, in the Alhambra palaces, Granada, Spain, in a room roped off from tourist traffic, is a stained glass window featuring the four unique hues, built about 1370. © 2006 Wiley Periodicals, Inc. Col Res Appl, 31, 364–365, 2006

Unique hues, as recently determined by 40 observers using Munsell color chips, have been compared to published information on focal hues. While there is good agreement in the case of three hues, there is a significant disagreement (nearly 4 Munsell hue steps) in the case of green. An experiment was performed using mostly identical observers, identical color chips, and identical viewing conditions to have 40 observers determine their focal green hue. While their average unique green hue is located at Munsell Hue 2.75 BG, their average focal green is located at 2.5G, thus being in agreement with the average World Color Survey focal green. The result points to different concepts of the observers for unique green and focal green. © 2001 John Wiley & Sons, Inc. Col Res Appl, 26, 171–172, 2001

A set of possible cone spectral sensitivity functions has been used to obtain combinations of responses that provide good predictions for loci of constant hue, simple criteria for unique hues, and good approximations to the NCS and Munsell schemes for surface colours, and to data on the appearance of spectral colours.

A new color space is developed, based on a model of a trigonally symmetric, planar arrangement of three response vectors, which first separates a visual stimulus via tristimulus values into achromatic and chromatic components and then recombines them. Because three visual response vectors are mutually opposed, the model is called the mutually opposed, trichromatic response (MOTR) model. The MOTR model does not introduce any new visual concepts but rather uses established concepts in an empirically different way. The MOTR model directly represents a color as a combination of two chromatic primaries and one achromatic primary. It is, therefore, particularly useful for halftone color reproduction based on two primary colors plus black, sometimes referred to as 100% GCR (gray component replacement). It is useful also because of its linearity properties between lightness and the chromatic and achromatic contents. The MOTR model's color space is applicable to existing color-order systems and provides a graphic representation often better than CIELAB and CIELUV do. The MOTR model is also consistent with many known visual characteristics such as unique hues, illuminant adaptation, wavelength discrimination, and defective color vision. The model as described herein is limited to the comparison of related colors under a given photopic luminance.