Media‐dependent color appearance modeling based on artificial neural networks

In this study, we tried to consider various color appearance factors and device characterization together by visual experiment to simplify the across‐media color appearance reproduction. Two media, CRT display (soft‐copy) and NCS color atlas (hard‐copy), were used in our study. A total of 506 sample pairs of RGB and HVC, which are the attributes of NCS color chips, were obtained according to psychophysical experiments by matching soft copy and hard copy by a panel of nine observers. In addition, a set of error back‐propagation neural networks was used to realize experimental data generalization. In order to get a more perfect generalizing effect, the whole samples were divided into four parts according to different hues and the conversion between HVC and R_HVCG_HVCB_HVC color space was implemented. The current results show that the displays on the CRT and the color chips can match well. In this way, a CRT‐dependent reproduction modeling based on neural networks was formed, which has strong practicability and can be applied in many aspects. © 2006 Wiley Periodicals, Inc. Col Res Appl, 31, 218–228, 2006; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20209     

Prediction of Munsell appearance scales using various color‐appearance models

The chromaticities of the Munsell Renotation Dataset were applied to eight color‐appearance models. Models used were: CIELAB, Hunt, Nayatani, RLAB, LLAB, CIECAM97s, ZLAB, and IPT. Models were used to predict three appearance correlates of lightness, chroma, and hue. Model output of these appearance correlates were evaluated for their uniformity, in light of the constant perceptual nature of the Munsell Renotation data. Some background is provided on the experimental derivation of the Renotation Data, including the specific tasks performed by observers to evaluate a sample hue leaf for chroma uniformity. No particular model excelled at all metrics. In general, as might be expected, models derived from the Munsell System performed well. However, this was not universally the case, and some results, such as hue spacing and linearity, show interesting similarities between all models regardless of their derivation. © 2000 John Wiley & Sons, Inc. Col Res Appl, 25, 132–144, 2000     

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     

Assessing the application of an image color appearance model to basic self‐luminous scenes

Image color appearance models (Image CAMs) have been developed to predict the perception of complex scenes and are mainly used for image rendering and video reproduction applications. Among these Image CAMs, iCAM is an Image CAM that takes an image as the input and provides the perceptual attributes for each pixel. On the other hand, nonimaging CAMs are widely used and validated, but they always assume a simple test scene of a uniform flat stimulus, a quasi‐neutral background, and a surround. This study presents an evaluation of the performance of iCAM when applied to these simple self‐luminous scenes in predicting the influence of background luminance, background size, saturation, and stimulus size on stimulus brightness. The results show that iCAM is capable of predicting the effect of background luminance and some background size scenarios. However, for unrelated self‐luminous stimuli (dark background), the model predictions do not match the reference data. An evaluation of the effect of the filter kernel size and its relation to the physiological mechanism of image processing inside the visual system has been investigated. Furthermore, the impact of saturation and stimulus size on brightness seems to be underestimated by the model, because the Helmholtz‐Kohlrausch and stimulus size effects are not included. Hence, these findings call for an enhanced Image CAM.     

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     

Color appearance modeling of bicolor striped woven fabrics considering neighboring color effects

In this article, the effect of the spatial and colorimetric attributes of neighboring color on color appearance shift in bicolor striped woven fabrics is investigated. A total of 240 test/neighboring woven color combinations were constructed in four different striped paradigms. Each test color in the combinations was visually assessed by 12 observer panels with the use of the magnitude estimation method estimating the magnitude of perceptual color attributes lightness, colorfulness, and hue. The visual estimates obtained were analyzed statistically by employing correlation and simple regression methods, and, as a result, the following significant neighboring color effects were detected and individually defined: (1) neighboring color's size, lightness, colorfulness, and hue on test color's lightness, (2) neighboring color's colorfulness and hue on test color's colorfulness, and (3) neighboring color's hue on test color's hue. Furthermore, through multiple regression analysis, color appearance models by which the lightness, colorfulness, and hue of bicolor woven fabrics can be predicted were derived. The predictive performance of the models was evaluated by calculating the difference between the visually estimated and the predicted color appearances, using ΔL*, ΔC*, Δh°, and ΔE_CMC(2:1). Among all the derived models, the model producing the smallest mean error was chosen as a final model, and its great accuracy in color appearance predictions was verified through further statistical evaluation. It is envisaged that the findings of this research are of benefit to design textile products with bicolor striped woven fabrics to have desired color appearances. © 2016 Wiley Periodicals, Inc. Col Res Appl, 42, 512–521, 2017     

Investigation of metallic color perception using real‐world materials

Metallic colors have a unique appearance of glossiness with features such as highlights, contrast, and reflections on their surface, and therefore, metallic objects are very attractive to humans. Especially, gold, silver, and copper colors are familiar metals used as decorative materials, coins, and other furnishings. However, the mechanism and condition of metallic perception have not been fully investigated. There are a few studies for investigating metallic perception using rendered patches or images, but there is no study using real‐world objects. In our previous study, we developed a simple representation technique that made real objects appear to be made of gold by projecting a solid color onto a target nonmetallic object. By using the representation technique, in this study, we have further investigated the perception of metallic appearance such as gold, silver, and copper using real‐world materials, and analyzed the difference between these metallic perceptions. Our results indicate that the perception of the metallic object is different for gold, silver, and copper. Our new findings are as follows: the glitter required for the perception of gold and silver becomes an obstacle to the perception of copper; the metallic perception reveals that learning experience might be strongly affecting; and luminance adjustment is sensitive to the perception of metallic objects.     

Color reproduction and the naturalness constraint

This article aims to determine the process underlying the subjective impression about the fidelity of reproduced object colors. To this end, we present the concept of the naturalness constraint and a framework for specification of naturalness judgments. We consider several research questions that are essential for this framework and discuss plausible answers supported by experiments. In general, naturalness assessment of reproduced object colors can be (1) defined as similarity to prototypical object colors, and (2) characterized by a probability density function (e.g., Gaussian). Experiments show that (3) there is a considerable amount of consistency in naturalness judgments of locally and globally processed images (although observers are slightly more tolerant of global image processing), and (4) naturalness judgments vary for different object categories; e.g., subjects are more consistent in naturalness judgments of skin, grass, and sky reproductions than shirt reproduction. We suggest that (5) naturalness of a whole picture is determined by the naturalness of the most critical object in that picture. Finally, we introduce a naturalness index predicting perceived naturalness of color reproduction of real‐life scenes. © 1999 John Wiley & Sons, Inc. Col Res Appl, 24, 52–67, 1999     

Colour appearance shifts in two different‐sized viewing conditions

This study assessed the effect of size on colour appearance, using a colour matching paradigm where two sizes were presented in a setting similar to a normal colour selection interface. Twelve colours sampling the entire range of the colour spectrum were chosen as target stimuli. The target stimuli consisted of either a large (30° by 50°) or a small (0.5° by 0.5°) test field displayed on a cathode ray tube (CRT). In the experiment, a set of small colour samples consisting of the target and its neighboring colours was presented on the screen. Fifty‐seven participants were asked to pick a colour from the sample set that appeared to exactly match the target. Results in CIECAM02 showed a consistent increase in the apparent brightness (Q) but some decrease in saturation (s) for the larger field. Hue shifts were observed to form a systematic pattern. We noticed a discernable trend showing that, for targets of bluish or purplish colour hues, the accuracy of colour matching is lower and colour difference is greater in the condition of the large viewing field. © 2010 Wiley Periodicals, Inc. Col Res Appl, 2010     

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.     

Effective and efficient mapping of color appearance

The reproduction of color across different media and viewing condition requires color-appearance modeling. In order to obtain an effective and efficient mapping of color appearance, the authors define here a method to approximate the combination of the forward and reverse Hunt94 color-appearance models. The method consists in learning by examples the Hunt94 color mapping for each desired experimental setup. Learning is done by feed-forward neural networks trained with the back-propagation algorithm on training sets derived from the ANSI IT8 7.2 color target. Experimental results confirm the feasibility of the method. © 1997 John Wiley & Sons, Inc. Col Res Appl, 22, 308–317, 1997.     

Proposal of a new concept for color‐appearance modeling

A new type of color‐appearance model (CAM) is proposed together with its concept and flow of formulations. The topics described are: (1) The existence of two kinds of color‐appearance models, CAMs previously used and CAMs newly proposed. (2) All the CAMs, previously developed and used, do not predict color‐appearance attribute of perceived lightness of object colors under any illuminations. They may be adequately called “the model for predicting color‐appearance match between object colors under different adapting conditions.” (3) Newly improved CAMs take the Helmholtz–Kohlrausch effect in the VCC method into account. They can determine object colors with the same Tone (equi‐perceived lightness, equi‐whiteness‐blackness, and equi‐perceived chroma) irrespective of hues under reference illuminant. The newly improved models can be named Integrated CAMs. Their applicable fields are described in detail. © 2007 Wiley Periodicals, Inc. Col Res Appl, 32, 113–120, 2007     

Color‐person‐environment relationships

Although the nature of color and the person environment relationship are both well‐documented, it is posited that both domains need to be integrated to understand the active role that color plays in the relationship between a person and the surrounding environment. The color person environment relationship (COL‐PE) introduced in this article is an important theoretical concept for designers, and as a consequence, for environmental‐color researchers to investigate. The potential of color to be an active agent in the relationship between people and environments is introduced by drawing upon what is known about color and the person environment relationship from other sources. The nature of transition spaces is used to emphasize how color affects the emotional connection and disconnection between people and spaces. As an example of COL‐PE, transition spaces highlight the nature of the person who is also psychologically in‐transition and color as a potentially important aspect of the transitory experience. In addition, the connections between color and the constructs that we hold of the people who visit, work, or live in particular environments will be discussed briefly. Designers often focus on the object or artifact which is being colored (whether a building or a chair) as an end in itself, without considering in any depth how the designed objects or places can influence how people experience their daily activities and each other. COL‐PE is introduced as a means to address this omission and broaden designers' understandings of the potential impact of their work. The discussion of the aspects of environmental design (with particular reference to architecture and interior design), introduces the foundation of the COL‐PE as a particular way of addressing color in the built environment. The principles of COL‐PE are relevant for a range of disciplines involved in environmental design including urban design, landscape architecture, interior design, industrial design, and architecture. The COL‐PE aims to make explicit what is often an unrecognized or tacit understanding of the role of environmental color, and thereby, the article highlights the need for research to understand the relationship more fully. © 2008 Wiley Periodicals, Inc. Col Res Appl, 33, 312–319, 2008.     

Application of a color‐appearance model to vision through atmospheric haze

Environmental laws mandate the protection of visibility conditions in national parks and wilderness areas from atmospheric haze, which occurs due to the emissions of anthropogenic air pollutants. To calculate the improvement in visibility that results from the reduction of these air pollutants, it is necessary to quantify the relationship of haze to the color appearance of objects being viewed through it. To this end, a field study was conducted in the Great Smoky Mountains National Park in eastern Tennessee. Color appearance of objects was quantified by color matching with a special visual colorimeter. The Hunt94 color‐appearance model was used to compare these matches with simultaneous spectral measurements. In addition to the chromaticity coordinates and luminance of the object, the Hunt94 model requires a number of parameters such as the chromaticity of the adapting light and chromatic and brightness surround induction factors, which need to be determined for the outdoor viewing conditions. This article describes how this was accomplished. Although it accounts for differences in viewing conditions between the colorimeter and daylight conditions, the Hunt94 model does not account for the perceptual transparency effect of haze on outdoor color appearance. These results challenge the manner in which current air quality–visibility models are being utilized. © 1999 John Wiley & Sons, Inc. Col Res Appl, 24, 112–120, 1999     

Background luminance and subtense affects color appearance

Two psychophysical experiments were conducted to investigate the color appearance under non‐uniform surround conditions with variation of stimulus luminance, surround luminance, background luminance, background orientation, and background size. The results show that the background size and surround luminance influence the appearance intensively, but that the orientation of background pattern has little effect. A method to determine optimal parameters for the CIECAM02 color appearance model in lighting applications is proposed. An UGR‐based model also is optimized for brightness estimation. The luminance of adapting field can be estimated by Gaussian‐like functions. © 2016 Wiley Periodicals, Inc. Col Res Appl, 42, 440–449, 2017     

Differences in attributes between color difference and color appearance (chroma and hue) for near‐neutral colors

Chroma‐step perception and its corresponding color difference in the same hue direction are the different attributes on color perception. The differences between them are different for different hues. Hue‐appearance step and its corresponding color difference along the same hue circle also have completely different concepts. The causes of the above two facts are clarified. The information based on various experiments and theoretical considerations are given for supporting the facts. In addition, it is clarified that the relationship on color‐appearance step and color difference has completely different characteristics between the quantitative (chroma) and the qualitative (hue) attributes of object colors. The importance of chromatic strength (CS) on hue is clarified in each of the three color attributes hue, value, and chroma. © 2004 Wiley Periodicals, Inc. Col Res Appl, 30, 42–52, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20073     

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     

An integrated color‐appearance model using CIELUV and its applications

A new type of color‐appearance model is presented together with its formulations. It is named In‐CAM(CIELUV), which means the integrated color‐appearance model using CIELUV space. Using the In‐CAM(CIELUV), we can integrate its fields of applications in both colorimetric engineering and artistic color design. Various applications are introduced in colorimetric and color design fields. The In‐CAM(CIELUV) connects directly colorimetric color space and perceptual Hue‐Tone color order systems. In other words, the In‐CAM (CIELUV) gives a colorimetric basis for Hue‐Tone system. The three color attributes in the In‐CAM(CIELUV) space are mutually independent. This is a very convenient feature for selecting color combinations. Some two‐color combinations selected systematically in the In‐CAM(CIELUV) space are shown. © 2008 Wiley Periodicals, Inc. Col Res Appl, 33, 125–134, 2008     

Individual differences of unique hue loci and their relation to color preferences

Loci of the four unique hues (red, green, blue, and yellow) on the equiluminant plane on the color display and three preferred colors were obtained from 115 normal trichromats. We sought possible correlations between these measures. Different unique hue loci were not correlated with each other. The three preferred colors were not correlated with each other. We found five combinations of significant correlation between a preferred color and unique hue settings, yet the overall tendency is not very clear. We conclude that individual differences in color appearance measured by unique hues and color preferences measured by asking for favorite colors may not be predicted from each other or even within a category because the differences in the earlier visual mechanisms can be compensated for and these high‐level measures can be influenced by learning and experience. © 2004 Wiley Periodicals, Inc. Col Res Appl, 29, 285–291, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20023