A preliminary comparison of CIE color differences to textile color acceptability using average observers

Ninety‐six nylon pairs were prepared, including red, yellow, green, and blue standards, each at two lightness levels with CIE94 ΔE units ranging from 0.15 to 4.01. Visual assessments of acceptability were carried out by 21 females. Logistic regression compared visual results to four color‐difference equations, CIELAB, CMC, CIE94, and CIEDE2000. It was found that CMC most closely represented judgments of average observers. © 2005 Wiley Periodicals, Inc. Col Res Appl, 30, 288–294, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20124     

Visual evaluation at scale of threshold to suprathreshold color difference

Visual evaluation experiments of color discrimination threshold and suprathreshold color‐difference comparison were carried out using CRT colors based on the psychophysical methods of interleaved staircase and constant stimuli, respectively. A large set of experimental data was generated ranged from threshold to large suprathreshold color difference at the five CIE color centers. The visual data were analyzed in detail for every observer at each visual scale to show the effect of color‐difference magnitude on the observer precision. The chromaticity ellipses from this study were compared with four previous published data, of CRT colors by Cui and Luo, and of surface colors by RIT‐DuPont, Cheung and Rigg, and Guan and Luo, to report the reproducibility of this kind of experiment using CRT colors and the variations between CRT and surface data, respectively. The present threshold data were also compared against the different suprathreshold data to show the effect of color‐difference scales. The visual results were further used to test the three advance color‐difference formulae, CMC, CIE94, and CIEDE2000, together with the basic CIELAB equation. In their original forms or with optimized K_L values, the CIEDE2000 outperformed others, followed by CMC, and with the CIELAB and CIE94 the poorest for predicting the combined dataset of all color centers in the present study. © 2005 Wiley Periodicals, Inc. Col Res Appl, 30, 198–208, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20106     

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     

Testing CIELAB‐based color‐difference formulas

The CMC, BFD, and CIE94 color‐difference formulas have been compared throughout their weighting functions to the CIELAB components ΔL*, ΔC*, ΔH*, and from their performance with respect to several wide datasets from old and recent literature. Predicting the magnitude of perceived color differences, a statistically significant improvement upon CIELAB should be recognized for these three formulas, in particular for CIE94. © 2000 John Wiley & Sons, Inc. Col Res Appl, 25, 49–55, 2000     

Analysis of five sets of color difference data

In a systematic optimization process five sets of recent color difference data have been analyzed for commonalities. Adjustment of the X tristimulus values and application of a systematic, surround dependent S_L function was found to be beneficial in all cases. Other modifications of the CIE94 color‐difference formula were found to bring improvements only in some cases and may be spurious. Application of what seem to be nonsystematic scale factors in a range of 0.78–1.38 improve correlation between calculated and visual color differences in all cases. After optimization, calculated color difference values explain between 80–90% of the variation in visual color differences. Some of the datasets are shown not to be well suited for formula optimization. Optimization in all cases by set, for three sets of data by quadrant in the a^*b^* diagram, and for one set by subset did not reveal any additional systematic trends for improvement. It appears that the basic structure of CIE94, with the recommended modifications, is a good approximation as a model for color‐difference evaluation in the range from 0.5–10 units of difference. The model is surround dependent. A number of issues remain to be resolved. © 2001 John Wiley & Sons, Inc. Col Res Appl, 26, 141–150, 2001     

Optimization of color reproduction on CRT‐color monitors

In the present experimental study, we quantify the influence of the brightness and contrast levels of a CRT‐color monitor in the color reproduction of 60 Munsell chips distributed throughout the chromatic diagram. The images were captured by two CCD cameras, and the color differences were evaluated after reproducing the chips on a color monitor (the experiment was performed with 3 different monitors) for 9 combinations of brightness‐contrast levels. We evaluated the color differences with 3 different formulas: CIELAB, CIELUV, and CIE94. The results indicate that the optimal settings of a monitor, to minimize the color differences, is a medium or minimum brightness level in combination with a maximum contrast level. This combination ensures a more faithful color reproduction with respect to the original image. © 1999 John Wiley & Sons, Inc. Col Res Appl, 24, 207–213, 1999     

Simple estimation methods for the Helmholtz—Kohlrausch effect

Four kinds of simple estimation equations are proposed for the Helmholtz—Kohlrausch effect. Two of them can be used for luminous colors, and the other two for object colors. In each of luminous and object colors, the two estimation equations are given to each of the Variable-Achromatic-Color (VAC) and the Variable-Chromatic-Color (VCC) methods. All the equations are similar in type to the Ware—Cowan equation. They give the ratio between luminance (or metric lightness) of test color stimulus and its equivalent luminance (or equivalent lightness) directly. Though their computations are simple, they can apply to various H—K effects including their adapting luminance dependency. The applicable fields of the proposed equations are wider than those of the Ware—Cowan equation. The proposed equations can be applied to predict the H—K effect within the whole chromaticity gamut including spectral colors, spectral luminosity functions based on direct color matching from 0.01 Td to 100 000 Td using the photopic and the scotopic spectral luminosity functions specified by CIE, equivalent lightness values of NCS colors, and others. © 1997 John Wiley & Sons, Inc. Col Res Appl. 22, 385–401, 1997     

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     

Suprathreshold color-difference ellipsoids for surface colors

The RIT-DuPont visual color-difference data [Color Res. Appl. 16, 297–316 (1991)] have been used to estimate contours of equal color-differences (ellipsoids) at 19 color centers, in CIELAB and x, y, Y/100 color spaces. The ellipsoid fits are better in the CIELAB space than in x, y, Y/100, since the design of the RIT-DuPont experiment emphasized directional balance in CIELAB. The ellipsoids estimated are hardly tilted with respect to L* or Y/100, and they appear to be in overall good agreement with those reported for object colors in recent publications. From the characteristics and accuracy of the RIT-DuPont experiment, the current ellipsoids can be considered highly reliable and representative of color discrimination under the observational conditions employed, these closely following the “reference conditions” recently suggested by the CIE for industrial color-difference evaluation [Color Res. Appl. 20, 399–403 (1995)]. © 1997 John Wiley & Sons, Inc. Col Res Appl, 22, 148–155, 1997     

Visual determination of hue suprathreshold color‐difference tolerances using CRT‐generated stimuli

Suprathreshold hue color‐difference tolerances were measured at four color centers using CRT‐generated stimuli. The tolerances, defined using CIELAB, were measured using two different methods of presentation. In the Absolute Experiment, the stimuli were presented at luminance levels that matched those of the previous object‐color experiments, so that the CRT stimuli were nearly metameric to the originals. In the Relative Experiment, the white point of the monitor was defined as L* = 100 at a corresponding chromaticity to the object‐color viewing environment, but at a lower luminance level. The results from these two experiments followed the same general trends; however, they were significantly different from each other for three of the four color centers. The same trends were seen in the object‐color results, although neither CRT experimental condition produced tolerances that were conclusively more similar to the object‐color results than the other. The feasibility of the use of the CRT has been demonstrated. It is likely that parametric effects of stimulus presentation are the cause of the differences in results among the different experiments, as opposed to differences in the mode of appearance. These parametric effects can be studied more quickly and economically using a computer‐controlled CRT display. © 1999 John Wiley & Sons, Inc. Col Res Appl, 24, 164–176, 1999     

The shifting gamma perception

True to life, color display and color management depend on a proper technical model of the display used. Current gamma models and fitting procedures are not accurate in modeling the lower part of the tone reproduction curve. The GOG‐ and GOGO‐model used in color management standards tend to clip the luminance to zero for digital values were luminance can be seen and measured. Two improvements to the models are suggested. First, the models should be fitted by optimizing the root mean square error (RMSE) of the CIE lightness instead of the luminance. Second, a shifting gamma model is adopted, with gamma increasing in value for lower voltages. Results show that the adapted models correspond better with the luminance measurements. The clipping values are nearer to the measured zero luminance threshold, and the average RMSE and ΔE over the whole scale are smaller. © 2005 Wiley Periodicals, Inc. Col Res Appl, 30, 332–340, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.     

Correlation between visual and colorimetric scales ranging from threshold to large color difference

Psychophysical experiments of color discrimination threshold and suprathreshold color‐difference comparison were carried out with CRT‐generated stimuli using the interleaved staircase and constant stimuli methods, respectively. The experimental results ranged from small (including threshold) to large color difference at the five CIE color centers, which were satisfactorily described by chromaticity ellipses as equal color‐difference contours in the CIELAB space. The comparisons of visual and colorimetric scales in CIELAB unit and threshold unit indicated that the colorimetric magnitudes typically were linear with the visual ones, though with different proportions in individual directions or color centers. In addition, color difference was generally underestimated by the Euclidean distance in the CIELAB space, whereas colorimetric magnitude was perceptually underestimated for threshold unit, implying the present color system is not a really linear uniform space. Furthermore, visual data were used to test the CIELAB‐based color‐difference formulas. In their original forms CIEDE2000 performed a little better than CMC, followed by CIELAB, and with CIE94 showing the worst performance for the combined data set under the viewing condition in this study. © 2002 Wiley Periodicals, Inc. Col Res Appl, 27, 349–359, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.10081     

Concerning the calculation of the color gamut in a digital camera

Several methods to determine the color gamut of any digital camera are shown. Since an input device is additive, its color triangle was obtained from their spectral sensitivities, and it was compared with the theoretical sensors of Ives‐Abney‐Yule and MacAdam. On the other hand, the RGB digital data of the optimal or MacAdam colors were simulated to transform them into XYZ data according to the colorimetric profile of the digital camera. From this, the MacAdam limits associated to the digital camera are compared with the corresponding ones of the CIE‐1931 XYZ standard observer, resulting that our color device has much smaller MacAdam loci than those of the colorimetric standard observer. Taking this into account, we have estimated the reduction of discernible colors by the digital camera applying a chromatic discrimination model and a packing algorithm to obtain color discrimination ellipses. Calculating the relative decrement of distinguishable colors by the digital camera in comparison with the colorimetric standard observer at different luminance factors of the optimal colors, we have found that the camera distinguishes considerably fewer very dark than very light ones, but relatively much more colors with middle lightness (Y between 40 and 70, or L* between 69.5 and 87.0). This behavior is due to the short dynamic range of the digital camera response. © 2006 Wiley Periodicals, Inc. Col Res Appl, 31, 399–410, 2006; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20245     

Neural mechanisms of chromatic and achromatic vision

Building upon electrophysiological recordings from the lateral geniculate nucleus (LGN) of the macaque monkey, we describe a model for neural processing of color and brightness/lightness information that starts in the cone receptors and continues in the opponent cells of the retina, LGN, and visual cortex. The excitation of the three cone types to direct stimulation by light is modified in accordance with a hyperbolic response function before providing inputs to retinal ganglion cells. Using weighted differences of such cone outputs, we simulate the responses of common types of opponent ganglion and geniculate cells to light modulation along the chromatic and luminance dimensions. Extrapolating the results of the simulation, we suggest a way in which the brain might combine inputs from the geniculate to obtain correlates of chromatic and achromatic color vision and of brightness/lightness perception. In particular, we demonstrate for the first time how combinations of “L–M” and “M–L” parvocellular ON‐ and OFF‐opponent‐cells may lead to a quantitative account of brightness and blackness scaling. © 2008 Wiley Periodicals, Inc. Col Res Appl, 33, 433–443, 2008     

Euclidization of the first quadrant of the CIEDE2000 color difference system for the calculation of large color differences

The calculation of colour distances in the first quadrant of the CIEDE2000 space can be realized now after the author succeeded in working out such calculations in the CIE94 and CMC space in preceeding articles. The new system is presented and then the Euclidean line element is established, from which terms are derived for the new coordinates of lightness, hue, and hue angle. The calculations of colour distances are carried out with the new Euclidean coordinates according to a well‐known method and are demonstrated by examples guided by CIE94 and CMC distances from the preceeding articles. Finally, proposals are given for the eventual improvement of the CIEDE2000 formula. © 2005 Wiley Periodicals, Inc. Col Res Appl, 31, 5–12, 2006; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20168     

A Euclidean color space in high agreement with the CIE94 color difference formula

Many consider it futile to try to create color spaces that are significantly more uniform than the CIELAB space, and, therefore, efforts concentrate on developing estimates of perceived color differences based on non‐Euclidean distances for this color space. A Euclidean color space is presented here, which is derived from the CIELAB by means of a simple adjustment of the a* and b* axes, and in which small Euclidean distances agree to within 10.5% with the non‐Euclidean distances given by the CIE94 formula. © 2000 John Wiley & Sons, Inc. Col Res Appl, 25, 64–65, 2000     

The use of metamers to compare the color vision of observers

In this research we compare the colorimetric behavior of several observers. For color centers recommended by CIE we have produced large sets of spectral distributions, which are metameric for the CIE 1931 standard observer. For each one of the color centers, we compare the clouds of chromaticity coordinates with the chromaticity thresholds. We define a parameter that provides a quantitative measure of the interobserver variability. This parameter is used to arrange the observers by their degree of likeness. A similar procedure has been used to compare two real observers. It is shown how there is no reciprocity between the colorimetric behavior of two real observers. © 2001 John Wiley & Sons, Inc. Col Res Appl, 26, 262–269, 2001     

Color space and its divisions

A synthesis of the author's recent work on color‐order systems and color‐difference evaluation is provided in context of current knowledge and practices. The development of a colorimetric model is demonstrated using Munsell “Celtic crosses” as a model of perceptual space. Issues surrounding color‐matching functions, unique hues, the Helmholtz–Kohlrausch effect, and lightness and chroma crispening are addressed, as is the difficulty of reconciling a difference‐based hue, chroma, lightness model with an Euclidean model. A new lightness scale and treatment of lightness crispening is proposed. The results indicate that, despite problems, relatively simple modified opponent‐color models provide good accuracy in predicting color‐order system and supra‐threshold small color‐difference data. © 2001 John Wiley & Sons, Inc. Col Res Appl, 26, 209–222, 2001