A fallacy in the definition of ΔH*

When a color differs from the reference, it is desirable to ascribe the difference to differences in the perceptual attributes of hue, chroma, and/or lightness through psychometric correlates of these attributes. To this end, the CIE has recommended the quantity ΔH* as a psychometric correlate of hue as defined by ΔH* = [(ΔE*)² - (ΔL*)² - (ΔC*)²]^1/2, where the correlates correspond to either the 1976 CIELAB or CIELUV color spaces. Since ΔH* is defined as a “leftover,” this definition is valid only to the extent that ΔE* comprises exclusively ΔL*, ΔC*, and ΔH* and that ΔL*, ΔC*, and ΔH* are mutually independent compositionally, both psychophysically and psychometrically. It will be shown that as now defined ΔH* lacks psychometric independence of chroma and always leads to incorrect hue difference determination. Such a deficiency causes problems, especially in the halftone color printing industry, since it can suggest an incorrect adjustment for the hue of the inks. A revised definition herein of ΔH* provides a psychometric hue difference independent of chroma, valid for large and small psychometric color differences regardless of chroma. However, for small chromas, the seldom used metric ΔC might be a better color difference metric than ΔH* because complex appearance effects make the perceptual discrimination of lightness, chroma, and hue components more difficult than for high chromas.     

Proposal of an opponent‐colors system based on color‐appearance and color‐vision studies

A new theoretical color order system is proposed on the basis of various studies on color appearance and color vision. It has three orthogonal opponent‐colors axes and an improved chromatic strength of each hue. The system has color attributes whiteness w, blackness bk, grayness gr, chroma C, and hue H. A method is given for determining Munsell notations of any colors on any equi‐hue planes in the system. A method is also given for determining grayness regions and grayness values on hue‐chroma planes in the system. It is concluded that colors with the same color attributes [w, gr, bk, C] but with different hues in the theoretical space have approximately the same perceived lightness, the same degree of vividness (“azayakasa” in Japanese), and also the same color tone. The tone concept, for example used in the Practical Color Coordinate System (PCCS), is clarified perceptually. The proposed system is a basic and latent color‐order system to PCCS. In addition, the concept of veiling grayness by a pure color with any hue is introduced. Further, relationships are clarified between generalized chroma c(gen) and grayness. © 2004 Wiley Periodicals, Inc. Col Res Appl, 29, 135–150, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.10234     

Hue scale adjustment derived from the Munsell system

Hue scale adjustment factors have been determined for CIELAB using the Munsell system. They have been found to vary significantly as a function of hue angle. A formula has been derived based on the 2° observer color‐matching functions that models the chroma scale of the Munsell system much more accurately than CIELAB using the same opponent color relationships. In this formula, hue differences can be calculated from hue angle differences, hue scale adjustment factors, and chroma. The hue scale adjustment factors based on hue angle required for the Munsell system have been derived. The variability by hue angle of these factors is such that an analytical hue scale adjustment function as those in CMC or BFD appears insufficient. The adjustment factors are compared to those recently derived by Qiao and coworkers. © 1999 John Wiley & Sons, Inc. Col Res Appl, 24, 33–37, 1999     

Colorimetric study of SCOTDIC colour specifier

In this study, SCOTDIC cotton standard colours (a physical exemplification of the Munsell system) were studied extensively. L*, a*, b* values were measured and plotted to check the uniformity of the Munsell (SCOTDIC) hue, value and chroma values in a CIELAB diagram. Although for some borderline hues the hue angles were quite different than expected (around 0° or 360°), the correlation between SCOTDIC hue and CIELAB hue angle was fairly good and the correlation between SCOTDIC value and CIELAB lightness was also quite high. However, the correlation between SCOTDIC chroma and CIELAB chroma was only moderate. In the CIELAB diagram, the constant SCOTDIC hue and constant chroma loci took the shape of approximately linear radial lines starting from the origin and approximately concentric circles with the origin as their centres, respectively. However, some deviations were observed for high chroma colours and yellow hues in the respective cases. The instrumentally predicted Munsell notations were compared with the actual SCOTDIC notations. Some deviations of the SCOTDIC system from the Munsell system were observed.     

Are chroma tolerances dependent on hue‐angle?

Relationships between suprathreshold chroma tolerances and CIELAB hue‐angles have been analyzed through the results of a new pair‐comparison experiment and the experimental combined data set employed by CIE TC 1–47 for the development of the latest CIE color‐difference formula, CIEDE2000. Chroma tolerances have been measured by 12 normal observers at 21 CRT‐generated color centers L*₁₀ = 40, C*_ab,10 = 20 and 40, and h_ab,10 at 30° regular steps). The results of this experiment lead to a chroma‐difference weighting function with hue‐angle dependence W_CH, which is in good agreement with the one proposed by the LCD color‐difference formula [Color Res Appl 2001;26:369–375]. This W_CH function is also consistent with the experimental results provided by the combined data set employed by CIE TC 1–47. For the whole CIE TC 1–47 data set, as well as for each one of its four independent subsets, the PF/3 performance factor [Color Res Appl 1999;24:331–343] was improved by adding to CIEDE2000 the W_CH function proposed by LCD, or the one derived by us using the results of our current experiment together with the combined data set employed by CIE TC 1–47. Nevertheless, unfortunately, from the current data, this PF/3 improvement is small (and statistically nonsignificant): 0.3 for the 3657 pairs provided by CIE TC 1–47 combined data set and 1.6 for a subset of 590 chromatic pairs (C*_ab,10>5.0) with color differences lower than 5.0 CIELAB units and due mainly to chroma. © 2004 Wiley Periodicals, Inc. Col Res Appl, 29, 420–427, 2004; Published online in Wiley Interscience (www.interscience.wiley.com). DOI 10.1002/col.20057     

Computational color combination analysis of Papilionidae butterflies as aesthetic objects

In this study, our aim is to clarify the color combination rules of the human-preferred Papilionidae butterflies as aesthetic objects. A set of 118 butterfly images, including color polyphenism from the 47 Papilionidae species that are generally preferred by humans, was selected. These images were classified using hierarchical cluster analysis based on similarities of lightness, chroma, and hue attributes in CIELAB space, determined using histogram intersection. Then, the color distributions and combinations in each cluster were analyzed using a Gaussian mixture model and the color combination types defined in the present study. Accordingly, we obtained the following main color combination rules of human-preferred Papilionidae: (a) dominant low lightness and contrasting lightness components, (b) dominant low chroma and similar chroma components, and (c) dominant orange to yellow-green hue and similar hue components. These rules partly agree with the robust harmony principles found in previous research. We infer that the cognitive effects concerning the processing fluency through these color combination rules influence human aesthetic responses.     

Subjective evaluation of uniform color spaces used for color-rendering specification

Three attributes of color appearance of sixteen samples illuminated by various light sources were estimated directly by two observers. The results are plotted on a subjective chroma diagram, with which the psychometricchroma diagrams calculated from the CIELUV and CIELAB spaces are compared. The comparison and numerical evaluations show that the CIELAB space is much better than the CIELUV and U* V* W* spaces in simulating surface-color appearance under various illuminants. Substitution of the CIELAB space for the U* V* W* space used in the CIE method of color-rendering specification is proposed.     

Effect of chromatic components on facial skin whiteness

Although the color measurement of facial skin becomes more common in dermatology and cosmetics, little is known about the relationship between subjective color perception and colorimetric values in facial skin. In this study, the possible relationships among perceived whiteness and the metric lightness, chroma and hue angle of Japanese females' facial skin color were investigated. First, the perceived brightness of the facial skin of Japanese females was evaluated visually and compared with metric lightness, chroma and hue angle, and the effect of hue and chroma on the perceived brightness was discussed. Second, a psychophysical experiment on the whiteness of the facial images and synthesized skin color plate images was conducted for examining the effect of hue and chroma on the perceived whiteness more precisely and independently. The results of two experiments showed that in regard to the facial skin color of the Japanese female, metric lightness disagrees with perceived whiteness or brightness in a narrow lightness range. The reddish facial skin color appeared brighter or whiter than that of a yellowish one in high lightness regions, and the low‐chroma facial skin color appeared brighter or whiter than a high‐chroma one. However, in the color plate images, a change in perceived whiteness by hue could not be confirmed, and the change in perceived whiteness by chroma was weaker than that from facial images. These results indicated that a higher‐level process of face recognition affected whiteness perception, and the criterion of facial skin whiteness was determined by facial skin color distribution. © 2011 Wiley Periodicals, Inc. Col Res Appl, 2011;     

COLOR CHANGE KINETICS OF CELERY LEAVES UNDERGOING MICROWAVE HEATING

The aim of this study was to investigate the effect of microwave output power and sample amount on color change kinetics of celery leaves (Apium graveolens L.) during microwave heating. The color parameters of the materials were quantified by the Hunter Lab system. These values were also used for calculation of the total color change, chroma, hue angle, and browning index. The microwave heating process changed color parameters of L, a, and b, causing a color shift towards darker region. The mathematical modeling study of color change kinetic showed that L, a, b, and chroma fitted to a first-order kinetic model, while total color change (ΔE), hue angle, and browning index (BI) followed a zero-order kinetic model. For calculation of the activation energy for color change kinetic parameters, the exponential expression based on the Arrhenius equation was used.     

基于色调区域分割的扫描仪颜色转换

扫描仪的颜色响应数值RGB与对应CIE视觉色度值间的转换用于颜色的正确捕获。实验建立了从RGB到CIEXYZ的转换关系。基于扫描仪响应数值RGB与颜色三刺激值CIEXYZ的形成机理,设计了将颜色空间分割为红、黄、绿、蓝、青、品红共6个色调区域,分别进行关系建立的方法。在两台扫描仪上的实验表明,对IT8.7/2标准色标,采用2阶10项的多项式拟合关系,颜色转换的CIEL*a*b*平均色差可达到1.0左右,最大色差小于4;对检验色标具有同样的转换精度,表明了该方法较强的泛化能力。实验同时表明,采用该方法,RGB到CIEXYZ的转换精度高于到CIEL*a*b*的转换。     

Categorical color constancy under RGB‐LED light sources

The light‐emitting diode (LED)‐based light sources have been widely applied across numerous industries and in everyday practical uses. Recently, the LED‐based light source consisting of red, green and blue LEDs with narrow spectral bands (RGB‐LED) has been a more preferred illumination source than the common white phosphor LED and other traditional broadband light sources because the RGB‐LED can create many types of illumination color. The color rendering index of the RGB‐LED, however, is considerably lower compared to the traditional broadband light sources and the multi‐band LED light source (MB‐LED), which is composed of several LEDs and can accurately simulate daylight illuminants. Considering 3 relatively narrow spectral bands of the RGB‐LED light source, the color constancy, which is referred to as the ability of the human visual system to attenuate influences of illumination color change and hold the perception of a surface color constant, may be worse under the RGB‐LED light source than under the traditional broadband light sources or under the MB‐LED. In this study, we investigated categorical color constancy using a color naming method with real Munsell color chips under illumination changes from neutral to red, green, blue, and yellow illuminations. The neutral and 4 chromatic illuminants were produced by the RGB‐LED light source. A modified use of the color constancy index, which describes a centroid shift of each color category, was introduced to evaluate the color constancy performance. The results revealed that categorical color constancy under the 4 chromatic illuminants held relatively well, except for the red, brown, orange, and yellow color categories under the blue illumination and the orange color category under the yellow illumination. Furthermore, the categorical color constancy under red and green illuminations was better than the categorical color constancy under blue and yellow illuminations. The results indicate that a color constancy mechanism in the visual system functions in color categories when the illuminant emits an insufficient spectrum to render the colors of reflecting surfaces accurately. However, it is not recommended to use the RGB‐LED light source to produce blue and yellow illuminations because of the poor color constancy.     

Visual determination of hue suprathreshold color-difference tolerances

This research extends the previous RIT-DuPont research on suprathreshold color-difference tolerances in which CIELAB was sampled in a balanced factorial design to quantify global lack of visual uniformity. The current experiments sampled hue, specifically. Three complete hue circles at two lightnesses (L* = 40 and 60) and two chroma levels ( = 20 and 40) plus three of the five CIE recommended colors (red, green, blue) were scaled, visually, for hue discrimination, resulting in 39 color centers. Forty-five observers participated in a forced-choice perceptibility experiment, where the total color difference of 393 sample pairs were compared with a near-neutral anchor-pair stimulus of 1.03 A supplemental experiment was performed by 30 additional observers in order to validate four of the 39 color centers. A total of 34,626 visual observations were made under the recently established CIE recommended reference conditions defined for the CIE94 color-difference equation. The statistical method logit analysis with three-dimensional normit function was used to determine the hue discrimination for each color center. A three-dimensional analysis was required due to precision limitations of a digital printer used to produce the majority of colored samples. There was unwanted variance in lightness and chroma in addition to the required variance in hue. This statistical technique enabled estimates of only hue discrimination. The three-dimensional analysis was validated in the supplemental experiment, where automotive coatings produced with a minimum of unwanted variance yielded the same visual tolerances when analyzed using one-dimensional probit analysis. The results indicated that the hue discrimination suprathresholds of the pooled observers varied with CIELAB hue angle position. The suprathreshold also increased with the chroma position of a given color center, consistent with previous visual results. The results were compared with current color-difference formulas: CMC, BFD, and CIE94. All three formulas had statistically equivalent performance when used to predict the visual data. Given the lack of a hue-angle dependent function embedded in CIE94, it is clear from these results that neither CMC nor BFD adequately predict the visual data. Thus, these and other hue-suprathreshold data can be used to develop a new color-difference formula with superior performance to current equations. © 1998 John Wiley & Sons, Inc. Col Res Appl, 23, 302–313, 1998     

Gloss and goniocolorimetry of printed materials

Angular distribution of reflectance spectra and of colorimetric parameters for printed papers (varnished and not) and foils, clear and metallized, were measured by goniospectrophotometry, with a photomultiplier for visible region, or a spectrocolorimeter as a detector, keeping the light source in a fixed position, ?45° anormally. All reflectance spectra were related to near‐Lambertian BaSO₄ powder white standard, relative to which the color coordinates were calculated. The photometric cosine law holds for an ideal diffuser; consequently, all color parameters are significantly perturbed by gloss in a large region, several 10's of degrees around the specular angle. The reflectance peak in the specular angle region of glossy material can be well approximated by the Lorentz function, especially in the vicinity of the specular angle. Lightness, chroma, and hue angle in the gloss angle region suffer as a result of high changes and extremes depending on the gloss of the material tested. This is what complicates color measurements and full determination or definition of the complex appearance of printed materials. The change of chroma with varnishing of glossless materials was clearly elucidated. It was found that “bottom color gloss” considerably influences the appearance of printed metallized foils or other prints on high glossy substrates. © 2003 Wiley Periodicals, Inc. Col Res Appl, 28, 335–342, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.10177     

Design and performance of a color chart based in digitally processed images for sensory evaluation of piquillo peppers (Capsicum annuum)

A chart of color standards for visual color evaluation of the piquillo pepper (Capsicum annuum) has been designed. The chart comprises six rectangular regions of digitally processed images of piquillo peppers covering the observed visual range of variability in this product. Colorimetric characterization of piquillo peppers and the color chart has been made using instrumental color measurements. Both trained and untrained sensory panels tested the reliability of the designed color chart. The Pearson correlation coefficient between color chart scores and subjective color quality scores is 0.831 (P < 0.01). Correlation between all instrumental color coordinates, with the exception of CIELAB a*, and visual color chart scores are significant at P< 0.001 and Pearson correlation coefficients range from ?0.747 with CIELAB chroma C* to ?0.926 with CIELAB hue angle h. Repeatability of visual color chart scores is completely satisfactory, having found no statistically significant differences between color chart scores in samples evaluated twice by panelists. © 2004 Wiley Periodicals, Inc. Col Res Appl, 29, 305–311, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20026     

Unique hue judgments using saturated and desaturated Munsell samples under different light sources

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 D_uv (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.     

A comment about the chroma scale of Nayatani‐theoretical color order system

Nayatani‐theoretical (NT) color order system is a Hue–Tone color order systems. It can be used for determining surface colors with the same Tone (equiperceived lightness and equiperceived chroma) irrespective of hues under reference illuminant. The fundamental structure of NT system uses Munsell attributes HV/C for the easiness of its use. Some deviations caused by the approximation on chroma scale are naturally expected in NT system, although the formula used for deriving equivalent lightness V_eq has the same structure as that for deriving L*_eq using the corresponding CIELUV formula. The present article discusses the degree of approximation, and confirms the goodness of approximation. NT system can be used as it is for the field of artistic color design (complete accuracy is not required). The corrections, however, should be introduced in NT system, when higher accuracy is required. © 2007 Wiley Periodicals, Inc. Col Res Appl, 32, 230–233, 2007     

3D Master Toothguide according to L*, C*, and h* coordinates

The purposes of this study are to describe the color coordinates of the 26 shade tabs of the 3D Master Toothguide according to their L*, C*, h* coordinates, and to calculate ΔE_ab*, ΔL*, ΔC*, and Δh* in the 26 shade tabs. The tooth color of 1361 maxillary central incisors was measured “in vivo” using a spectrophotometer. Tooth color was recorded following the 3D Master system and its corresponding L*, C*, h*color coordinates. Of the 325 shade tabs pairs compared a color difference ( ) of between 2.6 and 5.5 units was found in 9.54% (31 pairs). In 291 pairs (89.54%) there was color difference that exceeded the 5.5 units. Only 0.92% of the color differences () were less than 2.6 units. The minimum color difference ( ) found was 2.1 units and the maximum 45.0 units. The intervals in lightness, chroma, and hue groups between adjacent shade tabs were not uniform. In conclusion, this toothguide is clearly ordered regarding lightness or the L* coordinate. Most of the color differences between the 26 shade tabs of the 3D Master exceed the perceptible threshold of 2.6 units. Some clinical implications are as follows: the 26 shade tabs of the 3D Master Toothguide offer improvements as far as spatial arrangement is concerned. Thus, it is highly possible that the subjective visual color of the measurement would be correct. If there is a mistake when choosing the shade tab from the 3D Master guide there will quite probably be an unacceptable color difference from the clinical point of view. © 2014 Wiley Periodicals, Inc. Col Res Appl, 40, 518–524, 2015.     

Color Change Kinetics of Microwave-Dried Basil

The aim of this study was to investigate the effect of microwave output power and sample amount on color change kinetics of basil (Ocimum basilicum L.) during microwave drying. The color parameters for the color change of the materials were quantified by Hunter L (whiteness/darkness), a (redness/greenness), and b (yellowness/blueness) system. These values were also used for calculation of the total color change (ΔE), chroma, hue angle, and browning index. The microwave-drying process changed color parameters of L, a, and b, causing a color shift toward the darker region. The mathematical modeling study of color change kinetics showed that a and b fitted to a first-order kinetic model, while L and total color change (ΔE) followed a zero-order kinetic model. However, chroma and browning index (BI) followed a first-order kinetic model, whereas hue angle followed a zero-order kinetic model. For calculation of the activation energy for colour change kinetic parameters, the exponential expression based on Arrhenius equation was used.     

Accuracy of approximations for CIELAB chroma and hue difference computation

The transformation in CIELAB from differences in the L^*, a^*, b^* coordinates to those in lightness, chroma, and hue, ΔL^*, ΔC_ab^*, ΔH_ab^*, can be approximated by a rotation in 3-space. Expressions for the error in the approximation of chroma and hue differences are developed. Significant errors are introduced if either the hue angle or chroma difference between reference and sample colors are large. A computed example illustrates the use of the analysis. © 1997 John Wiley & Sons, Inc. Col Res Appl, 22, 61–64, 1997.