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A color rendition chart, the preferred memory color (PMC) chart, has been produced. It comprises 30 colored patches, divided into three groups: preferred memory colors, reference color‐gamut colors, and a gray scale. The main purpose of the new chart is to enable users to produce satisfactory preferred color reproduction using digital cameras, displays, and printing systems. The methods used to develop the various colors, and the color specification of each color are presented. Finally, several potential applications of the chart for the characterization of imaging devices, for the evaluation of image color quality, and for the calculation of color rendering indices for lighting are suggested. [ABSTRACT FROM AUTHOR]

Measuring color matching differences between observers is an important means of investigating individual differences in human color vision. In this article, we introduce a new LED‐based visual trichromator with which we have estimated color matching functions and cone spectral sensitivities in a group of five normal observers. The trichromator has side‐by‐side semi‐circular matching fields that are illuminated by two spectrally tunable LED light sources, each comprised of 18 LEDs with center wavelengths ranging from 400 to 700 nm. We used Maxwell's method to derive a set color match. A fixed triplet of red‐green‐blue (RGB) primaries produced the white standard field of 120 cd/m2 in one field. The other field, the mixture field, was illuminated by one of 11 different triplets of lights with various center wavelengths. Observers adjusted the intensities of the triplets in the mixture field to match the white standard field. All matches were made for field diameters of 2° and 10° of visual angle to allow comparisons with colorimetric standards and were repeated five times. Calibrations and tests showed that the trichromator and the measurements were stable and repeatable. Grassmann's laws predict that at the 11 color matches the excitations in the three cone types should be the same. Consequently, we can use those matches and a model of how cone spectral sensitivities vary between individuals to estimate the three underlying corneal cone spectral sensitivities for each observer (and thus how they vary from the standard (or mean) observer). We find good agreement with the CIE 2006 standards, but our observers show small but consistent differences. [ABSTRACT FROM AUTHOR]

CIE has recommended two previous appearance models, CIECAM97s and CIECAM02. However, these models are unable to predict the appearance of a comprehensive range of colours. The purpose of this study is to describe a new, comprehensive colour appearance model, which can be used to predict the appearance of colours under various viewing conditions that include a range of stimulus sizes, levels of illumination that range from scotopic through to photopic, and related and unrelated stimuli. In addition, the model has a uniform colour space that provides a colour-difference formula in terms of colour appearance parameters. [ABSTRACT FROM AUTHOR]

This article addresses some general practices for the computation of CIE tristimulus values (TSVs), including different methods used for the interpolation, extrapolation, and truncation of data in the visible wavelength range. In each case, a quantitative analysis is presented on the basis of a dataset with 2365 spectral reflectances covering a wide color gamut, assuming six CIE illuminants and the two CIE standard colorimetric observers. For interpolation, it is found that among five tested methods, the (cubic) spline method is the best one when the spectral reflectance factors are uniformly sampled over the visible wavelength range. For extrapolation, it is found that the second-order extrapolation method gives better results than the use of nearest available data points or linear extrapolation methods. With respect to truncation, considering five different usual truncated ranges, it is found that the range from 360 to 780 nm provides more accurate results than the range from 380 to 780 nm currently recommended by CIE for nonfluorescent samples, and the use of the truncated range from 400 to 700 nm in place of the CIE-recommended range of 360 to 830 nm leads to TSVs with considerably high color differences of up to 0.9 CIELAB units. © 2016 Wiley Periodicals, Inc. Col Res Appl, 42, 10-18, 2017 [ABSTRACT FROM AUTHOR]

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 NC) were optimized, and Ncb 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 [ABSTRACT FROM AUTHOR]

A set of 10 color pairs was proposed and produced in 2002 to show the advantages of the CIEDE2000 color-difference formula with respect to CIELAB. These 10 color pairs illustrated each of the five corrections to CIELAB proposed by CIEDE2000. The 10 color pairs were visually assessed, under reference conditions close to those proposed by CIEDE2000, by two groups of 31 and 21 inexperienced observers, using two different gray scales. Average visual results in these experiments fitted CIEDE2000 predictions much better than CIELAB, as shown by a decrease of Standardized Residual Sum of Squares values of about 20 units. Current visual results showed only the improvement of CIEDE2000 upon CIELAB in predictions of perceived color differences, but they are not recommended for testing new advanced color-difference formulas. © 2012 Wiley Periodicals, Inc. Col Res Appl, 38, 429-436, 2013. [ABSTRACT FROM AUTHOR]

Small displays are widely used; they are small enough to be carried around and are often viewed under extreme surround conditions. Under bright illumination, mobile display users experience 'veiling glare' caused by bright ambient lighting. A refined version of CIECAM02 called 'Refined CIECAM02 and original CIECAM02' were tested to predict visual results in terms of lightness (J), colourfulness (M), and brightness (Q) on a 2-inch sized display (2″) mobile phone under four surround conditions; dark (0 cd/m2), dim (5 cd/m2), average (1000 cd/m2), and bright (10,000 cd/m2). Other than the two versions of CIECAM02 using the original data, a correction to the models' predicted lightness J and a black correction to the original data were developed. Overall, the refined CIECAM02 plus the J correction performed the best for predicting the lightness, brightness and colourfulness under all the viewing conditions, especially for bright surround condition. Furthermore, another experiment was carried out using complex images to verify different versions of CIECAM02. The images were reproduced using JMh (lightness, colourfulness, and hue) spaces from the modified CIECAM02 versions. The experiment was conducted by comparing original images viewed under dim, average, or bright surround conditions and the predicted images were viewed under dark surround condition on two identical mobile displays. The different versions of the CIECAM02 showed similar results to each other for dim and average surround conditions but large differences when predicting the images under bright surround condition. The refined CIECAM02 with the J′ formula performed the best amongst all four CIECAM02 versions. © 2011 Wiley Periodicals, Inc. Col Res Appl, 2013. [ABSTRACT FROM AUTHOR]