Estimating black‐level emissions of computer‐controlled displays

It is quite common for computer‐controlled displays to emit light in image areas set to digital values of zero, referred to as their black level. This is expected for liquid–crystal displays and also can occur for cathode‐ray tube displays when the “brightness” (gun‐amplifier offset) is set excessively high. For either display, the light emission at the black level results in color channels whose chromaticities vary with luminance level. Consequently, typical methods of colorimetric characterization result in large error. When this black‐level emission is measured and accounted for suitably, characterization accuracy is dramatically improved. Unfortunately, many instruments used to measure displays have too low a sensitivity to measure black‐level emission with sufficient precision and accuracy. A method of estimating black‐level emissions was derived and tested. Because the optimal black‐level results in channel chromaticities that are invariant to the greatest extent with luminance level, an objective function was defined as the sum of chromaticity variances of each channel over a range of measurements. Minimizing this objective function resulted is an estimate of a display's black level. The estimated black level resulted in equivalent or superior performance to direct measurements. © 2003 Wiley Periodicals, Inc. Col Res Appl, 28, 379–383, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.10181     

CRT colorimetry. part I: Theory and practice

The relationship was derived for computer-controlled color CRT displays between spectral radiant exitance emitted and digital counts. The derivation was historical and could be traced to pioneering work in photographic sensitometry, vacuum tube physics, and broadcast television. By performing radiometric measurements relative to a display's maximum exitance, the model simplified to a two-stage model. The first stage was a nonlinear transformation relating normalized digital-to-analog converter values to device-dependent monitor tristimulus values using model parameters of gain, offset, and γ. The second stage was a linear transformation where the device-dependent monitor tristimulus values were transformed to device-independent CIE tristimulus values. By using the model, colorimetric characterization accuracy of better than 0.5 CIELAB color-difference units for 125 colors sampling the display color gamut was achieved by measuring the CIE tristimulus values of only eight colors. The model had equivalent performance to methods using extensive measurements and table lookup. © 1993 John Wiley & Sons, Inc.     

CRT colorimetry. Part II: Metrology

The colorimetric characterization of computer-controlled CRT displays require radiometric measurements with high precision and accuracy in order to achieve acceptable colorimetric accuracy in defining stimuli generated with this type of imaging modality. Precision and accuracy requirements for photometers, colorimeters, and spectroradiometers were evaluated. When models are used to relate digital counts defining a stimulus and resulting spectral radiant exitance, displays are assumed to exhibit channel and spatial independence. A variety of tests and the results of evaluating four imaging systems are described. From these analyses, measurement accuracy is mainly limited by wavelength scale in the case of spectro-radiometers and filter fit in the case of colorimeters. Measurement precision is limited by the number of significant figures for fixed-range devices and signal-to-noise limitations for low-luminance stimuli. Display accuracy is limited by a lack of channel and spatial independence. Display precision is mainly limited by the electronic design of the display and the stability and load independence of the gun amplifiers. © 1993 John Wiley & Sons, Inc.     

Two‐primary crosstalk model for characterizing liquid crystal displays

The conventional methods for colorimetric characterization of displays assume that the displays satisfy the constraints of primary chromaticity invariance across gray levels and primary channel independence. The liquid crystal displays (LCDs) that reasonably satisfy the two constraints have been accurately characterized with the conventional methods and black‐level correction. For the LCDs that do not reasonably satisfy the two constraints, we propose a higher‐order method for accurate colorimetric characterization. Two‐primary crosstalk (TPC) is observed for two tested LCDs that may be due to signal interference. We derive the crosstalk function and develop the TPC model for characterizing the LCDs, which comprises a set of the simultaneous equations with offset constants, one‐color variables, and two‐color‐product variables. The results show that the accuracy of the TPC model is significantly improved compared with conventional device models and only slightly worse than the three‐dimensional look‐up‐table (3D‐LUT) model, while the numbers of measurement data are 49 and 512 for the TPC and 3D‐LUT models, respectively. The average color difference of 224 test samples is about 2.0 (1976 CIELAB color difference formula) with the TPC model for the LCD monitor either with higher or with lower two‐primary crosstalk. While the proposed TPC model yields improved characterization accuracy over conventional models, the TPC model is evaluated on only two LCDs of the same manufacturer. Thus, the generality of the LCD crosstalk deficiency is unknown and should be determined in future research. © 2006 Wiley Periodicals, Inc. Col Res Appl, 31, 90–101, 2006; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20187     

The PLVC display color characterization model revisited

This work proposes a study of the Piecewise Linear assuming Variation in Chromaticity (PLVC) display color characterization model. This model has not been widely used as the improved accuracy compared with the more common PLCC (Piecewise Linear assuming Chromaticity Constancy) model is not significant for CRT (Cathode Ray Tube) display technology, and it requires more computing power than this model. With today's computers, computational complexity is less of a problem, and today's display technologies show a different colorimetric behavior than CRTs. The main contribution of this work is to generalize the PLVC model to multiprimary displays and to provide extensive experimental results and analysis for today's display technologies. We confirm and extend the results found in the literature and compare this model with classical PLCC and Gain‐Offset‐Gamma‐Offset models. We show that using this model is highly beneficial for Liquid Crystal Displays, reducing the average error about a third for the two tested LCD projectors compared with a black corrected PLCC model, from 3.93 and 1.78 to respectively 1.41 and 0.54 ΔE units. © 2008 Wiley Periodicals, Inc. Col Res Appl, 33, 449–460, 2008     

Printed thermochromic displays

Thermochromic displays, which were evaluated in this study, combine printed electronics with the thermochromism phenomenon. Conductive lines printed on the reverse side and thermochromic printing ink printed on the front side of cardboard packaging form a thermochromic display that gives cardboard packaging additional value. Displays were printed on different printing materials, and thermochromic printing ink was deposited in one and two layers. In addition, half of the samples were varnished. The influence of the printing material, the thickness of the thermochromic printing ink layer, the varnish, the high temperature, and light fastness on the display's operability were all evaluated. It was clearly shown that the choice of printing material plays a crucial role in the display's operability. Moreover, high temperature and light fastness also have a significant influence, although the impact is negligible when the display is used at room temperature.     

The properties of multiple CMF determinations using alternative primary sets part I: Evidence and modeling

This article concerns William Thornton's single‐observer colour matching functions (CMFs). Alternative “prime colour” (or PC), “non‐prime” (or NP), and “anti‐prime” (or AP) wavelengths were used, and the measurements appear to challenge the basis on which conventional colorimetry predicts metameric colour matches. An analysis of Thornton's visual match data for alternative‐primary CMFs is presented. Using conventional colorimetric calculations, Thornton's articles establish failures of linear transformability between experimental data sets, failures of tristimulus sum prediction, and differences in CIE chromaticity for a set of strongly metameric stimuli that all match the same neutral reference stimulus. Error analysis using an optimization model is first used to confirm that Thornton's data represent a significant challenge to the standard colorimetric model. Thornton's assertion is supported that spectral power appears to be visually subadditive at NP and AP wavelengths compared with spectral power at the PC wavelengths. It is next shown that each of the individual failures of prediction can be eliminated by relatively minor adjustments to the relevant CMFs. However, each instance of failure required a different adjustment. Multiple and significantly incompatible linear adjustments of the CMFs are apparently needed to explain Thornton's results. The implication is that the visually additive value of the spectral stimuli used in the matches varies not only with wavelength but also as a nonlinear function of stimulus power. The implied variations in visual additivity become significant only at certain wavelengths. Thus a small and specific subset of strongly metameric light‐source matches, such as those chosen by Thornton, are required to reveal significant variations. Such spectrally localized variations have a minimal overall effect in the tristimulus sum predictions for surface‐colour matches using broadband stimuli. A detailed analysis of the central assumptions concerning additive colour mixing is given. It suggests that any super and subadditive visual effects revealed by Thornton's measurements can be accommodated within the standard colorimetric model by extending the model rather than by modifying the CMFs. An extension is proposed in which any possible super‐ or subadditive phenomena are modeled by a redefinition of the units of visual additivity, using a spectral‐level precursor transform. Its intent is to equate the additive properties of all possible incident stimuli numerically, prior to manipulation using the Standard Model. An appropriate methodology is also described for confirming measuring and classifying any spectrally distinct super and subadditive effects. Under The Heading for Prediction Failures the methods described are applied to Thornton's data. They reveal consistent evidence of additivity differences that are both wavelength and stimulus power dependent. © 2004 Wiley Periodicals, Inc. Col Res Appl, 29, 273–284, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20022     

Improving color reproduction accuracy of an OLED‐based mobile display

For improving color reproduction accuracy of mobile displays, we recently developed a generic model for device‐specific display characterization model that also accounts for the influence of illuminance from ambient light. In the present article, this MDCIM model (Mobile Display Characterization and Illumination Model) is applied to a Samsung Galaxy S4 display, representing OLED displays. The performance of the model was tested by determining the values of all model parameters using publicly available technical data only. We organized visual tests under various ambient illuminance levels from 600 to 3000 lux. Seven observers compared the color of displayed images with the color of physical samples. With the MDCIM method, the quality of the color match was shown to improve considerably as compared to using only device‐independent encoding color space. On a five‐point scale to quantify color reproduction accuracy, the MDCIM resulted in more than 1 unit improvement at 1000 lux illuminance. At lower and higher illuminance, the improvement was even larger. Color reproduction accuracy was found to be at least reasonable, according to the subjective assessment of visual observers, for more than 75% of the samples when using the MDCIM method, but only 20% or less when using the common device‐independent encoding color space.     

Calibration of a computer controlled color monitor

Because of the large number of stimulus configurations that may be displayed on a computer controlled color monitor, direct measurement of the relation between the digital input values to the frame buffer and the output of the monitor is not possible. To calibrate a monitor, it is necessary to make assumptions about the monitor's performance. These assumptions allow the monitor's output for any set of input values to be predicted from the input values and the results of a feasible number of calibration measurements. This article describes a set of assumptions that are sufficient to render the problem of monitor calibration tractable. These are the assumptions of phosphor constancy, phosphor independence, spatial independence, and the single scale factor assumption. If these assumptions hold, a monitor may be calibrated by measurements of the phosphor spectral power distributions, measurements of the phosphor input-output relations, and measurements of the spatial scale factor at a number of locations. Violations of these assumptions limit the accuracy of calibration. The results of measurements that test the validity of these assumptions for a Barco 5351 monitor are presented.     

A multi-primary empirical model based on a quantum dots display technology

In this work, we built a multi-primary display model based on the new quantum dots (QD) technology to enlarge the display color gamut. In this way, first the emission spectral radiance curves of the three RGB channels of a commercial QD display were fitted to a four-parameter function. From this modeling, it is possible to gain new theoretical color primaries by selecting new spectral peaks (cyan, yellow, magenta, and/or additional RGB primaries) and imposing some colorimetric conditions for the resulting white of this proposed theoretical multi-primary display. Proper characterization to assess the performance of the display was conducted to know if the basic “gain-offset-gamma” (GOG) model can be used for direct and inverse color reproduction (from RGB to CIE-XYZ, and vice versa). The GOG model was found to well characterize this display. The spatial uniformity of the display was also evaluated in luminance and color chromaticity terms. Finally, with the primaries modeling and color characterization based on the GOG model, a 5-primary model (RGBYC) was tested. The evaluation of this theoretical RGBYC display model confirms the gamut enlargement, which can also improve goniochromatic color reproduction.     

A comparative study of a CRT colorimetric prediction model by neural networks and the models by conventional method

In order to produce desired colors on CRT screens, much work has been done on the problem of the CRT colorimetric prediction. However, it would take great pains to overcome the troubles such as the constant channel chromaticity, the gun or channel independence, and the screen background effect, etc., with the conventional prediction methods such as PLCC and PLVC models, etc. To solve such problems, we propose a completely different CRT colorimetric prediction model by using a set of Artificial Neural Networks (ANN), where a set of back‐propagation (BP) neural networks is used to perform a nonlinear conversion between RGB values and XYZ values. By comparing some typical conventional CRT colorimetric prediction models with our neural‐networks‐based model theoretically, the article indicates that our new model can overcome the troubles faced by the conventional models, and by experiment the article shows that our new model can yield a satisfactory prediction result. © 1999 John Wiley & Sons, Inc. Col Res Appl, 24, 45–51, 1999     

Variations in the colorimetric characteristics of verdigris pictorial films depending on the process used to produce the pigment and the type of binding agent used in applying it

The term verdigris embraces a wide range of synthetic pigments whose compositions can also vary. All are salts of copper, but their chemical composition will vary depending on the ingredients used to synthesize them and the conditions in which that synthesis is performed. This article presents the results of applying some of the recipes contained in treatises; the recipes used here, specifically, were taken from the Mappae Clavicula (12th century) and the Ms. of Pierre Lebrun (17th century). The ingredients mentioned present some variations, so that the pigments prepared in turn exhibit significant differences in terms of chemical composition and colorimetric characteristics. The recipes from the Mappae Clavicula, for example, produced monohydrated copper(II) acetate, which upon binding with gum arabic created bluish‐green pictorial films, whereas the colour was yellowish green when the binder was linseed oil. The pigment made from Pierre Lebrun's recipe was a copper(II) chloride mixed with an organo‐copper complex, which can be bound with gum arabic to produce a yellowish‐green colour, whereas mixing with linseed oil presented certain difficulties. These results are derived from colorimetric measurements, which were used to produce values of lightness (L), chroma (C) and hue (H), and also percent reflectance spectra. © 2007 Wiley Periodicals, Inc. Col Res Appl, 32, 414–423, 2007     

Estimation of optoelectronic conversion functions of imaging devices without using gray samples

In the colorimetric or spectral characterization of imaging devices such as digital cameras and scanners, the optoelectronic conversion functions (OECFs) are traditionally obtained from standard gray samples. However, these gray samples are sometimes unavailable when conducting color characterization. We propose an efficient method for recovering OECFs by using nongray samples, based on the finite‐dimensional modeling of spectral reflectance and the second‐order polynomial fitting of OECFs. Experimental results indicate that the accuracy of the estimated OECFs are close to those obtained from gray samples, with the correlation coefficients R² larger than 0.995. The proposed method should be useful in colorimetric and spectral characterization of imaging devices by using custom‐made color samples in textile or other industries, when standard gray samples are not available and not easily made. © 2008 Wiley Periodicals, Inc. Col Res Appl, 33, 135–141, 2008     

Color measurements for pearlescent coatings

This article describes recent developments at the National Institution of Standards and Technology in the colorimetric characterization of pearlescent coatings. The goal of this research is to develop a measurement protocol for the accurate color characterization of these coatings using an understanding of their scattering mechanism as a guide. A large ensemble of bi‐directional reflectance measurements on a series of pearl interference pigmented coatings show general trends in the color variations with illumination and viewing angles. These measurements were used to define a set of geometries (illumination angles of 15°, 45°, and 65° and aspecular angles of 15°, 35°, 45°, 70°, and 85°) to characterize the angle dependent color travel observed in these coatings. © 2003 Wiley Periodicals, Inc. Col Res Appl, 29, 38–42, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.10210     

Camera characterization for improving color archaeological documentation

Determining the correct color is essential for proper cultural heritage documentation and cataloging. However, the methodology used in most cases limits the results since it is based either on perceptual procedures or on the application of color profiles in digital processing software. The objective of this study is to establish a rigorous procedure, from the colorimetric point of view, for the characterization of cameras, following different polynomial models. Once the camera is characterized, users obtain output images in the sRGB space that is independent of the sensor of the camera. In this article we report on pyColorimetry software that was developed and tested taking into account the recommendations of the Commission Internationale de l'Éclairage (CIE). This software allows users to control the entire digital image processing and the colorimetric data workflow, including the rigorous processing of raw data. We applied the methodology on a picture targeting Levantine rock art motifs in Remigia Cave (Spain) that is considered part of a UNESCO World Heritage Site. Three polynomial models were tested for the transformation between color spaces. The outcomes obtained were satisfactory and promising, especially with RAW files. The best results were obtained with a second‐order polynomial model, achieving residuals below three CIELAB units. We highlight several factors that must be taken into account, such as the geometry of the shot and the light conditions, which are determining factors for the correct characterization of a digital camera.     

Evaluating the 1931 CIE color‐matching functions

The use of colorimetry within industry has grown extensively in the last few decades. Central to many of today's instruments is the CIE system, established in 1931. Many have questioned the validity of the assumptions made by Wright¹ and Guild,² some suggesting that the 1931 color‐matching functions are not the best representation of the human visual system's cone responses. A computational analysis was performed using metameric data to evaluate the CIE 1931 color‐matching functions as compared to with other responsivity functions. The underlying assumption was that an optimal set of responsivity functions would yield minimal color‐difference error between pairs of visually matched metamers. The difference of average color differences found in the six chosen sets of responsivity functions was small. The CIE 1931 2° color‐matching functions on average yielded the largest color difference, 4.56 ΔE. The best performance came from the CIE 1964 10° color‐matching functions, which yielded an average color difference of 4.02 ΔE. An optimization was then performed to derive a new set of color‐matching functions that were visually matched using metameric pairs of spectral data. If all pairs were to be optimized to globally minimize the average color difference, it is expected that this would produce an optimal set of responsivity functions. The optimum solution was to use a weighted combination of each set of responsivity functions. The optimized set, called the Shaw and Fairchild responsivity functions, was able to reduce the average color difference to 3.92 ΔE. In the final part of this study a computer‐based simulation of the color differences between the sets of responsivity functions was built. This simulation allowed a user to load a spectral radiance or a spectral reflectance data file and display the tristimulus match predicted by each of the seven sets of responsivity functions. © 2002 Wiley Periodicals, Inc. Col Res Appl, 27, 316–329, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.10077     

Optimal display color for nighttime smartphone users

The study investigated the optimal display color for comfortable use of smartphones at night under low illuminance, while not distorting the perceived quality of displays. Two phases of psychophysical experiments were conducted to judge perceptibility and acceptability of the displays in various shades of white. The experimental results showed that the scores in acceptability were always higher than those in perceptibility all across the hues, and yellow received the highest scores in acceptability among the six hue categories. This can be interpreted that the observers have the intention of using a display in a yellow shade of white even though it is not perceived as pure white. Through the analysis, a white in yellow shade with the RGB values of 255, 255, and 230 was determined as the optimal display color for nighttime smartphone users regardless of display luminance or contents. The proposed display color supports physiological comfort by reducing the blue light, which involves an adverse effect on the biological system, and provides psychological satisfaction by allowing users to decide the color within the range of the user's acceptable threshold. © 2016 Wiley Periodicals, Inc. Col Res Appl, 42, 60–67, 2017     

Color heterogeneity in visual search

Distractor color heterogeneity refers to a condition in which a target is presented among distractors of different chromaticities. In the present study, the amount distractor color heterogeneity was varied systematically to determine how efficiently the visual system processes displays composed of search elements of multiple colors. Distractor color heterogeneity was expressed by selecting distractor chromaticities from sectors of various angles in a cone‐based normalized color space. The generalizability of the measurements was tested using two different visual search paradigms. An accuracy search task was used in which the search displays were presented as brief flashes and the dependent variable was search accuracy. A latency search task was used in which the display presentation time was under the participant's control and the dependent variable was reaction time. Compared to a homogeneous condition with distractors of a single color, distractor color heterogeneity had a deleterious effect on search performance in both paradigms. In normalized units, the measurements were similar across participants, target chromaticities, and tasks, but the same measurements expressed in non‐normalized units showed clear and systematic individual differences. © 2010 Wiley Periodicals, Inc. Col Res Appl, 2011     

Refined CIECAM02 for bright surround conditions

Displays such as mobile phones are viewed under surround conditions that vary from dark night to bright sunlight. The overall goal of this study is to test the appropriateness of CIECAM02 for mobile displays, and modify it according to any insufficiency found. Firstly, the testing of CIECAM02 is described using the visual data from 2‐inch display of three achromatic backgrounds (gray, black, and white), and three surround conditions (dark, dim, and average). Secondly, CIECAM02 was tested under four surround conditions (dark, dim, average, and bright), and three displays (2‐, 4‐, and 7‐inch), with only the gray background used, to focus more on the surround conditions. Those twelve experimental phases were used to refine CIECAM02, considering the surround factors. The surround parameters (c, F, and N_C) were optimized, and N_cb was modified from the CIECAM02; the modified model is named MobileCAM‐v1. Colourfulness prediction by MobileCAM‐v1 has been improved, especially for a black background under average surround condition. A further refined version of CIECAM02, MobileCAM‐v2, was developed, for mobile displays viewed under different surround conditions. A set of equations based on surrounding conditions was first derived, to be able to accurately define surround parameters. The MobileCAM‐v2 model gave the largest improvement in brightness, followed by lightness, and with colourfulness the smallest. The improvement is significant for bright surround conditions, improving the performance of CIECAM02 in predicting the visual results. © 2014 Wiley Periodicals, Inc. Col Res Appl, 40, 114–124, 2015     

Calibrated color mapping between LCD and CRT displays: A case study

The primary goal of a color characterization model is to establish a mapping from digital input values d_i (i = R,G,B) to tristimulus values such as XYZ. A good characterization model should be fast, use a small amount of data, and allow for backward mapping from tristimulus to d_i. The characterization models considered here are for the case of an end user who has no direct knowledge of the internal properties of the display device or its device driver. Three characterization models tested on seven different display devices are presented. The characterization models implemented in this study are a 3D look up table (LUT) (Raja Balasubramanian, Reducing the Cost of Lookup Table Based Color Transformations, Proc IS&T/SID 7th Color Imaging Conference 1 ), a linear model (Fairchild MD, Wyble DR. Colorimetric Characterization of the Apple Studio Display (Flat Panel LCD). Munsell Color Science Laboratory Technical Report, 1998), and the masking model (Tamura N, Tsumura N, Miyake. Masking Model for accurate colorimetric characterization of LCD. Proc IS&T/SID 10th Color Imaging Conference 3 ). The devices include two CRT monitors, three LCD monitors, and two LCD projectors. The results of this study indicate that a simple linear model is the most effective and efficient for all devices used in the study. A simple extension to the linear model is presented, and it is demonstrated that this extension improves white prediction without causing significant errors for other colors. © 2005 Wiley Periodicals, Inc. Col Res Appl, 30, 438–447, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.