Unique hue data for colour appearance models. Part III: Comparison with NCS unique hues

In this study, Swedish Natural Color System (NCS) unique hue data were used to evaluate the performance of unique hue predictions by the CIECAM02 colour appearance model. The colour appearance of 108 NCS unique hue stimuli was predicted using CIECAM02, and their distributions were represented in a CIECAM02 a_c–b_c chromatic diagram. The best‐fitting line for each of the four unique hues was found using orthogonal distance regression in the a_c–b_c chromatic diagram. Comparison of these predicted unique hue lines (based on the NCS data) with the default unique hue loci in CIECAM02 showed that there were significant differences in both unique yellow (UY) and unique blue (UB). The same tendency was found for hue uniformity: hue uniformity is worse for UY and UB stimuli in comparison with unique red (UR) and unique green (UG). A comparison between NCS unique hue stimuli and another set of unique hue stimuli (obtained on a calibrated cathode ray tube) was conducted in CIECAM02 to investigate possible media differences that might affect unique hue predictions. Data for UY and UB are in very good agreement; largest deviations were found for UR. © 2014 Wiley Periodicals, Inc. Col Res Appl, 40, 256–263, 2015     

Unique hue data for colour appearance models. Part II: Chromatic adaptation transform

Unique hue settings of 185 observers under three room‐lighting conditions were used to evaluate the accuracy of full and mixed chromatic adaptation transform models of CIECAM02 in terms of unique hue reproduction. Perceptual hue shifts in CIECAM02 were evaluated for both models with no clear difference using the current Commission Internationale de l'Éclairage (CIE) recommendation for mixed chromatic adaptation ratio. Using our large dataset of unique hue data as a benchmark, an optimised parameter is proposed for chromatic adaptation under mixed illumination conditions that produces more accurate results in unique hue reproduction. © 2011 Wiley Periodicals, Inc. Col Res Appl, 2013     

Experimental object color unique hue data for the mean observer for color appearance modeling

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     

Unique hue data and CIECAM02: A comment on Xiao et al

This letter to the editor notes the offsets from the origin of unique hue loci in the recent article, Unique Hue Data for Colour Appearance Models. Part III: Comparison with NCS Unique Hues by Xiao et al. [Color Res Appl 2015;40:256–263] and suggests that modifications to the cone response function in CIECAM02 be explored. © 2015 Wiley Periodicals, Inc. Col Res Appl, 2015     

A theory of unique hues and colour categories in the human colour vision

A novel approach to assessing colour appearance is described. It is based on a new technique—partial hue‐matching—which allows for measuring colour in terms of component 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‐matching can be described as a reflexive and symmetric binary relation (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, 2011     

Cognitive comparison of unique and intermediate hues

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     

A comparison of colour appearance for surface colours between outdoor and indoor environments

Psychophysical experiments of colour appearance, in terms of lightness, colourfulness, and hue, were conducted outdoors and indoors to investigate whether there was any difference in colour appearance between outdoor and indoor environments. A panel of 10 observers participated in the outdoor experiment, while 13 observers took part in the indoor experiment. The reference white had an average luminance of 12784 cd/m² in the outdoor experiment and 129 cd/m² in the indoor experiment. Test colours included 42 colour patches selected from the Practical Coordinate Color System to achieve a reasonable uniform distribution of samples in CIECAM02. Experimental results show that for both outdoor and indoor environments, there was good agreement between visual data and predicted values by CIECAM02 for the three colour appearance scales, with the coefficient of variation values all lower than 25 and the R² values all higher than 0.73, indicating little difference in the three dimensions of colour appearance between indoor and outdoor viewing conditions. Experimental data also suggest that the observers were more sensitive to variation in lightness for grayish colours than for highly saturated colours, a phenomenon that seems to relate with the Helmholtz-Kohlrausch effect. This phenomenon was modeled for predicting perceived lightness (J′) using the present experimental data. The new J′ model was tested using three extra sets of visual data obtained both outdoors and indoors, showing good predictive performance of the new model, with an average coefficient of variation of 14, an average R² of 0.88, and an average STRESS index of 14.18.     

Changes in colour appearance of a large display in various surround ambient conditions

This article focuses on the change in colour appearance of a large display arising from various illumination conditions. Nine experimental phases were conducted according to different surround conditions including dark, indoor, and outdoor conditions. Each of the presented test colours was assessed by 10 observers using a magnitude estimation method. The surrounds used in all phases were divided into two groups: excluding and including veiling glare. Additionally, the effect due to different sizes of both stimuli and surround was investigated. Diverse visual effects were examined and reported. Finally, the visual colour appearance data were used to test the CIECAM02 colour appearance model. © 2010 Wiley Periodicals, Inc. Col Res Appl, 2010     

Dynamic cone response functions for models of colour appearance

The CIECAM97s type of colour appearance models results in some changes in hue and saturation for series of colours of constant chromaticity but changing luminance factor. To keep hue and saturation constant for such series, a model in which the dynamic cone response is based on a power function has been developed. By optimizing its parameters, its correlates of hue, lightness, colourfulness, brightness, and saturation perform nearly as well as those of CIECAM97s. A similar performance is achieved in a modified power model, which is more physiologically plausible. © 2003 Wiley Periodicals, Inc. Col Res Appl, 28, 82–88, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.10128     

Individual differences of unique hue loci and their relation to color preferences

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     

A comprehensive model of colour appearance for related and unrelated colours of varying size viewed under mesopic to photopic conditions

CIE has recommended two previous appearance models, CIECAM97s and CIECAM02. However, these models are unable to predict the appearance of a comprehensive range of colours. The purpose of this study is to describe a new, comprehensive colour appearance model, which can be used to predict the appearance of colours under various viewing conditions that include a range of stimulus sizes, levels of illumination that range from scotopic through to photopic, and related and unrelated stimuli. In addition, the model has a uniform colour space that provides a colour‐difference formula in terms of colour appearance parameters. © 2016 Wiley Periodicals, Inc. Col Res Appl, 42, 293–304, 2017     

An investigation of colour appearance for unrelated colours under photopic and mesopic vision

Data were obtained for the colour appearance of unrelated colours under photopic and mesopic conditions. The effects of changes in luminance level and stimulus size were investigated. The method used was magnitude scaling of brightness, colourfulness, and hue. Two stimulus sizes (10° and 0.5°) and four starting luminance levels (60, 5, 1, and 0.1, cd/m²) were used. The results at 0.1 cd/m² had large variations, so data were obtained for two additional stimulus sizes (1° and 2°) at this luminance level. Ten observers judged 50 unrelated colours. A total of 17,820 estimations were made. The observations were carried out in a completely darkened room, after 20 min adaptation; each test colour was presented on its own. Brightness and colourfulness were found to decrease with decreases of both luminance level and stimulus size. The CAM97u model predicted brightness more accurately than CIECAM02 but gave worse performance in predicting colorfulness. For hue, CAM97u and CIECAM02 both gave satisfactory predictions. Using the brightness correlate from CAM97u, a new colour‐appearance model based on CIECAM02 was developed specifically for unrelated colours under photopic and mesopic conditions, with parameters to allow for the effects of luminance level and stimulus size. © 2011 Wiley Periodicals, Inc. Col Res Appl, 2011;     

Optimum solution of the CIECAM02 yellow–blue and purple problems

Brill [Color Res Appl 2006;31:142‐145] and Brill and Süsstrunk [Color Res Appl 2008;33:424‐426] found that CIECAM02 has the yellow–blue and purple problems and gave partial solutions to them. In this article we model the optimum solution to the yellow–blue and purple problems simultaneously as a constrained non‐linear optimization problem. An optimum solution resulting in a new CAT02 matrix is numerically obtained. This new matrix satisfies the nesting rule and performs better than the Hunt‐Pointer‐Estévez (HPE) matrix in predicting both corresponding colours and colour appearance data sets. Specifically, it was found that the new and HPE matrices performed significantly different on nine (out of 21) corresponding colour data sets and on all corresponding colours data sets as a whole. © 2014 Wiley Periodicals, Inc. Col Res Appl, 40, 491–503, 2015     

What scene information is needed for models of colour appearance in the natural world?

Colorimetry is an essential tool in every part of colour. This article looks over our shoulders at the colour research of Maxwell, Wright, Land and Wyszecki to build a framework for colour. Then, the article looks forward to the needs of digital imaging's future. Colour is the fusion of today's imaging technology with our understanding of colour. Molecular physical chemistry describes the light–matter interactions, while human colour is controlled by neurons that compare light from the entire scene, covering a nearly 180° visual angle. This article's question asks about the information required by a future Model of Colour Appearance that is able to predict any scene: all natural scenes and any experimental display.     

Determination of constant Hue Loci for a CRT gamut and their predictions using color appearance spaces

A colorimetrically characterized computer-controlled CRT display was used to determine 24 loci of constant perceived hue for pseudo-object related stimuli, sampling the display's interior color gamut at constant lightness and the edge of its gamut at variable lightness. Nine observers performed three replications generating matching data at 132 positions. the constant hue loci were used to evaluate the correlation between perceived hue and hue angle of CIELAB, CIELUV, Hunt, and Nayatani color appearance spaces. the CIELAB, CIELUV, and Hunt spaces exhibited large errors in the region of the blue CRT primary, while the Nayatani and CIELUV spaces produced large errors in the region of the red primary for constant lightness stimuli. Along the edge of the CRT's color gamut (variable lightness stimuli), all the spaces had a similar trend, large errors in the cyan region. the differences in performance between the four spaces were not statistically significant for the constant lightness stimuli. For the variable lightness stimuli, CIELAB and CIELUV had statistically superior performance in comparison with the Nayatani space and equal performance in comparison with the Hunt space. It was concluded that for imaging applications, a new color appearance space needs to be developed that will produce small hue error artifacts when used for gamut mapping along loci of constant hue angle. © 1995 John Wiley & Sons, Inc.     

A study of colour emotion and colour preference. Part I: Colour emotions for single colours

This article classifies colour emotions for single colours and develops colour‐science‐based colour emotion models. In a psychophysical experiment, 31 observers, including 14 British and 17 Chinese subjects assessed 20 colours on 10 colour‐emotion scales: warm–cool, heavy–light, modern–classical, clean–dirty, active–passive, hard–soft, tense–relaxed, fresh–stale, masculine–feminine, and like–dislike. Experimental results show no significant difference between male and female data, whereas different results were found between British and Chinese observers for the tense–relaxed and like–dislike scales. The factor analysis identified three colour‐emotion factors: colour activity, colour weight, and colour heat. The three factors agreed well with those found by Kobayashi and Sato et al. Four colour‐emotion models were developed, including warm–cool, heavy–light, active–passive, and hard–soft. These models were compared with those developed by Sato et al. and Xin and Cheng. The results show that for each colour emotion the models of the three studies agreed with each other, suggesting that the four colour emotions are culture‐independent across countries. © 2004 Wiley Periodicals, Inc. Col Res Appl, 29, 232–240, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20010     

Colour‐appearance modeling using feedforward networks with Bayesian regularization method. Part II: Reverse model

In Part I of this article, the development of a multilayer perceptrons feedforward artificial neural network model to predict colour appearance from colorimetric values was reported. Bayesian regularization was employed for the training of the network. In this part of the article, the reverse model, that is, the perdition of colorimetric values from the colour appearance attributes is reported using the same neural network design methodology developed in Part I. This study should contribute to the building of an artificial neural network–based colour appearance prediction, both forward and reverse, using the most comprehensive LUTCHI colour appearance data sets for training and testing. Good prediction accuracy and generalization ability were obtained using the neural networks built in the study. Because the neural network approach is of a black‐box type, colour appearance prediction using this method should be easier to apply in practice. © 2002 Wiley Periodicals, Inc. Col Res Appl, 27, 116–121, 2002; DOI 10.1002/col.10030     

A study of colour emotion and colour preference. Part II: Colour emotions for two‐colour combinations

Eleven colour‐emotion scales, warm–cool, heavy–light, modern–classical, clean–dirty, active–passive, hard–soft, harmonious–disharmonious, tense–relaxed, fresh–stale, masculine–feminine, and like–dislike, were investigated on 190 colour pairs with British and Chinese observers. Experimental results show that gender difference existed in masculine–feminine, whereas no significant cultural difference was found between British and Chinese observers. Three colour‐emotion factors were identified by the method of factor analysis and were labeled “colour activity,” “colour weight,” and “colour heat.” These factors were found similar to those extracted from the single colour emotions developed in Part I. This indicates a coherent framework of colour emotion factors for single colours and two‐colour combinations. An additivity relationship was found between single‐colour and colour‐combination emotions. This relationship predicts colour emotions for a colour pair by averaging the colour emotions of individual colours that generate the pair. However, it cannot be applied to colour preference prediction. By combining the additivity relationship with a single‐colour emotion model, such as those developed in Part I, a colour‐appearance‐based model was established for colour‐combination emotions. With this model one can predict colour emotions for a colour pair if colour‐appearance attributes of the component colours in that pair are known. © 2004 Wiley Periodicals, Inc. Col Res Appl, 29, 292–298, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20024     

A study of colour emotion and colour preference. Part III: Colour preference modeling

In this study three colour preference models for single colours were developed. The first model was developed on the basis of the colour emotions, clean–dirty, tense–relaxed, and heavy–light. In this model colour preference was found affected most by the emotional feeling “clean.” The second model was developed on the basis of the three colour‐emotion factors identified in Part I, colour activity, colour weight, and colour heat. By combining this model with the colour‐science‐based formulae of these three factors, which have been developed in Part I, one can predict colour preference of a test colour from its colour‐appearance attributes. The third colour preference model was directly developed from colour‐appearance attributes. In this model colour preference is determined by the colour difference between a test colour and the reference colour (L*, a*, b*) = (50, ?8, 30). The above approaches to modeling single‐colour preference were also adopted in modeling colour preference for colour combinations. The results show that it was difficult to predict colour‐combination preference by colour emotions only. This study also clarifies the relationship between colour preference and colour harmony. The results show that although colour preference is strongly correlated with colour harmony, there are still colours of which the two scales disagree with each other. © 2004 Wiley Periodicals, Inc. Col Res Appl, 29, 381–389, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20047     

Computational production of colour harmony. Part 2: Experimental evaluation of a tool for gui colour scheme creation

Although webpage and computer interface designers generally have little experience at generating effective colour schemes, colour selection appears only rarely in user interface design literature. This article describes the experimental evaluation of an algorithmic technique that applies colour harmony rules to the selection of colour schemes for computer interfaces and web pages. The technique uses a genetic algorithm to evolve colour schemes; the evolutionary path is determined by a quantitative colour harmony evaluation function. Our technique first creates abstract colour schemes by applying those rules to specific features of the interface or web page; the user then holistically modifies the scheme's overall colour cast, overall saturation, and light–dark distribution, producing colourings that are both harmonious and usable. We demonstrate experimentally that the software is relatively simple to use and produces colourings that are well‐received by humans. In an earlier article, the criteria for a colour harmony tool for computer interfaces and websites were described and used in the design of the Colour Harmoniser, our software implementation of a system that is based on classical rules of colour harmony, adapted and extended to suit graphical user interfaces. In this article, we describe two sets of experiments that have demonstrated the usability and effectiveness of the Colour Harmoniser tool, compared with standard methods of colour selection. These experiments suggest that the tool functions somewhat more effectively than we originally anticipated, producing colour schemes that were rated more highly on several quality scales than those produced by random choice, by humans who self‐classify as nonartists, and by humans who self‐classify as artists. © 2011 Wiley Periodicals, Inc. Col Res Appl, 38, 218–228, 2013.