Unique hue data for colour appearance models. Part III: Comparison with NCS unique hues

In this study, Swedish Natural Color System (NCS) unique hue data were used to evaluate the performance of unique hue predictions by the CIECAM02 colour appearance model. The colour appearance of 108 NCS unique hue stimuli was predicted using CIECAM02, and their distributions were represented in a CIECAM02 a_c–b_c chromatic diagram. The best‐fitting line for each of the four unique hues was found using orthogonal distance regression in the a_c–b_c chromatic diagram. Comparison of these predicted unique hue lines (based on the NCS data) with the default unique hue loci in CIECAM02 showed that there were significant differences in both unique yellow (UY) and unique blue (UB). The same tendency was found for hue uniformity: hue uniformity is worse for UY and UB stimuli in comparison with unique red (UR) and unique green (UG). A comparison between NCS unique hue stimuli and another set of unique hue stimuli (obtained on a calibrated cathode ray tube) was conducted in CIECAM02 to investigate possible media differences that might affect unique hue predictions. Data for UY and UB are in very good agreement; largest deviations were found for UR. © 2014 Wiley Periodicals, Inc. Col Res Appl, 40, 256–263, 2015     

Unique hue data for colour appearance models. Part I: Loci of unique hues and hue uniformity

Psychophysical experiments were conducted to assess unique hues on a CRT display for a large sample of colour‐normal observers (n = 185). These data were then used to evaluate the most commonly used colour appearance model, CIECAM02, by transforming the CIEXYZ tristimulus values of the unique hues to the CIECAM02 colour appearance attributes, lightness, chroma and hue angle. We report two findings: (1) the hue angles derived from our unique hue data are inconsistent with the commonly used Natural Color System hues that are incorporated in the CIECAM02 model. We argue that our predicted unique hue angles (derived from our large dataset) provide a more reliable standard for colour management applications when the precise specification of these salient colours is important. (2) We test hue uniformity for CIECAM02 in all four unique hues and show significant disagreements for all hues, except for unique red which seems to be invariant under lightness changes. Our dataset is useful to improve the CIECAM02 model as it provides reliable data for benchmarking. © 2010 Wiley Periodicals, Inc. Col Res Appl, 2011     

Testing the performance of CIECAM02 from 100 to 3500 cd/m2

Color appearance models were developed to characterize the color attributes of stimuli under different viewing conditions based on data collected through magnitude estimation or color matching experiments. Although human beings experience very high light levels under daylight and the reproduction of colors under daylight is important in the color and imaging industries, the existing color appearance models were developed based on the data that were collected under the conditions with luminance levels below 700 cd/m² due to the lack of facilities to produce stable illumination at high light levels. A recent study investigating color preference of an artwork under a wide range of light levels from 20 to 15 000 lx suggested that CIECAM02 cannot accurately characterize the color appearance under extremely high light levels. This study was designed to directly test the performance of CIECAM02 from 100 to 3500 cd/m². Human observers performed color match for four hues under a series pairs of adapting conditions with a haploscopic viewing condition. It was found that CIECAM02 had the best performance in characterizing the hue angles but the worse performance in characterizing the brightness with a maximum underprediction around 200% across a wide range of luminance. This was mainly due to the fact that CIECAM02 was developed based on the data collected under relatively low adapting luminance levels. The color appearance model that was proposed to use the adapting luminance levels in characterizing the cone compression in the postadaptation process was found to have a much better performance in characterizing the brightness.     

An investigation of colour appearance for unrelated colours under photopic and mesopic vision

Data were obtained for the colour appearance of unrelated colours under photopic and mesopic conditions. The effects of changes in luminance level and stimulus size were investigated. The method used was magnitude scaling of brightness, colourfulness, and hue. Two stimulus sizes (10° and 0.5°) and four starting luminance levels (60, 5, 1, and 0.1, cd/m²) were used. The results at 0.1 cd/m² had large variations, so data were obtained for two additional stimulus sizes (1° and 2°) at this luminance level. Ten observers judged 50 unrelated colours. A total of 17,820 estimations were made. The observations were carried out in a completely darkened room, after 20 min adaptation; each test colour was presented on its own. Brightness and colourfulness were found to decrease with decreases of both luminance level and stimulus size. The CAM97u model predicted brightness more accurately than CIECAM02 but gave worse performance in predicting colorfulness. For hue, CAM97u and CIECAM02 both gave satisfactory predictions. Using the brightness correlate from CAM97u, a new colour‐appearance model based on CIECAM02 was developed specifically for unrelated colours under photopic and mesopic conditions, with parameters to allow for the effects of luminance level and stimulus size. © 2011 Wiley Periodicals, Inc. Col Res Appl, 2011;     

Correcting veiling glare of refined CIECAM02 for mobile display

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.     

Repairing gamut problems in CIECAM02: A progress report

The color‐appearance model CIECAM02 has several problems, which can result in mathematical instabilities, due to the position of the chromatic‐adaptation primaries relative to the spectrum locus and to the presumed physiological cone primaries. To keep a corresponding (adapted) color within the positive gamut given by the chromatic adaptation primaries, the gamut must lie within the cone primary octant. To contain adapted colors within the positive cone‐primary octant, it suffices to truncate the action of adaptation at the boundary of that octant. Such modifications may be needed to avoid the mathematical problems in CIECAM02. © 2008 Wiley Periodicals, Inc. Col Res Appl, 33, 424–426, 2008     

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     

Experimental object color unique hue data for the mean observer for color appearance modeling

Color appearance models, among other things, predict the hue of a stimulus when compared with defined stimuli that represent the four unique hues. Recent studies have indicated that the stimuli representing with high reliability unique hue (UH) percepts vary widely for different color‐normal observers. The average yellow and blue UH stimuli for 102 observers, as determined in a recent experiment at medium chroma, differ considerably from the CIECAM02 defined unique hues, based on the Swedish NCS. Wide inter‐observer variability precludes color appearance models from accurately predicting, for individual observers, all four unique hue stimuli. However, models should predict accurately those of a well‐defined average observer. © 2008 Wiley Periodicals, Inc. Col Res Appl, 33, 505–506, 2008     

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.     

Proposed modification to the CIECAM02 colour appearance model to include the simultaneous contrast effects

A modified CIECAM02 colour appearance model, named CIECAM02‐m2, is proposed to enable CIECAM02 to predict the simultaneous contrast effect. The structure of the CIECAM02‐m2 is a development from CIECAM02, and contains two different procedures for modifying the reference white; one is for lightness and the other is for hue. The model was tested using a data set accumulated in this study and the LUTCHI data. The CV values for three colour attributes between predictions and experimental data were used to evaluate the accuracy of the model. The low CV values obtained show the performance of the CIECAM02‐m2 model to predict the simultaneous contrast effect satisfactorily. © 2007 Wiley Periodicals, Inc. Col Res Appl, 32, 121 – 129, 2007     

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     

Unique hue judgments using saturated and desaturated Munsell samples under different light sources

Past studies investigating the unique hues only used samples with a relatively high saturation levels under standard illuminants. In this study, 10 observers selected the four samples with unique hues from 40 V6C8 (Value 6 Chroma 8) and 40 V8C4 (Value 8 Chroma 4) Munsell samples under six light sources, comprising three levels of D_uv (i.e., 0, ?0.02, and ?0.04) and two levels of correlated color temperature (i.e., 2700 and 3500 K). Significant differences were found between the two chroma levels for unique blue and yellow, with the hue angles of unique yellow and blue judged using the desaturated samples being significantly different from those defined in CIECAM02. The iso‐lines of unique yellow, blue, and green did not always go through the origin of the a*‐b* or a′‐b′ planes in CIELAB and CAM02‐UCS. Thus, the problems of CIECAM02, CIELAB, and CAM02‐UCS identified in this study need further investigations.     

Irregularity in CIECAM02 and its avoidance

Were it not for an algorithm patch, the color‐appearance model CIECAM02 would sometimes be forced to evaluate fractional powers of negative numbers. The artifact arises because the red and green primaries of the initial CAT02 chromatic adaptation lie outside the positive gamut of the Hunt–Pointer–Estévez (HPE) primaries that subsequently convey the color signal in the model. Relocating the chromaticities of the HPE red and green primaries so as to lie on the CAT02 red–green line alleviates the problem, but adds a bit of X and Y to the revised HPE blue. An (x,y) diagram aids in visualizing the CIECAM02 gamut overlaps, with an extension that accommodates the HPE RGB triangle's enclosure of the point at infinity. © 2006 Wiley Periodicals, Inc. Col Res Appl, 31, 142–145, 2006     

Unique hue data and CIECAM02: A comment on Xiao et al

This letter to the editor notes the offsets from the origin of unique hue loci in the recent article, Unique Hue Data for Colour Appearance Models. Part III: Comparison with NCS Unique Hues by Xiao et al. [Color Res Appl 2015;40:256–263] and suggests that modifications to the cone response function in CIECAM02 be explored. © 2015 Wiley Periodicals, Inc. Col Res Appl, 2015     

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     

Investigation of colour appearance models for illumination changes across media

The key to achieving successful cross‐media colour reproduction is a reliable colour appearance model, which is capable of predicting the colour appearance across a variety of imaging devices under different viewing conditions. The two most commonly used media, CRT displays (soft copy) and printed images (hard copy), were included in this study using four complex images. The original printed images were captured using a digital camera and processed using eight colour appearance models (CIELAB, RLAB, LLAB, ATD, Hunt96, Nayatani97, CIECAM97s, and CAM97s2) and two chromatic adaptation transforms (von Kries and CMCCAT97). Psychophysical experiments were carried out to assess colour model performance in terms of colour fidelity by comparing soft‐copy and hard‐copy images. By employing the memory‐matching method, observers categorized the reproductions displayed on a CRT and compared them to the original printed images viewed in a viewing cabinet. The experiment was divided into three phases according to the different colour temperatures between the CRT and light source, i.e., print (D50, A, and A) and CRT (D93, D93, and D50), respectively). It was found that the CIECAM97s‐type models performed better than the other models. In addition, input parameters for each model had a distinct impact on model performance. © 2001 John Wiley & Sons, Inc. Col Res Appl, 26, 428–435, 2001     

The CRI‐CAM02UCS colour rendering index

A new colour rendering index, CRI‐CAM02UCS, is proposed. It predicts visual results more accurately than the CIE CIR‐R_a. It includes two components necessary for predicting colour rendering in one metric: a chromatic adaptation transform and uniform colour space based on the CIE recommended colour appearance model, CIECAM02. The new index gave the same ranks as those of CIE‐R_a in the six lamps tested regardless the sample sets used. It was also found that the methods based on the size of colour gamut did not agree with those based on the test‐sample method. © 2011 Wiley Periodicals, Inc. Col Res Appl, 2012     

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.     

Applying chromatic adaptation transforms to mixed adaptation conditions

A set of psychophysical experiments was conducted to investigate the state of adaptation between hardcopy and softcopy images when viewed under mixed illumination conditions. The performance of three chromatic adaptation transforms, CMCCAT97, CMCCAT2000 and CIECAT94, was compared to that of the S‐LMS, a mixed adaptation model. The adaptation ratios of each model were varied to investigate the state of adaptation of the human visual system. Printed complex images were used as originals. A series of softcopy reproduction pairs was displayed on a CRT with a D93 white point and compared to the original in an illuminated room. Three ambient lights were studied: a D50 simulator, an Illuminant A simulator and a Cool‐white fluorescence lamp. The experiments were divided into nine phases according to the changes of illuminants and the luminance levels. A simultaneous binocular matching technique was employed. Observers compared the hardcopy with a given pair of softcopies and identified which reproduction was the closer colour match. The results showed that the state of adaptation of the human visual system was between 40–60% adapted to the white point of the monitor regardless of the changes in illumination conditions. The overall results showed that CMCCAT2000 with proper adaptation ratio outperformed the other models and could be applied to mixed adaptation conditions. © 2003 Wiley Periodicals, Inc. Col Res Appl, 28, 436–444, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.10196