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.     

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     

The perception of static colored noise: Detection and masking described by CIE94

We present psychophysical data on the perception of static colored noise. In our experiments, we use the CIE94 color difference formula to quantify the noise strength and for describing our threshold data. In Experiment 1 we measure the visual detection thresholds for fixed pattern noise on a uniform background color. The noise was present in one of three perceptual color dimensions lightness (L*), chroma (C*), or hue (h). Results show that the average detection threshold for noise in L* is independent of hue angle and significantly lower than that for noise in C* or h. Thresholds for noise in C* and h depend on hue angle in an opponent fashion. The measured detection thresholds, expressed in terms of the components ΔL*/k_LS_L, ΔC*/k_CS_C, and ΔH*/k_HS_H that build up the CIE94 color difference formula are used to tune CIE94 to our experimental conditions by adjusting the parametric scaling factors k_L, k_C, and k_H. In Experiment 2, we measure thresholds for recognizing the orientation (left, right, up, down) of a test symbol that was incremental in L*, C*, or h, masked by supra‐threshold background noise levels in L*, C*, or h. On the basis of the CIE94 color difference formula we hypothesized (a) a constant ratio between recognition threshold and noise level when the test symbol and background noise are in the same perceptual dimension, and (b) a constant recognition threshold when in different dimensions. The first hypothesis was confirmed for each color dimension, the second however, was only confirmed for background noise in L*. The L*, C*, h recognition thresholds increase with increasing background noise in C* or h. On the basis of some 16,200 visual observations we conclude that the three perceptual dimensions L*, C*, and h require different scaling factors (hue dependent for C* and h) in the CIE94 color difference formula, to predict detection threshold data for color noise. In addition these dimensions are not independent for symbol recognition in color noise. © 2008 Wiley Periodicals, Inc. Col Res Appl, 33, 178–191, 2008     

Improving the compatibility of disperse dye mixtures using levelling agent — assessment through colour coordinates

The addition of a nonionic levelling agent to a dyebath containing a mixture of three disperse dyes in equal proportions and having similar hues (all in the red—yellow sector of colour space) significantly improved their compatibility, especially at higher applied depths of 3.0% and 4.5%. The dyed samples were measured for the differences in their colour coordinates with respect to the undyed substrate on a spectrophotometer attached to an IBM personal computer. The plots of ΔL* vs ΔC*_ab, ΔL* vs K/S, Δb* vs Δa*, Δa* vs K/S and Δ6* vs K/S clearly indicated the improvement in compatibility of the dye mixture.     

Different transformation methods between CIELAB coordinates and Munsell hue

This research aims to convert CIE L*C*_abh_ab coordinates into corresponding Munsell hues. Different transformation methods for colour mapping from CIELAB colour space to Munsell hues are proposed. Polynomial equations that predict Munsell hue from CIELAB h_ab suffer from poor performance as there is no direct one‐to‐one mapping. Polynomial methods that predict Munsell hue from all three L*C*_abh_ab values also show limited performance. However, a distance‐weighted look‐up‐table model based upon the CIEDE2000 colour‐difference equation is able to predict Munsell hue to an accuracy of 1 unit of root mean square error. All transformation methods in this paper were developed using CIE illuminant C and the 2° standard observer conditions and were based on 2729 Munsell renotation colour samples.     

Evaluation of performance of various color‐difference formulae using an experimental black dataset

The objective of this study was to develop a specific visual dataset comprising black‐appearing samples with low lightness (L* ranging from approximately 10.4 to 19.5), varying in hue and chroma, evaluating their visual differences against a reference sample, and testing the performance of major color difference formulas currently in use as well as OSA‐UCS‐based models and more recent CAM02 color difference formulas including CAM02‐SCD and CAM02‐UCS models. The dataset comprised 50 dyed black fabric samples of similar structure, and a standard (L*= 15.33, a* = 0.14, b* = ?0.82), with a distribution of small color differences, in ΔE^*_ab, from 0 to approximately 5. The visual color difference between each sample and the standard was assessed by 19 observers in three separate sittings with an interval of at least 24 hours between trials using an AATCC standard gray scale for color change, and a total of 2850 assessments were obtained. A third‐degree polynomial equation was used to convert gray scale ratings to visual differences. The Standard Residual Sum of Squares index (STRESS) and Pearson's correlation coefficient (r), were used to evaluate the performance of various color difference formulae based on visual results. According to the analysis of STRESS index and correlation coefficient results CAM02 color difference equations exhibited the best agreement against visual data with statistically significant improvement over other models tested. The CIEDE2000 (1:1:1) equation also showed good performance in this region of the color space. © 2013 Wiley Periodicals, Inc. Col Res Appl, 39, 589–598, 2014     

Comparison of the metrics between the CIELAB and the DIN99 uniform color spaces using dental resin composite material values

The sizes for the perceptible or acceptable color difference measured with instruments vary by factors such as instrument, material, and color‐difference formula. To compensate for disagreement of the CIELAB color difference (ΔE^*_ab) with the human observer, the CIEDE2000 formula was developed. However, since this formula has no uniform color space (UCS), DIN99 UCS may be an alternative UCS at present. The purpose of this study was to determine the correlation between the CIELAB UCS and DIN99 UCS using dental resin composites. Changes and correlations in color coordinates (CIE L*,a*, and b* versus L₉₉, a₉₉, and b₉₉ from DIN99) and color differences (ΔE^*_ab and ΔE₉₉) of dental resin composites after polymerization and thermocycling were determined. After transformation into DIN99 formula, the a value (red–green parameter) shifted to higher values, and the span of distribution was maintained after transformation. However, the span of distribution of b values (yellow–blue parameter) was reduced. Although color differences with the two formulas were correlated after polymerization and thermocycling (r = 0.77 and 0.68, respectively), the color coordinates and color differences with DIN99 were significantly different from those with CIELAB. New UCS (DIN99) was different from the present CIELAB UCS with respect to color coordinates (a and b) and color difference. Adaptation of a more observer‐response relevant uniform color space should be considered after visual confirmation with dental esthetic materials. © 2006 Wiley Periodicals, Inc. Col Res Appl, 31, 168–173, 2006     

Determination of dyers’ perceived components of colour difference (depth,brightness and hue) between two similar colours from their spectral reflectance values

The partitioning of colour differences into ΔL^*, ΔC^* and ΔH^* is not directly equivalent to the dyer’s method of partitioning. The dyer’s method involves separation into the components of depth (ΔD), brightness (ΔB) and hue (ΔH), of which only hue difference has a qualitative (and quantitative) equivalent in the CIELAB system. Depth and brightness are important terms to dyers. Depth is related to the amount of dye taken up by a textile material and brightness to that component of colour difference that is neither depth nor hue. Brightness is best defined as the opposite of dullness, dullness being related to the amount of neutral grey present in the colour. An algorithm, called the Wardman–Smith–Farooq algorithm, has been developed to compute the dyers’ variables of ΔD,ΔB and ΔH from spectral reflectance values, enabling dyers to take full advantage of colorimetry. The algorithm is based on extensive experimental work to map surfaces of constant visual depth through the colour space and this paper describes the methodology of the calculation. The correlations of the values of ΔD,ΔB and ΔH, determined using the Wardman–Smith–Farooq algorithm with other empirical models for 117 sample pairs, are given.     

An abridged technique to diagnose spectrophotometric errors

The effect on colorimetric accuracy of spectrophotometric errors (±0.5 and ±1% reference white, ±0.25 and ±0.5% reference black, and ±0.5 and ±1 nm wavelength) was simulated for the BCRA Series II tile set by using previously investigated models for these errors. ΔE^*₉₄ color differences of up to 5.2 could result. Because the errors are linearly related to CIELAB differences for each tile, a technique was derived that enabled ΔL^*, Δa^*, and Δb^* coordinates between a calibrated tile and its measured value to be transformed into estimates of reference white, reference black, and wavelength error. The cyan tile was identified as the most effective tile for this technique. “Universal” equations are included for 45/Normal and Normal/Total geometries traceable to the National Institute of Standards and Technology (NIST), and Normal/45, Normal/Total, and Normal/Diffuse geometries traceable to the National Physical Laboratory (NPL). Measuring the cyan tile on a regular basis and transforming its colorimetric coordinates into spectrophotometric error metrics provides a useful method to validate the accuracy and reproducibility of a color-measurement instrument. © 1997 John Wiley & Sons, Inc. Col Res Appl, 22, 51–60, 1997.     

What can we learn from a dress with ambiguous colors?

We performed objective spectroradiometric measurements on an LCD image of the recently famous Tumblr dress which is typically perceived by people as blue/black or white/gold. The average ± standard deviation of the CIELAB coordinates was as follows: For a set of 33 points in the areas considered as blue/white, L* = 46 ± 6, C*_ab = 33 ± 6, and h_ab = 282 ± 3°, and for a set of 36 points in the areas considered as black/gold, L* = 29 ± 6; C*_ab = 10 ± 4; h_ab = 16 ± 34°. Initially, this first set of values has low variability and corresponds to a blue color, whereas the second set of values has a very large hue‐angle range, including points which can be considered as both gold and black colors. We also performed spectrophotometric measurements on an original model of this dress, and, assuming D65 illuminant and CIE 1931 colorimetric standard observer, the average results were L* = 26, C*_ab = 39, and h_ab = 289°, and L* = 10, C*_ab = 1, and h_ab = 290° for the blue/white and black/gold points, respectively. We discuss the influence of different factors on the blue/black and white/gold perceptions of different people, including observers' variability in color‐matching functions, Bezold–Brücke and Abney effects, background influence, and illumination assumptions. Although more research on the effect shown in this dress is needed, we think that from this example we can learn that objects do not have specific colors; that is, color is a human perception, and many times the answer of the human visual system is not simple and relies on assumptions of unknown, and variable, origin. © 2015 The Authors Color Research & Application Published by Wiley Periodicals, Inc., 40, 525–529, 2015     

A shade guide model based on the color distribution of natural teeth

The objectives were to determine the color distribution of natural teeth sorted by the parameters of Value, Chroma, and hue angle measured with a colorimeter, and to suggest a shade guide model. The color of maxillary and mandibular 12 anterior teeth was measured with a tristimulus colorimeter for 47 subjects (n = 564). The color of teeth was grouped initially by Value (CIE L*) by the interval of 3.3 units. After then, within each main group, the color of teeth was subgrouped by Chroma by the interval of 3.3 units. Chroma was calculated as C*_ab = (a*2 + b*2)^1/2. Since the hue angles were in the first or fourth quadrant, subgroups were further sorted by the first or fourth quadrant hue angles. Hue angle was calculated as h° = arctan (b*/a*). Mean color difference (ΔE*_ab) between the color of an individual tooth and the mean color of each main group was 2.5–3.3, which was lower than acceptable limit (ΔE*_ab < 3.3), and that in each subgroup was 0.9–3.1. The number of subgroups was 22, which was comparable to those of conventional shade guides. A shade guide model based on the color distribution of natural teeth sorted by Value in six main groups, three or four subgroups within each main group sorted by Chroma, and further sorted by hue angle (first or fourth quadrant values) was suggested. © 2007 Wiley Periodicals, Inc. Col Res Appl, 32, 278–283, 2007     

Some aspects of the visual scaling of large colour differences—II

In an earlier article the authors related visually‐ scaled large colour differences to ΔE* values calculated using four colour‐difference formulae. All four metrics yielded linear regressions from plots of visual colour difference against ΔE*, and ΔE gave the best linear fit, but the correlations were rather low. In an effort to clarify matters, the previous investigation is expanded to include data not hitherto examined. The link between visual colour difference and ΔE* colour metrics is further explored in terms of a power law relationship over a wide range of lightness, hue, and chroma variations within CIELAB colour space. It is shown that power‐law fits are superior to linear regressions in all cases, although correlations over large regions of the colour space are not very high. Partitioning of the experimental results to give reduced data sets in smaller regions is shown to improve correlations markedly, using power‐law fits. Conclusions are drawn concerning the uniformity of CIELAB space in the context of both linear and power‐law behavior. © 2000 John Wiley & Sons, Inc. Col Res Appl, 25, 116–122, 2000     

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.     

Influence of Turbidity Grade on Color and Appearance of Virgin Olive Oil

The appearance of most of the commercialized olive oils involves both their color and turbidity depending on the different technologies used for their elaboration. This research has been carried out to study the filtration impact on the colorimetric changes of virgin olive oils. Naturally turbid olive oils were blended at different proportions (100, 80, 60, 40, 20 and 0%) with their corresponding filtered replicates to obtain a scale of six levels of turbidity and simulating different turbidity grades. Tristimulus colorimetry, particularly the CIELAB uniform color, was used to follow color changes. As turbidity of the oil increased in the blend, yellowish oils, darker, and less saturated were obtained. Univariate correlations between the colorimetric parameters and turbid content were achieved with second degree polynomial equations, being chroma ( C_\textab ^* C_{{_{\text{ab}} }}^{ *} ) and hue (h _ab) the best correlated parameters. The color differences ( \Updelta E_\textab ^* \Updelta E_{{_{\text{ab}} }}^{ *} ) calculated between turbid oils (100%) and the consecutively decreasing turbid oils blends ranged from 3.18 to 18.72 CIELAB units, revealing differences in color visually perceptible to the human eye.     

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.     

Color evolution during a coating process of pharmaceutical tablet cores by random spraying

Placebo white tablet cores (lactose anhydrous [47.6%], corn starch [23.8%], microcrystalline cellulose [19.1%], polyvinylpyrrolidone [7.9%], magnesium stearate [0.8%], and talcum powder [0.8%]) were coated with a colorant (hydroxypropyl methylcellulose [8% w/v], titanium dioxide [0.2% w/v], FD&C yellow No. 6 with aluminum lacquer [0.8% w/v], polyethylene glycol 4000 [0.4% w/v], and purified water [q.s.p. 100 mL]) using a random spraying method during 130 minutes. During the coating process, batches of 21 samples were extracted every 10 minutes and measured with a DigiEye imaging system. The initial cores showed very similar and uniform colors (Mean Color Difference from the Mean [MCDM] of 0.8 CIELAB units), but partially coated tablets showed lower uniformity (MCDM below 2.0 CIELAB units). There was a high color variability (MCDM about 4.0 CIELAB units) among tablets of the same batch in the period between 10 and 30 minutes, which decreased as the coating process progressed, until achieving a final acceptable value (MCDM below 2.0 CIELAB units). During the coating process, L^* decreased, C^*_ab strongly increased, and h _ab remained nearly constant (disregarding results at 0 and 10 minutes). CIELAB and CIEDE2000 color differences (mainly chroma differences) with respect to the initial color of the tablets were modeled as a function of time by exponential functions with three coefficients. The color change in the interval from 90 to 130 minutes (4.3 CIELAB units, or 2.6 CIEDE2000 units), may be considered negligible bearing in mind the color variability in the batches of 21 samples and typical values of visual color thresholds.     

Improved coloristic properties and high NIR reflectance of environment-friendly yellow pigments based on bismuth vanadate

Herein, fine powders of yellow pigments based on BiVO₄ were successfully prepared in two crystalline forms, tetragonal zircon-structured and monoclinic scheelite-structured, through a ethylene glycol-assisted method subjected to a thermal treatment at two different temperatures. The obtained materials were brightly colored with different hues of yellow, exhibited high reflection in the near-infrared region and showed visible luminescence under excitation by UV light. The new preparation method had a considerable effect on chromatic properties of the prepared scheelite-structured BiVO₄ pigments. The sample with the most vivid and bright shade of yellow was found to have the L^*a^*b^* and L^*C^*_ab h^*_ab color coordinates of (87.28, 0.37, 91.53) and (87.28, 91.53, 89.79), which are indicative of exceptionally good chromatic properties superior and/or comparable to those of other inorganic yellow pigments, both commercially available and recently described. In addition, the NIR reflectance of this powder was very high (≥?80%).     

EFFECT OF CHITIN ON COLOR DURING OSMOTIC DEHYDRATION OF BANANA SLICES

ABSTRACT

Five conditions of the osmo-dehydration process of banana slices, which in our previous study underwent the most adequate color parameter changes. L, hue and chroma values were studied with the presence of chitin added to the syrup solutions at the concentration of 0.05, 0.1 and 0.5% w/w. After four hours of osmo-dehydration, color space results of L, a and b as well as polyphenol oxidase activity were measured. Color space results were used to calculate hue and chroma and total color difference changes. Chitin presence did not change the tendency of polyphenol activity decreased during osmotic drying as well as has not effect on chroma, hue and total color difference changes. Chitin presence had an effect on L value decrease in the inner and outer part of the slice, and these changes did not depend to osmotic dehydration conditions. It is highly recommended to use chitin during osmotic dehydration of some fruits that would undergo undesirable darkening.     

A shift of the perceptual attributes of color due to the manifestation of the simultaneous contrast effect on a display

This research shows the effect of simultaneous contrast on a design solution that generates it, and it also shows how its manifestation affects the shift of perception attributes of the observer's color. In the conducted research, 55 subjects had to harmonize the primary stimuli from the reproduction obtained with the help of digital printing technology, with the primary stimuli presented on two computer screens. As a visual harmonization technique, simultaneous binocular harmonization was used. The primary stimuli were made achromatic, with a 50% Raster Tone value (RTV), and are surrounded by achromatic secondary stimuli whose values increase in steps from 10% RTV up to 100% RTV. A shift in the perceptual attributes of color has been shown with the help of the CIEDE2000 system. Using ANOVA with repeated-measures and Fisher's post hoc analysis, statistically significant differences were found between the perceived means of shift in the ΔC₀₀ chroma and ΔL₀₀ lightness on defined samples on both computer screens, while in the case of the ΔH₀₀ hue, no statistically significant differences were observed. The research also determined colorimetric differences in the ΔE₀₀ color difference. Moreover, the student's t test was used to determine that the effect is stronger when manifested on the Lenovo computer than on the Asus computer screen (P < .05).     

Polystyrene–polyisobutylene network composites from in situ polymerizations

Crosslinked networks of butyl rubber [polyisobutylene (PIB) with 2 mol % unsaturation] were swelled with various amounts of styrene containing 0.25–4.6 wt % benzoyl peroxide as initiator. Polymerization of the styrene in situ, by increase in temperature, gave novel elastomeric composites. Scanning electron micrographs suggest phase separation which is locked in at the microscopic level, with no evidence for the particulate domains seen in the similarly prepared polystyrene-polydimethylsiloxane system. The wt % polystyrene (PS) extractible increased with increase in initiator concentration, which is consistent with decrease in the lengths of the PS chains being formed and grafted onto the PIB. Mechanical properties obtained in continuous extension showed maxima in their dependence on composition. Specifically, the ultimate strength (f/A^*)_m, maximum extensibility ε_r, energy E_r required for rupture, and permanent set ΔL/L₀ generally showed maxima in the vicinity of 50 wt % PS. The shortest-chain PS samples generally showed the largest values of (f/A^*)_m, ε_r, and E_r, and the smallest values of ΔL/L₀.