Adaptation and colour matching of display and surface colours

In an asymmetric colour matching experiment, eleven observers adjusted computer displays to colour‐match surface samples in a viewing booth. We found systematic discrepancies between the observers' judgments and the predictions of the CIE 1964 Standard Colorimetric Observer. The features of the discrepancies are consistent with previous reports on adaptation in colour matching and on failures of colorimetric additivity, but have never been confirmed to be significant in practical colorimetry. We attribute the discrepancies to post‐receptoral adaptation mainly of the blue‐yellow chromatic channel, and report a framework of an adaptation transform based on the MacLeod‐Boynton chromaticity diagram which can compensate for them without abandoning traditional colorimetry and the use of tristimulus values. © 2009 Wiley Periodicals, Inc. Col Res Appl, 34, 182–193, 2009     

Minimizing observer metamerism in display systems

Observer metamerism has long been known to be an issue of concern for color engineers. With the advent and mass proliferation of narrow‐band display devices, this article addresses the issue of observer metamerism and puts it in the context of first understanding the implication of interobserver variations in the color matching functions (CMFs) and additionally designing the ideal set of primary illuminant spectral power distributions (SPDs) such that observer metamerism is minimized. The article also suggests the use of the Full Width Half Maximum (FWHM) and the number of modes (peaks) in the primary SPDs as a means of assessing the susceptibility to observer‐to‐observer variations between various modern display technologies. © 2009 Wiley Periodicals, Inc. Col Res Appl, 34, 391–398, 2009     

Categorical observers for metamerism

A method is proposed to generate categorical colour observer functions (individual colour matching functions) for any field size based on the CIE 2006 system of physiological observer functions. The method combines proposed categorical observer techniques of Sarkar et al with a physiologically-based individual observer model of Asano et al and a clustering technique to produce the optimal set of categorical observers. The number of required categorical observers varies depending on an application with as many as 50 required to predict individual observers' matches when a laser projector is viewed. However, 10 categorical observers are sufficient to represent colour-normal populations for personalized colour imaging. The proposed and recommended categorical observers represent a robust and inclusive technique to examine and quantify observer metamerism in any application of colorimetry.     

Testing the behavior for metamerism of the new deviate observer (JF‐DO)

Recently,in our laboratories, a set of color‐matching functions (cmfs) has been formulated for small fields by using two groups of real observers: JAM, MM, CF and AY, JR, MR, JL, JA, FP. The measurements of these cmfs have been made using different experimental devices and methods and it has enabled us to propose a New Deviate Observer for small fields (JF‐DO). This new JF‐DO was derived from the average observer of our nine real observers, following the technique used by the CIE to establish the Standard Deviate Observer (CIE‐1989 SDO), which was established for fields of 10°, despite the CIE's assumption that it can be applied to smaller fields. In the present work, we report experimental results of the JF‐DO using metameric reflectances in comparison to the CIE‐1931 Standard Observer and to the CIE‐1989 SDO. © 2005 Wiley Periodicals, Inc. Col Res Appl, 30, 363–370, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.     

The usability of the CIE colour‐matching functions in the case of CRT monitors

During the past years, several papers have been published that question the use of the CIE colour‐matching functions in the case of metameric samples. Visually matching samples produced on CRT (Cathode Ray Tube) monitors are metameric to most colour stimuli created by illuminating reflecting materials. As CRT monitors are often used in colour design applications, it seemed important to check how well CIE colorimetry will predict such colour matches. To investigate this problem, we set up an experiment in which painted samples were matched with samples produced on a CRT monitor. The colour of incandescent lamp irradiated Munsell samples were visually matched to the mixture of the RGB primaries of a CRT monitor. Both the reflected colour stimuli of the Munsell samples and the emitted stimuli of the monitor were measured spectroradiometrically. Our results imply that there is an observer‐dependent variability among the matches, but we could not find a major difference between the tristimulus data of the hard copy and soft copy presentations that would indicate errors in the CIE colour‐matching functions. The measurement accuracy, quantization errors of the monitor, and the achieved accuracy of the colour matches are treated in this study. © 2001 John Wiley & Sons, Inc. Col Res Appl, 26, 436–441, 2001     

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     

Lightness and hue contrast effects in surface (fabric) colours

Simultaneous contrast effects on lightness and hue in surface colours were investigated. Test colours, surrounded by induction colours, were matched by colours surrounded by neutral gray. The matching colours were selected from a series of samples that varied in either lightness or hue respectively. The lightness experiments were carried out by a panel of 20 observers on 135 test/induction colour combinations. The hue experiments were conducted on 51 test/induction colour combinations by a panel of eight observers. The lightness of the test colour was found to decrease linearly with the lightness of the induction colour, regardless of the hue of the induction colour. The magnitude of the lightness contrast effect in fabric colours was found to be about one‐quarter of that found in CRT display colours in a previous study. The hue contrast effect found in this study followed the opponent‐colour theory. Two distinctly different regions could be identified when the hue difference was plotted against hue‐angle difference between the induction colour and the test colour. The slope of the line in the region where the hue of the induction colour is close to the test colour was much larger than the slope in the other region, indicating that the hue contrast effect was more obvious when the induction colour was close to the test colour. © 2006 Wiley Periodicals, Inc. Col Res Appl, 32, 55–64, 2007; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20285     

Uniform colour spaces based on the DIN99 colour‐difference formula

Several colour‐difference formulas such as CMC, CIE94, and CIEDE2000 have been developed by modifying CIELAB. These formulas give much better fits for experimental data based on small colour differences than does CIELAB. None of these has an associated uniform colour space (UCS). The need for a UCS is demonstrated by the widespread use of the a*b* diagram despite the lack of uniformity. This article describes the development of formulas, with the same basic structure as the DIN99 formula, that predict the experimental data sets better than do the CMC and CIE94 colour‐difference formulas and only slightly worse than CIEDE2000 (which was optimized on the experimental data). However, these formulas all have an associated UCS. The spaces are similar in form to L*a*b*. © 2002 Wiley Periodicals, Inc. Col Res Appl, 27, 282–290, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.10066     

Colour matching using LEDs as primaries

In our metameric experiment, the colour of a filtered incandescent lamp was matched with the additive mixture of three LEDs in a Lummer–Brodhun‐type visual photometer. Two sets of primaries were used, one had their dominant wavelengths at 467, 533, and 600 nm; the other set had dominant wavelengths at 478, 552, and 635 nm. These values correspond approximately to the characteristic wavelengths of the Prime and Non‐Prime Colour spectral regions defined by W. A. Thornton. 1 Both the light of the incandescent lamp and that of the LED clusters were seen monocularly in a centrally divided bipartite field at a visual angle of 2°. The luminance of the matching fields was in the order of 20 cd/m² to provide sufficient gamut for the LED mixture. Ten young observers with normal colour vision participated in the experiment. The emission spectra of the viewing fields were measured with an array‐type spectroradiometer, and two sets of colour‐matching functions were used to calculate the chromaticity of the matching stimuli: the CIE 1931 standard colorimetric observer and the Judd–Vos modification of the colour‐matching functions. We found that the Judd–Vos modification of the CIE 1931 standard observer represents more accurately the real observers in the evaluation of our results. No systematic differences between the use of the two sets of LEDs were detected in contradiction to Thornton's findings. © 2004 Wiley Periodicals, Inc. Col Res Appl, 29, 360–364, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20044     

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.     

Inter‐observer comparison of color‐matching functions

The colorimetric difference between pairs of observers is simulated by a proper filtering of the stimulating radiation, and their comparison is made on properly defined Common Reference Frames in the tristimulus space. As examples, two comparisons are proposed: (1) Comparison between the Vos modification of the CIE 1931 Standard Colorimetric Observer and the CIE 1964 Supplementary Standard Observer: in this case, it is supposed that the difference between these two color‐vision systems is due to the macula lutea only, which with a spectral selective absorbance alters the power spectral distribution of the color stimuli. The optical density of the macular pigment is well reproduced. (2) Comparison between the Vos modification of the CIE 1931 Standard Colorimetric Observer and the CIE 1931 Standard Colorimetric Observer: in this case, the difference between these two observers could be simulated by different calibration of the photodetectors. © 1999 John Wiley & Sons, Inc. Col Res Appl, 24, 177–184, 1999     

Investigation of texture effect on visual colour difference evaluation

The texture effect on visual colour difference evaluation was investigated in this study. Five colour centers were selected and textured colour pairs were generated using scanned textile woven fabrics and colour‐mapping technique. The textured and solid colour pairs were then displayed on a characterized cathode ray tube (CRT) monitor for colour difference evaluation. The colour difference values for the pairs with texture patterns are equal to 5.0 CIELAB units in lightness direction. The texture level was represented by the half‐width of histogram, which is called texture strength in this study. High correlation was found between texture strength and visual colour difference for textured colour pairs, which indicates that an increasing of 10 units of texture strength in luminance would cause a decreasing of 0.25 units visual difference for the five colour centers. The ratio of visual difference between textured and solid colour pairs also indicates a high parametric effect of texture. © 2005 Wiley Periodicals, Inc. Col Res Appl, 30, 341–347, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.     

Universal models of colour emotion and colour harmony

A new set of quantitative models of colour emotion and colour harmony were developed in this study using psychophysical data collected from 12 regions in the world, including Argentina, China, France, Germany, Hungary, Iran, Japan, Spain, Sweden, Taiwan, Thailand, and the UK. These data have previously been published in journals or conferences (for details see Tables 1 and 2 ). For colour emotion, three new models were derived, showing satisfactory predictive performance in terms of an average correlation coefficient of 0.78 for “warm/cool”, 0.80 for “heavy/light” and 0.81 for “active/passive”. The new colour harmony model also had satisfactory predictive performance, with an average correlation coefficient of 0.72. Principal component analysis shows that the common colour harmony principles, including hue similarity, chroma similarity, lightness difference and high lightness principles, were partly agreed by observers of the same region. The findings suggest that it is feasible to develop universal models of colour emotion and colour harmony, and that the former was found to be relatively more culture‐independent than the latter.     

Investigation of parametric effects using small colour differences

This experiment was carried out to investigate some viewing parameters affecting perceived colour differences. It was divided into eight phases. Each phase was conducted under a different set of experimental conditions including separations, neutral backgrounds, and psychophysical methods. Seventy‐five wool sample pairs were prepared corresponding to five CIE colour centers. The mean colour difference was three CIELAB units. Each pair was assessed by a panel of 21 observers using both the gray scale and pair comparison psychophysical methods. The assessments were carried out using the three different backgrounds (white, mid‐gray, and black) and a hairline gap between the samples. Assessments on the gray background were repeated using a large (3‐inch) gap between the samples. It was found that the visual results obtained from both psychophysical methods gave very similar results. The parametric effect was small, i.e., the largest effect was only 14% between the white and gray background conditions. These visual data were also used to test four colour‐difference formulae: CIELAB, CMC, BFD, and CIE94. The results showed that three advanced colour‐difference formulae performed much better than CIELAB. There was a good agreement between the current results and those from earlier studies. © 1999 John Wiley & Sons, Inc. Col Res Appl, 24, 331–343, 1999     

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     

A computer‐assisted colour selection system based on aesthetic measure for colour harmony and fuzzy logic theory

An aesthetic measure based approach for constructing a colour design/selection system is proposed in this article. In this model, an image data base for the relationships between the psychological preference of customers and clothing colour tones is built using the membership functions of a fuzzy set, and an aesthetic measure calculation method based on colour harmony is also proposed. In addition, a skin colour detection theory is proposed to construct a skin colour detection program to detect the skin colour of a customer, which is then taken as the major colour in matching the skin, polo shirt, and(or) pant colours to select the best colour combination. Integrating the skin colour detection theory, colour harmony theory, aesthetic measure method, and fuzzy set theory, a program is constructed to build an aesthetic measure based colour design/selection system. With the aid of this system, one can get proper cloth colours to match his/her skin colour and image requirement by starting with inputting one's colour photo, catching image with a camera, or inputting R, G, B values of his/her skin. The theoretical results for the ranks of clothing colours proposed by the system are examined with the experimental results and the result shows they are very close, suggesting that the proposed colour selection system is acceptable. Although the selection of clothing colours is taken as an example to specify the methodology, it can also be used to develop a system for other products. © 2008 Wiley Periodicals, Inc. Col Res Appl, 33, 411–423, 2008     

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     

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;     

Colour and tolerance of preferred skin colours on digital photographic images

Skin‐tone has been an active research subject in photographic colour reproduction. There is a consistent conclusion that preferred skin colours are different from actual skin colours. However, preferred skin colours found from different studies are somewhat different. To have a solid understanding of skin colour preference of digital photographic images, psychophysical experiments were conducted to determine a preferred skin colour region and to study inter‐observer variation and tolerance of preferred skin colours. In the first experiment, a preferred skin colour region is searched on the entire skin colour region. A set of nine predetermined colour centers uniformly sampled within the skin colour ellipse in CIELAB a*b* diagram is used to morph skin colours of test images. Preferred skin colour centers are found through the experiment. In a second experiment, a twice denser sampling of nine skin colour centers around the preferred skin colour center determined in the first experiment are generated to repeat the experiment using a different set of test images and judged by a different panel of observers. The results from both experiments are compared and final preferred skin colour centers are obtained. Variations and hue and chroma tolerances of the observer skin colour preference are also analysed. © 2011 Wiley Periodicals, Inc. Col Res Appl, 2013