Color appearance and color connotation models for unrelated colors

The purpose of this research is to investigate the color appearance and color connotation of unrelated colors. To investigate color appearance (i.e., brightness, colorfulness, and hue) for unrelated colors, 22 observers have answered their color appearance for 50 unrelated color stimuli using the magnitude estimation method. Perceptual data obtained by the experiment is compared with the color attributes data estimated by unrelated‐color appearance models, CAM97u and CAM02u. It is found that both models perform reasonably well but the performance of CAM02u is better than that of CAM97u. For investigating color connotation for unrelated colors, 32 observers have judged their color connotation for the 50 unrelated color stimuli using the 10 color connotation scales (i.e., “Warm – Cool,” “Heavy – Light,” “Modern – Classical,” “Clean – Dirty,” “Active – Passive,” “Hard – Soft,” Tense – Relaxed,” “Fresh – Stale,” “Masculine – feminine,” and “like – Dislike”), and semantic differential method is used for measurement. It is found that the color connotation models developed for related colors perform poorly for unrelated colors. Experimental results indicate that brightness attribute is confusing to estimate and does not affect color connotation significantly for unrelated colors. Based on the psychophysical data, new models for “Warm‐Cool”, “Heavy‐Light”, “Active‐Passive” and “Hard‐Soft” were proposed using CAM02u hue, brightness, and colorfulness. Color connotations for unrelated colors are classified into three categories, which “Color solidity,” “Color heat,” and “Color purity.” © 2013 Wiley Periodicals, Inc. Col Res Appl, 40, 40–49, 2015     

Chromatic adaptation by illuminant matrix products: An alternative to sharpened von kries primaries

Previous attempts to predict chromatic‐adaptation correspondence have led to a sharpening dilemma—i.e., Von Kries primaries are chosen that do not include in the positive octant all the realizable (x,y) chromaticities. This leads to paradoxical adaptation predictions for the colors that have negative Von Kries coordinates. A solution is proposed here that expresses the asymmetric‐matching relation of chromatic adaptation as the product of two matrix transformations, given source illuminant 1 and destination illuminant 2: from source tristimulus values via adaptation matrix 1 to the adapted state coordinates, and from the adapted state via the inverse of adaptation matrix 2 to the destination illuminant tristimulus values. To avoid the sharpening instability, the entire spectrum locus must lie within the positive octant of the adapted state tristimulus space. © 2013 Wiley Periodicals, Inc. Col Res Appl, 39, 275–278, 2014; Published Online 14 March 2013 in Wiley Online Library ( wileyonlinelibrary.com ). DOI 10.1002/col.21799     

A new method to evaluate a corresponding colors dataset based on its two derived transforms

Corresponding colors datasets are crucial in the study of chromatic adaptation transformations (CATs). A transform can be derived from a corresponding colors dataset. In this article, a second transform is derived by exchanging the two groups of tristimulus values of a dataset. Based on the two transforms a new method is proposed to evaluate a corresponding colors dataset. The evaluation criteria include the prediction difference between the two transforms and their prediction errors with visual results altogether. By the new method, nine superior datasets and four inferior datasets were picked from the 25 solo existing datasets. The research also included mixing different solo datasets and investigated their effectiveness. The results show that mixed datasets comprised of datasets with same illuminants and media have a certain value to derive CATs. Finally, 10 superior transforms derived in the experiment were compared with the four CATs recommended by the CIE. The results indicate that three of four CATs recommended by the CIE are superior to any sharpening transform derived in this experiment, but CIECAT94 is inferior to any one of them conversely. © 2016 Wiley Periodicals, Inc. Col Res Appl, 42, 150–155, 2017     

Color constancy from invariant wavelength ratios. III: Chromatic adaptation theory,model and tests

A theory of chromatic adaptation is derived from Parts I and II, and presented in terms of relative wavelength, purity, and radiant power, leading directly to a predictive model of corresponding hue, chroma, and lightness. Considering that even simple animals have effective color vision and color constancy, the aim was to develop a simple model of complete adaptation. The model is tested against well‐known data sets for corresponding colors in illuminants D65, D50, and A, and for small and large visual fields, and performs comparably to CIECAM02. Constant hue is predicted from Part I's mechanism of color constancy from invariant wavelength ratios, where constant hues shift wavelength linearly with reciprocal illuminant color temperature. Constant chroma is predicted from constant colorimetric purity. Constant lightness is predicted from chromatic adaptation of spectral sensitivity represented by power ratios of complementary colors (rather than cone responses which lack spectral sharpening). This model is the first of its type and is not formatted for ease of computation. © 2010 Wiley Periodicals, Inc. Col Res Appl, 2010     

Comprehensive color solutions: CAM16, CAT16, and CAM16‐UCS

The CIECAM02 color‐appearance model enjoys popularity in scientific research and industrial applications since it was recommended by the CIE in 2002. However, it has been found that computational failures can occur in certain cases such as during the image processing of cross‐media color reproduction applications. Some proposals have been developed to repair the CIECAM02 model. However, all the proposals developed have the same structure as the original CIECAM02 model and solve the problems concerned at the expense of losing accuracy of predicted visual data compared with the original model. In this article, the structure of the CIECAM02 model is changed and the color and luminance adaptations to the illuminant are completed in the same space rather than in two different spaces, as in the original CIECAM02 model. It has been found that the new model (named CAM16) not only overcomes the previous problems, but also the performance in predicting the visual results is as good as if not better than that of the original CIECAM02 model. Furthermore the new CAM16 model is simpler than the original CIECAM02 model. In addition, if considering only chromatic adaptation, a new transformation, CAT16, is proposed to replace the previous CAT02 transformation. Finally, the new CAM16‐UCS uniform color space is proposed to replace the previous CAM02‐UCS space. A new complete solution for color‐appearance prediction and color‐difference evaluation can now be offered.     

Statistical methods for analyzing color difference distributions

Multivalued measurands, such as spectral reflectance and tristimulus values, are usually analyzed by reducing the data to a single‐valued parameter, such as color difference. The variations in sets of color differences are nonnormal distributed. This article compares five statistical methods to determine the 95% tolerance limit on nine data sets of color differences. Published 2010 Wiley Periodicals, Inc. Col Res Appl, 36, 160–168, 2011;     

Investigating color appearance in optical see‐through augmented reality

Color appearance for real objects has been studied over decades and it has been well modeled. However, in augmented reality (AR) environments, virtual content is added to a real background and a mixed appearance is perceived. In this research, we studied color appearance in AR and investigated the applicability of the CAM16 color appearance model, one of the most comprehensive current color appearance models, in an AR environment. Using a benchtop optical mixing apparatus as an AR simulator, objective measurements of mixed colors in AR were performed. Then a psychophysical color matching experiment was performed with combinations of mixed foreground and background colors. The results showed that CAM16 is not accurate in predicting the color appearance in AR environment; therefore, it was modified with the addition of chromatic simultaneous contrast, resulting in an improved fit to the AR experiment data. A second psychophysical color matching experiment was performed on a single display to compare the color perception in AR with color perception in real world from a single display.     

Investigation on effects of adapting chromaticities and luminance on color appearance on computer displays using memory colors

CAT02, the most widely used chromatic adaptation transform to characterize the chromatic adaptation mechanism in the human visual system, includes a factor D to characterize the degree of chromatic adaptation. This factor, however, is only determined by the luminance level of the adapting field and surround. This study was designed to investigate how the change of adapting chromaticities and the simultaneous changes of adapting chromaticities and luminance affect the degree of chromatic adaptation and color appearance on computer displays. The human observers adjusted the color appearance of various familiar objects and cubes on different display backgrounds. A higher degree of chromatic adaptation was found when using familiar objects, which was likely due to the cognitive mechanism. Both the adapting chromaticities and luminance significantly affected the degree of chromatic adaptation, with a lower degree under an adapting condition with a lower adapting correlated color temperature and a lower adapting luminance. In addition, the effect of adapting luminance on colorfulness (known as the Hunt Effect) was likely to be overpredicted in CAM02-UCS, which merits further investigations.     

Visual color matching under various viewing conditions

In this article, we provide colorimetry data for which it was judged that the colors between different media matched under various viewing conditions. Painted color patches, a monitor, and printed color patches were used in the color matching experiments, in which we compared the appearances of the painted color patch and the monitor, or the monitor and the printed color patch, using the method of constant stimuli. The nine types of viewing conditions we used could be envisaged to occur when comparing different device outputs indoors. The experimental data obtained were compared with corresponding colors predicted with the use of five types of color appearance model, including color appearance formulae. We found that when the viewing conditions were the same for the different media, there was good agreement between the experimental data and the CIECAT94 model. And by adjusting the brightness induction and the chromatic induction factors, it was possible to improve conformity for the lightness and the chromaticity. Moreover, it was possible to improve the white point shift, which cannot be adjusted with the use of optimized parameters by introducing incomplete adaptation. By optimizing the parameters and introducing incomplete adaptation, it is possible to make the mean color difference ΔE between the corresponding color and the color matching point less than 10 CIELAB units for all of the viewing conditions.     

Grassmann's laws and individual color‐matching functions for non‐spectral primaries evaluated by maximum saturation technique in foveal vision

Over time, much work has been carried out to ascertain the validity of Grassmann's laws, Abney's law, CIE standard color‐matching functions and, up to now, no definitive answer has been given. Some of the phenomena subject of this debate are considered. An apparatus for color matching in 1.8° visual field has been realized with two sets of primary lights with broad spectral bands. This kind of primaries is the great difference with respect to other laboratories because it allows an indirect check of the Grassmann additivity law on the basis of the spectra and individual color‐matching functions by evaluating: (1) the tristimulus values of the primary lights; (2) the transformation matrices between the two reference frames defined by the two primary sets; and (3) the tristimulus values associated to all the pairs of matching lights in the bipartite field produced in the evaluation of the two sets of color‐matching function. The discrepancies of the data resulting in the check (1) and (2) are all compatible with the range defined by the uncertainty propagation of the individual color‐matching functions. In the check (3) fifteen tristimulus values over 18 have a discrepancy lower than one standard uncertainty. Grassmann's proportionality law is checked directly by reducing the matching lights with a neutral filter and holds true. © 2008 Wiley Periodicals, Inc. Col Res Appl, 33, 271–281, 2008.     

Introducing Wpt (Waypoint): A color equivalency representation for defining a material adjustment transform

The basis of this research is the manipulation of sensor excitation values to account for differences in observer or illuminant when spectral data are unknown. This touches on several related topics: color constancy, chromatic adaptation, and white balancing. The central premise is that these concepts make use of some form of intermediate color equivalency representation or waypoint system that makes comparison and color transformations possible. Differences between these concepts are related to the kind of color equivalency representation system used and how transformations are made into and out of it. A new sensor excitation normalization method was derived that has been optimized to predict changes in material color as Wpt (pronounced Waypoint) coordinates, which can be used to form a material adjustment transform. The prediction of such changes is also known as least dissimilar color matching. This is contrasted with a chromatic adaptation transform, which is optimized to predict corresponding color changes. As such a distinction is made between adaptation (which is based on corresponding color) and adjustment (which is based on other criteria). © 2014 Wiley Periodicals, Inc. Col Res Appl, 40, 535–549, 2015     

Numerical methods for smoothest reflectance reconstruction

Three numerical methods are presented for finding the smoothest reflectance curve associated with a given triplet of tristimulus values. The methods differ in how “smooth” is defined, and also differ in the domain of colors over which they are applicable. The first method is very quick and applies to any tristimulus values, but sometimes can yield reflectance curves with portions that fall outside the range 0 to 1. The second method applies to colors within the spectral locus (real colors) and guarantees that the reflectances produced are positive. The third method applies to colors within the object color solid (object colors) and guarantees that the reflectances fall within the range 0 to 1. The methods are shown to create reflectances that closely resemble those of real colors (natural and synthetic). Focus is given to implementing the numerical methods in very short MATLAB/Octave functions and to understanding the numerical behavior of the methods near the limits of their respective domains of applicability in terms of matrix conditioning and discretization artifacts.     

Digital image‐color conversion between different illuminants by color‐constancy actuation in a color‐vision model based on the OSA‐UCS system

In digital image capture, the camera signals produced by the D65 illuminant, once translated into tristimulus values of the CIE 1931 standard colorimetric observer (assuming the Maxwell‐Ives‐Luther criterion is satisfied), are considered good to produce accurate color rendering. An image obtained under any illuminant other than D65 does not appear realistic and the tristimulus values of the camera must be transformed into the corresponding ones produced by the D65 illuminant. This transformation must satisfy color constancy. In this work, the transformation is obtained by a color‐vision model based on the Optical Society of America‐Uniform Color Scales system [Color Res Appl 2005; 30: 31–41] and is represented by a matrix dependent on the adaptation illuminant. This matrix is obtained by minimizing the distance between the pairs of the uniform scale chromatic responses related to the tristimulus values of the 99 different color samples of the SG Gretag‐Macbeth ColorChecker measured under a pair of different illuminants, one of which is the D65. Then any picture captured under a given light source can be translated into the picture of the same scene under the D65 illuminant. Metameric reason allows only approximate solutions. The transformations from Daylight and Planckian illuminants to the D65 illuminant have a very regular dependence on the color temperature, that appears to be the typical parameter for the color conversion. © 2012 Wiley Periodicals, Inc. Col Res Appl, 38, 412–422, 2013     

Theoretical analysis of subtractive color mixture characteristics IV—Theorems on ideal color and tristimulus dimension

Giving a continuation to our work to understand the characteristics of the tristimulus values in colors obtained by subtractive color mixture, we extend several theorems provided in our previous articles. Previously, we started proving theorems for a single dimension, considering only individual tristimulus values. In the present article, the one‐dimensional discussion is extended to the three‐dimensional discussions of the tristimulus space. These theorems establish the absolute lower and upper bounds for tristimulus values of subtractive color mixtures of the ideal color. The results contribute toward a comprehensive modeling of subtractive color mixture. © 2005 Wiley Periodicals, Inc. Col Res Appl, 30, 427–437, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.     

Databases for spectral color science

In color science, spectral representation and analysis of colors have become a common approach to study color‐related problems, e.g., accurate industrial color measurement or analysis of color images. In developing algorithms for spectral color science, one often relies on existing databases of reflectance color spectra. Since a number of these databases are easily available, the same databases are commonly used by different research groups. During year 2003 the most popular one of our publicly available spectral reflectance databases was visited over 600 times. In the present article, we describe these color spectra databases and analyze their utility for spectral color science. However, the article does not take the complexity of fluorescent surfaces into account. The aim of this article is to set a solid ground for the comparisons of different methods in the spectral color science. The databases presented here include measured color spectra of natural and man‐made objects as well as spectra of some sets of standard colors. In addition to the commonly used data sets, some new data sets, including a set of standard calibrated colors and a set of natural colors, measured with 10 nm spectral resolution are introduced. © 2006 Wiley Periodicals, Inc. Col Res Appl, 31, 381–390, 2006; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20244     

Comparing two‐step and one‐step chromatic adaptation transforms using the CAT16 model

Color‐appearance models, CIECAM02 and CAM16, usually include two one‐step chromatic adaptation transforms: a forward (one‐step) transform to convert data from a first illuminant to CIE illuminant E, plus a reverse (one‐step) transform to convert the results from CIE illuminant E to a second illuminant. In practice, however, one‐step chromatic adaptation models, that avoid the use of the intermediate CIE illuminant E, are also employed. Tests using the one‐step CAT16 model indicate failures of both the symmetry and transitivity properties, except in the case where the degree of adaptation D is equal to unity. The magnitude of these failures depends on the specific illuminants selected, and increases as the degree of adaptation decreases. From four possible two‐step CAT16 models, we have identified two that obey the symmetry and transitivity properties, one with slightly better predictions of the experimental corresponding‐color datasets available in the literature, and more consistent with the one‐step CAT16 model. The findings of this article confirm that, for incomplete adaptation, the use of the one‐step CAT is incorrect, and we propose that the use of a two‐step CAT16 model be mandatory for future applications.     

Preprocessing to CIECAM02 input color with chromatic background

A preprocessing to CIECAM02 input color for color appearance prediction was proposed. In this study, 8640 color appearance matching pairs (NCS color charts with red, green, yellow, and blue backgrounds in a light booth and their reproductions with gray background on a CRT screen) were obtained by psychophysical experiment using the simultaneous‐binocular technique. Because only the lightness of background is included in CIECAM02, a color inducing vector based on opponent‐colors theory was introduced to preprocess CIECAM02 inputs, so that CIECAM02 may predict the corresponding color of an input color with chromatic background as well. By data fitting, a color preprocessing formula describing a relationship between the color inducing vector and the NCS chromaticness was conducted. Furthermore, the formula's performance was tested and the results showed that it was good for implementing the color appearance prediction of input colors with different chromatic backgrounds.© 2006 Wiley Periodicals, Inc. Col Res Appl, 32, 40–46, 2007; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20287     

Theoretical analysis of subtractive color mixture characteristics III—Realistic colorants and single tristimulus dimension

Continuing our work to further understand the characteristics of stimulus values of a single tristimulus dimension in colors obtained by subtractive color mixture, discussions proceed related to realistic colorants. New theorems are intended to provide for the establishment of bounds for realistic colorants in mixtures when stimulus measurements of the constituent single‐colorant samples and the illuminant are obtainable. Related to the new theorems, a formulation is derived for the calculation of the bounds of realistic colorants whose spectral transmittances are represented by weighted combinations of basic functions. By solving the formulation, numerical illustrations are provided for various conditions. The results contribute toward a comprehensive modeling of subtractive color mixture. © 2005 Wiley Periodicals, Inc. Col Res Appl, 30, 354–362, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.