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     

Lightness dependencies and the effect of texture on suprathreshold lightness tolerances

A psychophysical experiment was performed to determine the effects of lightness dependency on suprathreshold lightness tolerances. Using a pass/fail method of constant stimuli, lightness tolerance thresholds were measured using achromatic stimuli centered at CIELAB L* = 10, 20, 40, 60, 80, and 90 using 44 observers. In addition to measuring tolerance thresholds for uniform samples, lightness tolerances were measured using stimuli with a simulated texture of thread wound on a card. A texture intermediate between the wound thread and the uniform stimuli was also used. A computer‐controlled CRT was used to perform the experiments. Lightness tolerances were found to increase with increasing lightness of the test stimuli. For the uniform stimuli this effect was only evident at the higher lightnesses. For the textured stimuli, this trend was more evident throughout the whole lightness range. Texture had an effect of increasing the tolerance thresholds by a factor of almost 2 as compared to the uniform stimuli. The intermediate texture had tolerance thresholds that were between those of the uniform and full‐textured stimuli. Transforming the results into a plot of threshold vs. intensity produced results that were more uniform across the three conditions. This may indicate that CIELAB is not the best space in which to model these effects. © 2000 John Wiley & Sons, Inc. Col Res Appl, 25, 241–249, 2000     

A comparison of constant stimuli and gray‐scale methods of color difference scaling

Two psychophysical techniques, the method of constant stimuli and the gray‐scale comparison method, were used to determine color tolerances for three different color centers in the hue, chroma, and lightness directions in CIELAB color space. The same color‐difference pairs were used as the stimuli in both experiments. Although the results followed the same trends, they were different for the two techniques. Based on comparison of the validity and precision of the results, as well as the ease of implementation, use, and analysis, the method of constant stimuli is the preferable method. © 2002 Wiley Periodicals, Inc. Col Res Appl, 28, 36–44, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.     

RIT‐DuPont supra‐threshold color‐tolerance individual color‐difference pair dataset

The RIT‐DuPont dataset has been used extensively for formula development and testing since its inception during the 1980's, for example, in the development of CIE94 and CIEDE2000. The dataset was published as 156 color‐tolerances, T₅₀, along specific vector directions about 19 color centers. Probit analysis was used to transform judgments of 958 color‐difference pairs by 50 observers to these 156 tolerances. For most statistical significance testing, the number of samples determines the confidence limits. Thus, there was an interest in publishing the individual color‐difference pair visual and colorimetric data to improve the precision of significance testing. From these 958 pairs, 828 pairs had determinable visual differences. The others had either excessive visual uncertainty or had unanimous visual judgments such that visual differences were undefined. In addition, a method was devised to assign visual uncertainty to each of these pairs using the principles of maximum likelihood and the T₅₀ values. Comparisons were made between the T₅₀ and individual color‐difference pair data both including and omitting uncertainty weightings. The weighted dataset was found to be equivalent to the T₅₀ tolerances. © 2009 Wiley Periodicals, Inc. Col Res Appl, 2010     

Visual determination of suprathreshold color-difference tolerances using probit analysis

As part of a research program to improve the relationship between visual and numerical color-difference evaluation for industrial colorimetry, a color-difference tolerance data set for fitting and testing of color-difference metrics has been extended to include 156 individual color-tolerance determinations. These tolerances were designed to sample 19 color centers over a surface color gamut with balanced sampling of lightness and chromaticness differences. The tolerance determination procedures emphasized accurate estimation of population visual color-difference response and rigorous estimation of tolerance precision. Tolerance accuracy was confirmed by excellent agreement of these results and the majority of previous experiments on five color centers selected for CIE color-difference evaluations. The average uncertainty of the tolerance determinations was ± 11% of the tolerance value at a 2 ó level (95% confidence interval). The completed data set is suitable for estimating the parameters of color-difference metrics or testing the performance of such metrics. The color tolerances indicated the systematic lack of uniformity of the CIELAB space, in general agreement with previous experiments. A simple modification of the CIELAB color-difference metric was shown to account for much of the systematic lack of uniformity.     

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     

Evaluation of methods for verifying the performance of color‐measuring instruments. Part II: Inter‐instrument reproducibility

Part I described an experiment in which the repeatability of a number of common, commercially available spectrocolorimeters was compared using ASTM procedures. ASTM E2214‐02 Standard Practice for Specifying and Verifying the Performance of Color‐Measuring Instruments is intended to standardize the terminology and procedures used to evaluate color measuring instruments. In this article, we develop reproducibility results from a medium‐term study of 10 commercial spectrocolorimeters. The comparisons are presented so as to contrast between the traditional color difference based specifications found in the historical literature and in manufacturer's literature and the more complex multidimensional methods specified in E2214. Instrument to instrument contrasts are reported as well as tests of agreement across a set of instruments as a whole. The results confirm common understandings. Hemispherical diffuse instruments exhibit a higher level of inter‐instrument agreement than do bidirectional (45:0) instruments. The results also provide support for a surprising conclusion about the statistical significance of the minor differences in both inter‐instrument agreement and inter‐model agreement for a single manufacturer. Some speculations on the impact of these conclusions to the development of future comparisons of spectrocolorimeters are given. © 2007 Wiley Periodicals, Inc. Col Res Appl, 32, 176–294, 2007     

Evaluation of methods for verifying the performance of color‐measuring instruments. Part I: Repeatability

A recent ASTM specification (ASTM E2214‐02) was created to standardize the terminology and procedures used to evaluate color measuring instruments. This specification addresses the need for uniformity among the manufacturers of such instruments when quantifying the performance of their products. The scope of E2214 is necessarily large, covering the procedures required to compare instruments for a variety of metrics, all of which are important to their overall performance. In this work, we will focus on one aspect of the instrument evaluation: repeatability performance. We will present repeatability results from a long‐term study of twelve commercial spectrophotometers. Comparisons will be made between traditional color difference metrics and the more complex multidimensional methods specified in E2214. © 2007 Wiley Periodicals, Inc. Col Res Appl, 32, 166–175, 2007     

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     

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     

Prediction of Munsell appearance scales using various color‐appearance models

The chromaticities of the Munsell Renotation Dataset were applied to eight color‐appearance models. Models used were: CIELAB, Hunt, Nayatani, RLAB, LLAB, CIECAM97s, ZLAB, and IPT. Models were used to predict three appearance correlates of lightness, chroma, and hue. Model output of these appearance correlates were evaluated for their uniformity, in light of the constant perceptual nature of the Munsell Renotation data. Some background is provided on the experimental derivation of the Renotation Data, including the specific tasks performed by observers to evaluate a sample hue leaf for chroma uniformity. No particular model excelled at all metrics. In general, as might be expected, models derived from the Munsell System performed well. However, this was not universally the case, and some results, such as hue spacing and linearity, show interesting similarities between all models regardless of their derivation. © 2000 John Wiley & Sons, Inc. Col Res Appl, 25, 132–144, 2000     

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     

Theoretical considerations on small color differences ascribed to the standard observer made on the basis of individual color‐matching functions

An analytical method to determine how color‐matching functions influence the perception of chromaticity differences is proposed. We show that, as a consequence of the observer metamerism, a metameric color‐match perceived by one observer may appear to be a significant mismatch to a different observer. It is also shown that, on average, the differences between the color‐matchings made by two different observers can be estimated to be in the order of 2 CIELAB units. © 2009 Wiley Periodicals, Inc. Col Res Appl, 34, 194–200, 2009     

Study of color perceptibility of gonio‐apparent panels with curvature angle

Color tolerances of curved gonio‐apparent panels have been studied in this work. To achieve that, an experimental set‐up of the illumination and tilt variation of two identical coated panels was designed for simulation of curved panels with both concave and convex borders and with and without effect pigments (perceived as solid and gonio‐apparent colors, respectively). Finally, visual and instrumental measures were collected with both curvatures. The results show that the relationship of the instrumental color difference with the tilt angle can be modeled by a second‐order and the vertex did not depend on illumination, but on coating type. The critical angles (the angle marked when the color discrepancy between two identical samples is merely perceived) assessed by the observers showed that they were not equal according to border, nor according to coating type. The color tolerances at these angles were clearly higher than the conventional chromatic thresholds of industrial color comparisons.     

Comparison of unique hue stimuli determined by two different methods using Munsell color chips

Unique hue stimuli were determined by male and female observers using two different visual experimental procedures involving Munsell color chips of varying hue but identical chroma and value. The hypothesis was that unique hues can be more reliably established by explicit selection from a series of ordered stimuli than implicitly by hue scaling a series of stimuli in terms of neighboring UHs and this was statistically confirmed. The implicit selections based on long term memory of UHs appears to have been more challenging to observers since variability was increased by nearly 50% compared to when UHs were explicitly selected. The ranges of unique hues selected in the two methods were, however, comparable and no statistically significant difference was found between the results of females and males. The intra‐observer variability in picking a stimulus to represent a unique hue, for all observers and averaged for all hues, was approximately 12% of the mean spread of unique hues, confirming that the large inter‐observer variability is driven by differences in color vision and perhaps cognitive processes. © 2010 Wiley Periodicals, Inc. Col Res Appl, 2010     

An integrated color‐appearance model using CIELUV and its applications

A new type of color‐appearance model is presented together with its formulations. It is named In‐CAM(CIELUV), which means the integrated color‐appearance model using CIELUV space. Using the In‐CAM(CIELUV), we can integrate its fields of applications in both colorimetric engineering and artistic color design. Various applications are introduced in colorimetric and color design fields. The In‐CAM(CIELUV) connects directly colorimetric color space and perceptual Hue‐Tone color order systems. In other words, the In‐CAM (CIELUV) gives a colorimetric basis for Hue‐Tone system. The three color attributes in the In‐CAM(CIELUV) space are mutually independent. This is a very convenient feature for selecting color combinations. Some two‐color combinations selected systematically in the In‐CAM(CIELUV) space are shown. © 2008 Wiley Periodicals, Inc. Col Res Appl, 33, 125–134, 2008     

Digital color reconstructions of cultural heritage using color‐managed imaging and small‐aperture spectrophotometry

There are many examples of cultural heritage having optical properties that have changed with the passage of time. Examples include the yellowing, darkening, and fading of paints and varnishes caused by light exposure and atmospheric pollution. When it is infeasible to treat an object, an image simulation can provide a view to the past, known as a color reconstruction. A technique is described that relies on a color‐managed image, spectral reflectance factor measurements of the object, an optical model of colorant mixing, an optical database of artist materials, spreadsheet software, and image editing software. Spectral calculations are used to create adjustment curves where segmented portions of an object's image are translated in color. This approach has been used to produce color reconstructions of paintings by Vincent van Gogh and Georges Seurat. This colorimetric translation methodology is described and an example shown for the Chicago version of Vincent van Gogh's Bedroom. The methodology is compared with pixel‐based processing.     

Semantic interpretation of color differences and color‐rendering indices

A series of visual experiments were carried out to rate the similarity of color appearance of two color stimuli on categorical and continuous semantic rating scales. Pairs of color stimuli included two copies of the same colored real or artificial object illuminated by a test light source and a reference light source. A formula was developed to predict a category of color similarity (e.g., “moderate” or “good”) from an instrumentally measured color difference. Given a numeric value of a color difference between the two members of a pair of colors, for example, 2.07, the formula is able to predict a category of color similarity, for example, “good.” Because color‐rendering indices are based on color differences, the formula could be applied to interpret the values of the new color‐rendering index (n‐CRI or CRI2012) in terms of such semantic categories. This semantic interpretation enables nonexpert users of light sources to understand the color‐rendering properties of light sources and the differences on the numeric scale of the color‐rendering index in terms of regular language. For example, a numeric value of 87 can be interpreted as “good.” © 2013 Wiley Periodicals, Inc. Col Res Appl, 39, 252–262, 2014; Published online 14 March 2013 in Wiley Online Library ( wileyonlinelibrary.com ). DOI 10.1002/col.21798     

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     

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