CIELAB color space boundaries under theoretical spectra and 99 test color samples

A color space is a three-dimensional representation of all the possible color percepts. The CIE 1976 L*a*b* is one of the most widely used object color spaces. In CIELAB, lightness L* is limited between 0 and 100, while a* and b* coordinates have no fixed boundaries. The outer boundaries of CIELAB have been previously calculated using theoretical object spectral reflectance functions and the CIE 1931 and 1964 observers under the CIE standard illuminants D50 and D65. However, natural and manufactured objects reflect light smoothly as opposed to theoretical spectral reflectance functions. Here, data generated from a linear optimization method are analyzed to re-evaluate the outer boundaries of the CIELAB. The color appearance of 99 test color samples under theoretical test spectra has been calculated in the CIELAB using CIE 1931 standard observer. The lightness L* boundary ranged between 6 and 97, redness-greenness a* boundary ranged between −199 and 270, and yellowness-blueness b* boundary ranged between −74 and 161. The boundary in the direction of positive b* (yellowness) was close to the previous findings. While the positive a* (redness) boundary exceeded previously known limits, the negative a* (greenness) and b* (blueness) boundaries were lower than the previously calculated CIELAB boundaries. The boundaries found here are dependent on the color samples used here and the spectral shape of the test light sources. Irregular spectral shapes and more saturated color samples can result in extended boundaries at the expense of computational time and power.     

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.     

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     

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.     

Optimization of color design for military camouflage in CIELAB color space

The assessment of military camouflage is a key consideration in the modern military field. Traditionally, the assessment relies on traditional human visual detection tests because a large scale multi‐level and multi‐factor experiments are time‐ and resource‐consuming. One aspect of camouflage assessment, to which this current study pertains, entails improving upon or “enhancing” an existing or “selected” design. The current study presents a new and practical approach for enhancing the selected military camouflage by utilizing response surface methodology (RSM) of %L*, %a*, and %b* in CIELAB color space. Ten participants were recruited to evaluate 35 variations of %L*, %a*, and %b* on camouflage similarity index (CSI) and reaction time (RT). Based on RSM, the optimum combination occurs at L*: 61.4966, a*: ?5.6505, and b*: 10.5114. In addition, a predictive algorithm to calculate the optimum shift of %L*, %a*, and %b* from the original camouflage to the improved camouflage derived from RSM is also proposed. The optimum shift occurs at ?25%L*, ?55%a*, and + 80%b*. In the end, a new design guideline is proposed for the enhancement of selected military camouflage, which adopts the present study's research findings.     

Color difference measurement and color removal from dye wastewaters using different adsorbents

Pollution from textile mills is a problem of formidable dimensions and color removal is the most perplexing problem facing environmental engineers designing appropriate treatment facilities for textile wastewaters. The CIE colorimetric system has been used in this study to measure the color in the treatment of disperse-red-60 dye wastewater using different adsorbents. The color removal is determined by using the CIE 1976 L*a*b* (CIELAB) color difference equation. The effect of contact time and dosage on color and color removal has been investigated for various adsorbents, namely, powdered activated carbon, granular activated carbon, activated alumina, molecular sieves and diatomite.     

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     

Research on the detection of fabric color difference based on T‐S fuzzy neural network

T‐S fuzzy neural network algorithm is used to establish the mapping relationship from the RGB space to the L*a*b* space, which avoids the complex process of color space conversion. Meanwhile, the block method is adopted to detect color difference of dyed fabric that is wide format and wide viewing angle. Color differences in different regions can be calculated with Color Measurement Committee color difference formula based on T‐S fuzzy neural network. Experimental results are in accordance with the spectrophotometer measurement, which proves that T‐S fuzzy neural network algorithm used in real‐time color detection process is effective and feasible. Workers can make corresponding adjustment on‐line according to the deviation to ensure the quality of fabric color and reduce the loss.     

Low‐temperature UV irradiation induced the color change kinetics and the corresponding structure development of PVC film

The low‐temperature ultraviolet (UV) irradiation equipment, developed in our Lab, was used to study the photo‐aging of poly (vinyl chloride) (PVC) films at low temperature. The color change kinetics and corresponding structure development of PVC film during low‐temperature UV aging were studied through L*a*b* coordinates Commission International d' Eclau‐age (CIE 1976 color space) and Ultraviolet spectrophotometer (UV–vis) and Fourier transform infrared spectroscopy (FTIR). It was found that the yellowness difference (?b*) and color difference (?E*) of the PVC film increased almost linearly with the aging time. Their values had a slower change at lower temperature. The kinetic study showed that the relationship between the velocity of coloration of the PVC film and the temperature agreed well with Arrhenius equation at low temperature. The activation energy of coloration of the PVC film was calculated. The FTIR spectra indicated that photo‐dehydrochloration, resulting in the generation of conjugated carbon–carbon double bonds, was the main reaction for PVC during photo‐aging at low temperature. Meanwhile, the photo‐oxidation was also obvious and could not be neglected. It clearly confirmed that the absorption peaks of conjugated carbon–carbon double bond increased and shifted to longer wavelength during photo‐aging in the UV‐abs analysis. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2011.     

Formulating Pantone colors by unused base inks,formulation software,and a spectrophotometer

Unused base inks that are not going to be used for printing production are considered to be hazardous materials. Their disposal is expensive, and strict environmental regulations should be followed for their disposal. As an alternative, this article describes how spectral data of unused base inks can be gathered and mixed to generate new colors to incorporate them back to print production for small‐volume jobs. In this study, 30 different Pantone colors were selected as target colors. The CIE L*a*b* spectral data of Pantone colors and unused base inks were gathered via a spectrophotometer. A commercial formulation software, based on multiflux theory and CIE L*a*b* color space, was used to formulate ink recipes that contained the base inks. To quantify the performance of ink recipes, they were mixed and printed using an offset printability tester. The CIELAB ΔE*_ab metric, developed by CIE, was used to detect the visual differences between the target Pantone Color and printed colors.     

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     

Effect of Dipping Temperature and Dipping Time on Drying Rate and Color Change of Grapes

Thompson seedless grapes (Vitis vinifera) were pretreated in potassium carbonate and ethyl oleate solutions for 1, 2, and 3 min at 30, 40, 50, and 60°C and dried in a convective air dryer at 60°C. The effect of dipping time and solution temperature on drying rate and color kinetics were investigated. Grapes dipped into the solution at 60°C for 2 and 3 min had the fastest drying rate. Among the seven semi theoretical models compared, the Midilli equation best described the drying curves of grapes for all dipping pretreatments. Color data were obtained using a machine vision system in CIE L*a*b* color space. Regardless of the dipping time and temperature applied, all raisins had varying degrees of brown coloring. At all dipping times and temperatures the highest R ² value was obtained for a* values, which followed zero-order reaction kinetics during drying.     

Effect of orange fiber addition on yogurt color during fermentation and cold storage

Orange fiber obtained from orange juice by‐products was added to yogurt. Fiber (0%, 0.6%, 0.8%, and 1% doses and different fiber size: 0.417–0.701 and 0.701–0.991 mm) effects on color during yogurt fermentation and cold storage were studied. Overall composition, pH, acidity, syneresis, L*, a*, and b* values were determined. Sensory evaluation of yogurts was carried out. Fiber addition did not cause changes in yogurt acidification and color during fermentation process, though decreased L* value and increased b* value of the milk. Color evaluation along fermentation is pH dependent (R > 0.870). pH decreased and syneresis increased along cold storage. Because of the acidification process, L* value decreased and a* and b* values increased in all yogurts. Yogurts with 1% fiber were significantly different from the others along cold storage, presenting lower L*, higher a* and b* values, and lower syneresis. © 2005 Wiley Periodicals, Inc. Col Res Appl, 30, 457–463, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20158     

A general form of color difference formula based on color discrimination ellipsoid parameters

A general color difference formula has been derived based on the parameters of color discrimination ellipsoids in the CIE 1976 L*a*b* color space. By using different orders of approximation, the general formula resembles the basic forms of the current formulae. The method described in this article suggests a framework for modifying the CIE 1976 L*a*b* color difference formula.     

Design and study of a color sensitivity function

If we study color reproduction, such as computer color matching or the appraisal of metametric index, we wish to understand the characteristic of color differences that are caused by the object spectral reflectivity change at each wavelength. If we simulate the light source, we wish to know the characteristics of color differences that are caused by change in relative power distribution of the light source at each wavelength; if we simulate a human eye instrument, we wish to know the characteristics of color differences that are caused by change in visual sense of human eyes at each wavelength. So, we define the color‐sensitivity functions of an object, a light source, and human eyes. According to the chromatic theory, the color‐sensitive functions of an object, a light source, and human eyes are defined in the widely used CIE1976 (L*a*b*) color space and color difference.¹ Their mathematical formulae are deduced. The three kinds of color‐sensitive functions are studied systematically and comprehensively in the whole color space. The characteristics of the color‐sensitive functions are summarized, and the mathematical models of the three kinds of color‐sensitive functions can be utilized in some fields such as computer color matching, simulation of a standard light source, and humans viewing a colorimeter. © 2005 Wiley Periodicals, Inc. Col Res Appl, 30, 118–124, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20089     

Optimization of quinacridone magenta,Cu-phthalocyanine cyan,and arylide yellow ink films formulated for maximum color gamut

Investigation of ink formulation options with the purpose to obtain color-gamut-optimal set of Cyan Magenta and Yellow CMY inks is reported. Implementation of the thickness dependent Kubelka-Munk model on multiple ink layers having different and well-defined thicknesses, provides characteristic absorption and scattering (K, S ) spectra of the ink ingredients. These data enable accurate computation of the reflectance spectrum and thus the L*a*b* color coordinates for any given ink thickness or substrate. Pigment materials investigated are quinacridone as magenta, copper-phthalocyanine as cyan, and arylide yellow. Scaling the peak of the absorption band to the number of molecules per unit area for the specific pigments studied in this article provides the molar extinction coefficients, 1.21 × 10⁴ , 4.7 × 10⁴ , and 3.3 × 10⁴ cm²/millimole respectively, regardless of the different ink formulations used, in accord with Avogadro's principle. Having a set of three pairs of K, S spectra is used to compute the color gamut of any CMY color combination in the L*a*b* space as a function of ink layer thickness and formulation. Using an iterative algorithm, a color-gamut-optimal set of CMY inks is obtained.     

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     

Color distribution of maxillary primary incisors in Korean children

The purpose of this study was to investigate the color distribution of maxillary primary incisors measured with a colorimeter. The subjects were 100 Korean children aged 2–5 with total number of 400 teeth. A spot measurement intraoral colorimeter was used to determine the color of maxillary primary central and lateral incisors at labial central area. The CIE L*, a*, b* value of each tooth and color difference (ΔE) among each other were calculated and analyzed. The range of L*, a*, and b* values, regardless of the type of teeth, was 72.7–84.9, ?0.6 to 4.9, and 4.7–15.0, respectively. Mean value (SD) of L*, a*, and b* for maxillary primary incisors was 78.6 (2.3), 1.2 (0.9), and 9.6 (1.8), respectively. Boys showed more red (higher a* value) and less yellow (lower b* value) hue than girls in the central incisors (P < 0.05). Mean color difference (ΔE) (SD) between two values which selected from overall 400 L*, a*, b* values measured (n = ₄₀₀C₂) was 3.9 (1.8) with 95% confidence interval range of 3.86–3.89, and most of them were found to be present around the previously reported clinical acceptability thresholds (ΔE = 2.7–6.8). Because mean intraperson ΔE (SD) was 3.0 (1.6) with 95% confidence interval range of 2.86–3.12, most colors among primary incisors in the same person were presumably difficult to discern by naked eye (ΔE < 3.7). Age influenced L* and b* values significantly, but the correlation coefficients were not high (r = ?0.182 for L* of central incisors, P < 0.01; r = 0.188 for b* of central incisors, P < 0.01; and r = 0.143 for b* of lateral incisors, P < 0.05). The present study showed somewhat higher color coordinates than the previous reports which based on primary anterior teeth in other ethnic groups. The results of this study could be used for the color modification of esthetic materials for primary teeth. © 2009 Wiley Periodicals, Inc., Col Res Appl, 2010.     

Prediction of optical efficacy of vital tooth bleaching using regression analysis

Establishing a colorimetric guideline to predict the effectiveness of tooth bleaching could produce a more reliable dental treatment. The purpose of this study was to evaluate the effectiveness of tooth bleaching and to test the predictability of tooth color changes. A 10% carbamide peroxide bleaching system was used in studies at Harvard University and at Iwate Medical University in Japan. L*, a*, and b* values (CIELAB) for pre‐ and postbleaching were obtained and color differences (ΔE) were calculated. The b* and L* values of the original tooth color indicated a relatively strong to moderate correlation with ΔE values, whereas a* showed a weak correlation. The multiple‐regression equation obtained from the color data of Harvard subjects performed better than the predictive model. The predicted ΔE correlated strongly with the observed ΔE (r = 0.78). The validation of this equation on data collected from Iwate confirmed the strong correlation (r = 0.74). © 2004 Wiley Periodicals, Inc. Col Res Appl, 29, 390–394, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20048     

Effect of reactive dyeing on the UV protection affected by knitted fabric made from different types of cotton fibre

In this study, 100% cotton knitted fabrics made from combed cotton and combed pima cotton were dyed with reactive dye, with different dye concentrations. Colour properties such as CIE L*a*b* values as well as dyeing uniformity of the dyed fabrics were measured. The relationships between colour properties and the ultraviolet protection afforded by cotton knitted fabrics were investigated. Experimental results revealed that dye concentration is the most important factor. In addition, only L* values have a direct mathematical relationship with the ultraviolet protection factor; a* and b* values and dyeing uniformity were not found to have a significant correlation with ultraviolet protection factor values. Meanwhile, knitted fabric made from combed cotton fibre has better ultraviolet protection performance than fabric made from combed pima cotton fibre.