Chromatic discrimination in relation to luminance level

We have measured the chromatic‐discrimination ellipses with different luminances for 66 stimuli distributed throughout the CIE‐1931 chromatic diagram. The distribution of these stimuli enabled us to analyze the influence of luminance on discrimination from clearly photopic levels to levels that could enter the mesopic range. The results show a clear influence of the luminance level on the areas of the chromatic‐discrimination ellipses. These areas remain almost constant when the luminance level is clearly photopic, and clearly increase when the luminance diminishes. However, it is not necessary that the luminance level diminish far below 2–3 cd/m² to detect a substantial increase in the area of the ellipses. According to our data, within the photopic range appears a transition interval of luminance above which the most pronounced increase in the area of the ellipse would be appreciable. Other parameters characteristic of discrimination ellipses, such as orientation and relation to semi‐axes, vary with the luminance level, although without clearly following any rule. © 2001 John Wiley & Sons, Inc. Col Res Appl, 26, 123–131, 2001     

Color discrimination results from a CRT device: Influence of luminance

In this article, we report new color discrimination ellipsoids calculated from two normal observers, using a CRT device and five values of luminance at each of the five centers recommended by the CIE in 1978 (Col Res Appl 1978;3:149–151). Our main goal was to test the weighting function for lightness adopted by the CIE94 color‐difference model (CIE Publication 116, 1995). Although some of the experimental conditions employed here (CRT monitor, small size of the visual field, and controlled exposure time) did not fit those recommended by this model, our results support the weighting function for lightness proposed by CIE94. The only robust trends observed in the ellipsoids obtained were a confirmation of Weber's law and a decrease in the area of the x, y chromaticity ellipses, when the luminance of each reference stimulus increased towards the one of the surround. © 1999 John Wiley & Sons, Inc. Col Res Appl, 24, 38–44, 1999     

Categorical formation of Mandarin color terms at different luminance levels

This study presents the categorical formation of a set of Mandarin color terms on the International Commission on Illumination (CIE) 1931 chromaticity diagram across six luminance levels. This article conducted a study that employed 44 native Mandarin speakers to perform a force–choice sorting task. The Mandarin color terms for sorting were determined by a free‐recall pretest and are consistent with basic color terms proposed by Berlin and Kay. The square‐sampled stimuli were generated by evenly sweeping the x–y diagram of 5, 10, 25, 50, 100, and 170 cd/m² planes. The categorical sorting results and response time (RT) measurements suggest that: (1) the concepts of green, blue, purple, and gray stably exist at most luminance levels. The voting RT for the green, blue, and purple categories is particularly short. (2) Red, orange, yellow, and pink are highly luminance‐dependent; these can be identified without difficulty only at some restricted luminance levels. (3) The chromaticity areas designated as orange, partial yellow, red, and pink are recognized as brown when the luminance level decreases. (4) Brown and gray serve as representations of two distinct tints in the low saturation condition. (5) The location of boundaries between blue and green are remarkably different than those in a similar study that employed Japanese speakers. © 2011 Wiley Periodicals, Inc. Col Res Appl, 2011.     

On the relationship between tilt of a*b* tolerance ellipses in blue region and tritanopic confusion lines

There is reasonable agreement between the orientation of the major axes of the a*b* tolerance ellipses in the blue region and the slope of the tritanopic confusion lines passing through their centers. This agreement includes some experimental facts such as the approximate constant orientation of the ellipses when the luminance of the center changes and the clockwise rotation of the major axis of the ellipses when the luminous source D65 is replaced by A. However, the tilts predicted by the tritanopic lines do not follow the pattern proposed by the CIEDE2000 color‐difference formula; in particular, for the blue‐green centers with hue angles lower than 255°, the high tilts predicted by the tritanopic lines are quite different. From 132 ellipses previously reported, we found that the orientations of the 17 ellipses in the blue region (255° < h < 320°) were similarly predicted by both CIEDE2000 and the tritanopic confusion lines (average error of 12.2° in absolute value). © 2002 Wiley Periodicals, Inc. Col Res Appl, 27, 180–184, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.10053     

An adaptive color similarity function suitable for image segmentation and its numerical evaluation

In this article, we present an adaptive color similarity function defined in a modified hue‐saturation‐intensity color space, which can be used directly as a metric to obtain pixel‐wise segmentation of color images among other applications. The color information of every pixel is integrated as a unit by an adaptive similarity function thus avoiding color information scattering. As a direct application we present an efficient interactive, supervised color segmentation method with linear complexity respect to the number of pixels of the input image. The process has three steps: (1) Manual selection of few pixels in a sample of the color to be segmented. (2) Automatic generation of the so called color similarity image (CSI), which is a gray level image with all the gray level tonalities associated with the selected color. (3) Automatic threshold of the CSI to obtain the final segmentation. The proposed technique is direct, simple and computationally inexpensive. The evaluation of the efficiency of the color segmentation method is presented showing good performance in all cases of study. A comparative study is made between the behavior of the proposed method and two comparable segmentation techniques in color images using (1) the Euclidean metric of the a* and b* color channels rejecting L* and (2) a probabilistic approach on a* and b* in the CIE L*a*b* color space. Our testing system can be used either to explore the behavior of a similarity function (or metric) in different color spaces or to explore different metrics (or similarity functions) in the same color space. It was obtained from the results that the color parameters a* and b* are not independent of the luminance parameter L* as one might initially assume in the CIE L*a*b* color space. We show that our solution improves the quality of the proposed color segmentation technique and its quick result is significant with respect to other solutions found in the literature. The method also gives a good performance in low chromaticity, gray level and low contrast images. © 2016 Wiley Periodicals, Inc. Col Res Appl, 42, 156–172, 2017     

Properties of polymer light‐emitting diodes coated on surface‐treated ITO/glass substrates

We fabricated blue polymer light‐emitting diodes (PLEDs) with indium tin oxide (ITO)/PEDOT : PSS/PVK/PFO‐poss/LiF/Al structures. All of the organic film layers were prepared by the spin‐coating method on plasma and heat‐treated ITO/glass substrates. The dependences of the optical and electrical properties of the PLEDs on the plasma and heat treatment of the ITO film and the introduction of poly(N‐vinylcarbazole) (PVK) layer were investigated. The AFM measurements indicated that the surface roughness of the ITO transparent film was improved by the plasma and heat treatment. In the emission spectra, the intensity of the excimer peaks of the PFO‐poss [polyhedral oligomeric silsesquioxane‐terminated poly(9,9‐dioctylfluorene)] emission layer were decreased for the PLED device with the PVK film layer compared with the one without the PVK layer. The maximum current density, luminance and current efficiency of the PLEDs were found to be about 470 mA/cm², 486 cd/m² at an input voltage of 12 V and 0.55 cd/A at 100 cd/m² in luminance, respectively. The color coordinates (CIE chart) of the blue PLEDs were in the range of x = 0.17 ～ 0.20, y = 0.13 ～ 0.16, and the peak emission spectrum was about 430 nm, showing a good blue color. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2008     

Color of natural tooth crown in Japanese people

The aim of this study was to investigate the color of the natural maxillary incisor tooth from Japanese people of all age groups. These results were compared with the Trubyte Bioblend shade guide. The subjects of this study were in the age range of 13–84, 42 male and 45 female making 87 people in total. Areas with 1.0‐mm diameter at five sites were measured along the tooth axis for L*,a*,b*, according to CIELAB color spaces using a Spectroradiometric Color Computer. At the incisal site, two significant positive correlations were found between age and a* (r = 0.376, p < 0.001), and b* (r = 0.483, p < 0.001). At the center site, a significant negative correlation (r = −0.418, p < 0.001) was found between age and L*, but positive correlation (r = 0.497, p < 0.001) was found between age and b*. At the cervical site, a significant negative correlation (r = −0.326, p < 0.01) was found between age and L*, but positive correlation (r = 0.702, p < 0.001) was found between age and b*. Near the root, particularly, the values of a* were greater than those suggested by the Trubyte Bioblend shade guide. In conclusion, as the Trubyte Bioblend shade guide does not match the natural tooth color in red‐green chromaticity near the root, it is significant for us in dentistry to develop new shade guides that match the Japanese people based on the data collected. © 2000 John Wiley & Sons, Inc. Col Res Appl, 25, 43–48, 2000     

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     

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     

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     

The Weber fraction and asymmetries in luminance thresholds

Presented in this article is a method for the determination of the Weber fraction by analyzing data obtained from color‐matching experiments. The method is based on a rigorous analysis of the probability density function derived from discrimination judgments made in the xyY space. Analysis shows the thresholds for luminance increments and decrements are shown to be different and asymmetric and the Weber fraction to depend on the target's level of luminance and chromaticity. © 2002 Wiley Periodicals, Inc. Col Res Appl, 27, 330–334, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.10079     

Computational tongue color simulation in tongue diagnosis

Tongue color is one of the important indices for tongue diagnosis in traditional Chinese medicine. This study aims to analyze tongue colors of computational tongue diagnosis in traditional Chinese medicine using scientific quantification and computational simulation. The tongue color data are established according to the experiment in which the doctors who use Chinese traditional medicine assessed standard Munsell color charts under the standard lighting environment. Tongue color is classified into six color names, which are pale red, light red, red, crimson, dark red, and purple. The doctors assessed Munsell color charts to find the corresponding color charts' distributions of each color name in tongue color. The hue-lightness-chroma data of the chosen Munsell color charts were transformed to CIE xyY using the look-up table computation, then further were converted to CIELAB values and sRGB data. Based on the 95% confidence ellipses formed on CIELAB (a^*, b^*) plane and CIELAB (C^*, L^*) plane, the comparisons between tongue colors and general colors were analyzed. The computational tongue image simulation combining the elements of color, texture, and moisture was successfully established. This computational simulation method could potentially become a useful tool for teaching and learning diagnoses in the education of Chinese medicine.     

Why higher resolution graphics cards are needed in colour vision research

The colour resolution of a 14‐bit and an 8‐bit per channel graphics card were evaluated and compared with the just noticeable difference between colours (varying only in luminance) for: (1) a standard observer (based on the CIE 1976 L*u*v* colour space) and (2) real observers in a colour discrimination task. The results of this study show that an 8‐bit per channel graphics card seems adequate for colour discrimination experiments where stimuli only vary in luminance. However, considering that the resolution of the graphics card should be equal to the Nyquist rate, an 8‐bit per channel card turns out to be inadequate. For colour discrimination experiments where stimuli only vary in chromaticity, there is an undersampling of the colour space with respect to MacAdam ellipses when using 8‐bit per channel graphics cards. The extremely fine colour resolution of a 14‐bit per channel graphics card overcomes these problems. Its use allows more accurate measurements of achromatic and chromatic discrimination thresholds and avoids experimental (spatial or luminance) artefacts, such as bandings that can occur on achromatic or chromatic gradients. © 2010 Wiley Periodicals, Inc. Col Res Appl, 2011     

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     

Theoretical analysis of inter‐observer variability in the determination of luminance thresholds

We present an analytical method to analyze, from a theoretical point of view, the influence of color‐matching functions on the perception of luminance thresholds. We show that the thresholds depend on the spectral responsivities of each observer. We also analyze the influence of luminance level on the thresholds: a strong inter‐observer variability is found at low or moderate luminance levels (0.02 < Y < 1 ft?L) whereas at high intensities (1 < Y < 7 ft?L) the thresholds are observer‐independent. © 2006 Wiley Periodicals, Inc. Col Res Appl, 31, 468–474, 2006; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20259     

Automatic detection of layout of color yarns of yarn‐dyed fabric. Part 2: Region segmentation of double‐system‐Mélange color fabric

To detect the layout of color yarns automatically, a novel projection‐based fabric segmentation method is proposed to segment the double‐system‐mélange color fabric into several regions, which can be seen as single‐system‐mélange color fabrics. This method consists of five main steps: (1) yarn skew detection, (2) fabric image projecting, (3) projection curve smoothing, (4) variance curve calculating, and (5) curve peak confirmation. Based on the acquisition fabric image, the skew angles of warp and weft yarns are detected by Hough transform first. The projection curves of L, a, and b channels in Lab color model are generated and smoothed by Savitzky–Golay filter. The variance curves of L, a, and b are then calculated, and the peaks corresponding to the regional boundaries in each curve are detected. The regional boundaries are confirmed by synthesizing the curve peaks of L, a, and b. The experimental and theoretical analysis proves that the proposed method can segment the double‐system‐mélange color fabric into regions with satisfactory accuracy and good robustness. © 2015 Wiley Periodicals, Inc. Col Res Appl, 41, 626–635, 2016     

Chromaticity‐matched but spectrally different light source effects on simple and complex color judgments

As light‐emitting diode (LED) light sources mature, lighting designers will be able to deliver white light with a variety of spectral power distributions and a variety of color rendering properties. This experiment examined the effects of three spectral power distributions (SPDs) that were matched in illuminance and chromaticity on three measures of color perception: one objective (performance on the Farnsworth‐Munsell 100 hue test) and two subjective (judgments of the attractiveness of one's own skin, and preferences for the saturation of printed images). The three SPDs were a quartz‐halogen (QH) lamp and two LED sources that were matched to the QH lamp in terms of both illuminance and chromaticity; the three light sources were nominally CCT = 3500 K, x = 0.40, y = 0.39 and ～ 400 lx. LED A used three channels (red, green, blue), and had very poor color rendering (R_a = 18). LED B used four channels (red, amber, cyan, white) and had very good color rendering (R_a = 96, whereas the QH had R_a = 98). Secondary hypotheses addressed the effects of age and skin and eye color on the dependent measures. As expected, LED A delivered very different color perceptions on all measures when compared to QH; LED B did not differ from QH. The results show that it is possible for LED sources to match the familiar incandescent sources. However, although it is possible to deliver what appear to be millions of colors with a three‐chip (RGB) device, there is the risk of creating a very poor luminous environment. © 2013 National Research Council Canada and Wiley Periodicals, Inc. Col Res Appl, 39, 263–274, 2014; Published Online 12 April 2013 in Wiley Online Library ( wileyonlinelibrary.com ). DOI 10.1002/col.21811     

Chroma,chromatic luminance,and luminous reflectance. Part I: Basic research and illustration of relations

Chromatic luminance carries both wavelength and radiance of light, is the source of all psychophysical dimensions and all color attributes, and is a key to understand their relations. It has long attracted research, hindered in the past by flawed definitions of colorimetric purity (p_c), remedied in a recent article. This article investigates relations between luminous reflectance Y (i.e., total luminance, chromatic plus achromatic), chromatic luminance (calculated from Y per p_c), and chroma/colorfulness. Relations are clarified, illustrated by formulas and graphs including three‐dimensional schemas of luminance Y, chromatic luminance, and color solids. A useful new term, relative chromatic luminance, is introduced. Munsell chroma is shown to resemble inverted log luminance much more closely than inverted log colorimetric purity as claimed by previous researchers. The relationship is used in Part II to model chroma, colorfulness, and brightness. © 2008 Wiley Periodicals, Inc. Col Res Appl, 34, 45–54, 2009.     

Effects of cold plasma on the color parameters of Hyssop (Hyssopus officinalis L.) using color imaging instrumentation and spectrophotometer

This research was conducted to evaluate the effects of cold atmospheric plasma treatment on the color of Hyssop (Hyssopus officinalis L.) and also to compare the usage of the spectrophotometer vs the color imaging instrumentation for the evaluation of the treatment on the color parameters. The experiments were investigated at different treatment times of 1, 5, and 10 minutes and the voltage values of 17, 20, and 23 kV. Possible changes of color were evaluated by using CIE L*a*b* values obtained with HunterLab colorimeter and CIE L*a*b* values obtained with a digital still camera (DSC) using digital image processing (MATLAB software). The values of L*, a*, and b* of the samples were obtained using both the methods. The results revealed that the L*, a*, and b* values of the treated Hyssop samples changed with increasing the treatment time and the voltage applied. Evaluating the interaction effects revealed that there was a significant difference in the (−a^*/b^* ) ratio. In addition, the results showed that the effects of all variables on the color parameters were significantly different in the case of the DSC using digital image processing. However, these effects were not significantly different using HunterLab colorimeter except for time variable and interaction effects of a* and (−a^*/b^* ) ratio. The lightest green color and the maximum chlorophyll content loss were observed for 23 kV applied over 10 minutes. Based on the results, the digital image processing can be used as a practical tool to study the variations at the color of dried Hyssop leaves after cold plasma treatment.     

Image quality evaluation for high dynamic range and wide color gamut applications using visual spatial processing of color differences

High dynamic range (HDR) and wide color gamut imagery has an established video ecosystem, spanning image capture to encoding and display. This drives the need for evaluating how image quality is affected by the multitudes of ecosystem parameters. The simplest quality metrics evaluate color differences on a pixel‐by‐pixel basis. In this article, we evaluate a series of these color difference metrics on four HDR and three standard dynamic range publicly available distortion databases consisting of natural images and subjective scores. We compare the performance of the well‐established CIE L*a*b* metrics (ΔE₀₀ , ΔE₉₄ ) alongside two HDR‐specific metrics (ΔE_Z [J_za_zb_z], ΔE_ITP [IC_TC_P]) and a spatial CIE L*a*b* extension (). We also present a novel spatial extension to ΔE_ITP derived by optimizing the opponent color contrast sensitivity functions. We observe that this advanced metric, , outperforms the other color difference metrics, and we quantify the improved performance with the steps of metric advancement.