Changes in color appearance with variations in chromatic adaptation

Chromatic adaptation has been studied by applying methods of direct scaling to color appearances of invariant stimuli seen under different conditions of adaptation. The influence on color appearance of correlated color temperature of illumination, sample luminance factor, illuminance, and surround induction was studied. Perceived hue [expressed as proportions of unitary hues] varies with color temperature of illumination but not significantly with luminance factor or illuminance for the conditions of these experiments. Colorfulness varies with color temperature and also with luminance factor and illuminance, although relative colorfulness does not change significantly with illuminance. Lightness varies with luminance factor but is essentially independent of color temperature and illuminance over the ranges investigated here. Achromatic and chromatic lightnesses for samples of equal luminance differ in systematic ways that depend upon dominant wavelength and excitation purity. Color appearance data for daylight adaptation are highly correlated with Munsell Renotation specifications. The results may be used to determine corresponding colors for the adaptation conditions studied [equivalent to CIE Illuminants D₆₅, D₅₀, A, and dark adaptation]. They may also be used to determine color appearances under those conditions throughout a color solid. It is anticipated that they will be used as the basis for developing mathematical expressions for predictions of corresponding colors under other illumination conditions as well.     

Separate processing of chromatic and achromatic contrast in color constancy

In a preceding study we measured human color constancy in experimental conditions in which simulated illuminants and surface colors were varied in the chromatic domain only. Both illumination level and sample reflectance were fixed in that study. In the present study we focus on the achromatic dimension, both with respect to luminance contrast (Experiment 1) and overall illumination (Experiment 2). Sample‐to‐background contrast was varied over a two log unit range that covered both luminance decrements and increments. Illumination level was varied either for the short‐wave‐sensitive (S) cones only or for all three cone types simultaneously. Data predictions on the basis of a cone‐specific response function, derived in our preceding study, indicate that this model has difficulty in accommodating the results obtained with varying luminance contrast. However, a modified version of the response function, incorporating separate processing of color and luminance contrast, correctly predicts the data from both the present and the previous study. We also show that over a limited stimulus range our earlier response function is mathematically equivalent to Jameson and Hurvich's model of brightness contrast. The latter model, cast into a trichromatic format, performs equally well or better than our original response function, but is less accurate than our modified model. © 2005 Wiley Periodicals, Inc. Col Res Appl, 30, 172–185, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20105     

Modelling of chromatic contrast for retrieval of wallpaper images

Colour remains one of the key factors in presenting an object and, consequently, has been widely applied in retrieval of images based on their visual contents. However, a colour appearance changes with the change of viewing surroundings, the phenomenon that has not been paid attention yet while performing colour‐based image retrieval. To comprehend this effect, in this article, a chromatic contrast model, CAMcc, is developed for the application of retrieval of colour intensive images, cementing the gap that most of existing colour models lack to fill by taking simultaneous colour contrast into account. Subsequently, the model is applied to the retrieval task on a collection of museum wallpapers of colour‐rich images. In comparison with current popular colour models including CIECAM02, HSI and RGB, with respect to both foreground and background colours, CAMcc appears to outperform the others with retrieved results being closer to query images. In addition, CAMcc focuses more on foreground colours, especially by maintaining the balance between both foreground and background colours, while the rest of existing models take on dominant colours that are perceived the most, usually background tones. Significantly, the contribution of the investigation lies in not only the improvement of the accuracy of colour‐based image retrieval but also the development of colour contrast model that warrants an important place in colour and computer vision theory, leading to deciphering the insight of this age‐old topic of chromatic contrast in colour science. © 2014 Wiley Periodicals, Inc. Col Res Appl, 40, 361–373, 2015     

Matching large color differences with achromatic and chromatic surrounds

A color-difference-matching experiment was carried out using a computer-interfaced video-display system. Two reference color stimuli (i) and (j), and one test stimulus (i,j) surrounded by a large achromatic or chromatic stimulus were presented on the video screen. An observer was asked to adjust the test stimulus until he perceived it to have a color precisely “half way” between the colors of the given reference stimuli. A satisfactory half-way color was the one that produced perceptually equal color differences between (i) and (i,j) and (j) and (i,j) and simultaneously made these color differences as small as possible. Although the given color difference between the test stimuli (i) and (j) was generally quite large (100–200 just-perceptible color-difference steps) with the achromatic surround condition, the color-difference matching required to obtain the desired half-way color did not present any serious difficulties to the observer. The uncertainty of the chromaticity point of the half-way color was established by an ellipse of small to moderate size surrounding the mean chromaticity setting. The orientation and shape of the uncertainty ellipse was comparable with the orientation and shape of uncertainty ellipses obtained by other investigators studying color-difference matching involving much smaller color differences. The unexpected and noteworthy result of the present study lies in the location of the chromaticity point of (i,j) relative to those of (i) and (j) as a function of surround color. The location of (i,j) depends on the saturation of the surround stimulus but not its hue. Some speculative explanations of the observed results are offered.     

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     

Color classification of natural color images

The present article describes a color classification method that partitions a color image into a set of uniform color regions. The input image data are first mapped from device coordinates into the CIE L*a*b* color space, an approximately uniform perceptual color space. Colors used to represent a natural color image are classified by means of cluster detection in the uniform color space. The basic process of color classification is based on histogram analysis to detect color clusters sequentially. The principal components of a color distribution are extracted for effective discrimination of clusters. We present an algorithm for sequential detection of color clusters in the uniform color space, and the related algorithms for region processing and color computation. The performance of the method is discussed in an experiment using three kinds of natural color images.     

On attributes of achromatic and chromatic object‐color perceptions

Adapting luminance dependencies of various color attributes of object colors (lightness, brightness, whiteness‐blackness, whiteness‐blackness strength, chroma, and colorfulness) were clarified under white illumination with various adapting illuminances. The correlation between the perceptions of lightness and brightness and those of whiteness‐blackness and whiteness‐blackness strength is also clarified for achromatic object colors. The difference between the increase of brightness and that of whiteness‐blackness contrast (the effect studied by Stevens and Jameson—Hurvich) by raising their adapting illuminance is resolved without any contradiction. It is also shown that the nonlinear color‐appearance model developed by the author and his colleagues is able to explain the complex characteristics of all the above color attributes of object colors by making minor modifications to it. In addition, two kinds of classifications of various color attributes are given; one is based on the similarity of perception level, and the other on the degree of adapting illuminance dependency. © 2000 John Wiley & Sons, Inc. Col Res Appl, 25, 318–332, 2000     

Clarification of differences between variable achromatic color and variable chromatic color methods in the Helmholtz–Kohlrausch effect

The Helmholtz–Kohlrausch effect consists of two different approaches: the variable achromatic color (VAC) and variable chromatic color (VCC) methods. In this article the difficult conceptual difference between the methods is clarified using new explanations with their schematic figures. The concept of loci with various parameters on B / L or L / Y ratios is completely different between the two methods. The VCC method can determine perceived lightness values for achromatic and chromatic colors in the whole color space. The VAC method gives perceived lightness deviation between reference achromatic color and each of the various test chromatic colors both kept at the same Munsell Value. The VAC method can never give any information on equiperceived lightness to test chromatic colors. Despite the difference between the two methods, misuse of the VAC method is sometimes found for perceived lightness studies of various chromatic colors, because of its ease in observations. An example is shown for the L scale of OSA‐UCS. © 2006 Wiley Periodicals, Inc. Col Res Appl, 31, 146–155, 2006     

Simple reaction time to chromatic changes along L&M‐constant and S‐constant cone axes

The present study uses simple reaction time (RT) to examine the temporal response to chromatic changes of the red‐green (L‐2M) and yellow‐blue (S‐(L+M)) chromatic opponent channels. The hue‐substitution method was adopted to negate the luminance channel and generate changes in the chromatic input. The equiluminant stimuli were distributed along three tritanopic and three red‐green confusion lines. RTs were measured at equiluminance from three reference stimuli with chromatic changes occurring in either the tritan or red‐green directions. These reference stimuli also allowed evaluation of the influence of chromatic adaptation level on RT. The results showed that the mean value of RT, for the cone‐input variation either of the L‐2M channel (S‐constant cone axis) or of the S‐(L+M) channel (L&M‐constant cone axis), was described by a similar law as for luminance variations (Piéron's law). Then, the sensitivity of the two channels for chromatic changes was equalized to study their relative response speed. In addition, for both axes, an increase in the chromatic adaptation level lengthens response delay. © 2001 John Wiley & Sons, Inc. Col Res Appl, 26, 223–233, 2001     

The effect of spatial and chromatic parameters on chromatic induction

Chromatic induction is the change in the perceived color of a visual stimulus caused by surrounding stimuli in the field of view. Most reports of chromatic induction present results for a limited range of center and surround colors. We performed a series of forced response color matching trials in which size, location and color of surrounding visual fields were varied. Results are reported which illustrate that the effect of the surround on the center decreases exponentially as a function of separation between center and surround and that the effect of the surround on the center increases exponentially as a function of surround size. We also show that there is an optimal center-surround color difference for which chromatic induction is greatest.     

The effects of achromatic and chromatic color schemes on participants' task performance in and appraisals of an office environment

This study explores the effects of chroma on participants' performance and environmental appraisal of an office. The research was conducted in a full‐scale experimental room designed as a private office where achromatic and chromatic color schemes with coequal values were applied. Sixty participants were assigned tasks and given a questionnaire to appraise the spatial color schemes. The findings show that chroma significantly affects performance and space appraisal. In terms of accuracy and time spent performance scores measured significantly better in the room with the chromatic scheme than those in the room with the achromatic scheme. The office with the chromatic scheme was found to be more pleasant, attractive, satisfying and dynamic than the one with the achromatic scheme, whereas the achromatic scheme was thought to be more formal and harmonious. Categorization of pleasantness, harmony, dynamism and spaciousness by factor analysis also showed differences between the achromatic and chromatic schemes. © 2011 Wiley Periodicals, Inc. Col Res Appl, 2012     

Lighting source classification applied in color images to contrast enhancement

A novel methodology is proposed to identify the distribution of the intensity of the illuminant across a real-world image; with this information, the image can be classified as a homogeneous or nonhomogeneous lighting source. A criterion is proposed for deciding whether the illumination in the tested image is homogeneous or nonhomogeneous. This criterion is based on well-established methods that are dedicated to improving color characteristics and are commonly used to determine the color of the lighting source during a captured scene. The classification of homogeneous or nonhomogeneous illumination in real-world images is implemented in the BSD500 database, and the results are compared with a manual classification of images—proposed under subjective criteria—by the authors; in this way, one can analyze how the lighting source affects the image. This procedure provides a classification methodology for real-world image databases found in the scientific literature.     

Color reproduction of authenticable luminescent backlit transmissive color images

We propose a method for creating authenticable color images under UV excitation backlight by printing an invisible luminescent white emissive ink layer on the verso side of a transmissive substrate and a classical cmy image on the recto side of the substrate. In order to obtain a backlit image whose colors are as close as possible to the original image colors, we map the input image sRGB color gamut into the gamut formed by the emissive white source attenuated by the classical ink halftones. The relationship between surface coverages of the classical cmy ink halftones and the resulting backlit colors is obtained by accounting for the transmission of the emissive white through the paper substrate and through the classical cmy ink halftones. The transmittance of the classical ink halftones is modeled by a new halftone absorbance prediction model. The lightness range of the luminescent backlit color gamut is expanded by printing a black and white UV‐absorbing instance of the original color image in superposition with the luminescent white emissive layer and in registration with the cmy image printed on the recto side. Luminescent backlit color images provide a high anticounterfeiting security, as they combine a verso printed invisible luminescent ink layer, a verso printed black and white instance of the original image and a matching recto printed cmy instance of the original image. The resulting luminescent backlit image colors are close to the original image colors only when observed in transmission mode under UV light. © 2013 Wiley Periodicals, Inc. Col Res Appl, 39, 331–340, 2014     

Evaluation of the chromatic effectiveness of color pigments in restoration materials (lime and Portland cement)

The present work investigates the way in which cementing materials such as lime or Portland cement alter the quality of pigments normally used in coloring mortars for use in restoring stone construction of historic or artistic value. The colorimetric measurements indicated that both conglomerants diminish the chromatic capacity of the most pigments studied, with noteworthy losses of saturation and, in some cases, substantial variations in hue. The most serious incidents involved lead—vermilion and yellow—in both cases the hue shifting towards the orange range. The compositional study of the material by X‐ray diffraction (XRD) showed the decomposition of the compound chromophore, thereby accounting for its loss of color stability. © 2000 John Wiley & Sons, Inc. Col Res Appl, 25, 286–291, 2000     

Heuristic analysis influence of saliency in the color diversity of natural images

The estimation of chromatic diversity of natural images is commonly quantified through the computation of the number of discernible colors and has received much attention because of the different implications it has. However, the relationship between that number and the number of colors that really attracts the attention from an observer is still not clear and has been given little attention. New concepts about salient discernible colors‐the salient chromatic diversity of images‐ and remarkable salient colors‐connected colors in the same salient image area‐are introduced as opposed to the classical number of discernible object colors, which is usually evaluated for the global image without differentiating between probable attended and non‐attended image regions. We have used different well‐known saliency models to locate the salient regions in the scenes and have heuristically studied the extent to which those models preserve the chromatic diversity of natural images. Based on a bottom‐up approach, a reduction of around 40%‐55% in the number of discernible colors were obtained, and not all saliency algorithms preserved a uniform sampling of the original color gamut. Thus, our results suggests that particularly the graph‐based visual saliency model got good low dissimilarity values in comparison with other approaches that put emphasis solely on color as the main low‐level feature. Furthermore, we have introduced a quantification scheme of the average number of remarkable salient colors appearing in the images, and have proved how the heuristic‐based analysis of salient image areas can be used to create segmented images automatically according to their salient chromatic diversity.     

Considerations on the calibration of color displays assuming constant channel chromaticity

To calibrate a CRT color monitor, several assumptions are often made about its performance, one of the most accepted being constanel channel chromaticity. However, when the measurements are taken in a extended field of CRT screen, where it is assumed that only one primary phosphor is excited, the relative spectral radiance of the other primary phosphors that are contained in that field also contributes, if the background luminance is not zero. This contribution is greater at low levels of RGB channel stimulation and would invalidate the results obtained with calibration methods based on the hypothesis of constancy of chromaticity coordinates of RGB channels. We have studied this effect on the calibration of the CRT color monitor and, as a result, we propose a calibration that takes this effect into account. to evaluate the accuracy of the method, we have calculated color differences between the chromaticity that we wanted to reproduce and the one displayed with the CIELUV color-difference formula, and the color tolerances with the line element of MacAdam ellipses.     

Field trials on color appearance and brightness of chromatic object colors under different adapting-illuminance levels

Field trials of the nonlinear color-appearance model were done by using chromatic object colors under different illuminance levels. Color-appearance match and brightness match were made for Munsell color pairs by using haploscopic matching. Each color pair was only different in Munsell Chroma. The color-appearance and the brightness match were realized by adjusting the illuminance of one of the two haploscopic fields. Observed illuminances were significantly different between the color-appearance and the brightness matches for the same color pairs. The model accurately predicted the illuminances of color-appearance matches by using the metrics of lightness and chroma Q, T, P of the model, and those of brightness matches by using the metric brightness of the chromatic color B_c. In addition, the estimated contribution of colorfulness to brightness of chromatic colors was generally consistent with that predicted by the formula of Ware and Cowan. To test metric brightness B_c further, an additional experiment on haploscopic matching was done using illuminants with different R_a values. In the experiment, the same samples were used in both fields. Again, matching illuminances in this case were well predicted by using the same contribution factor of colorfulness to brightness already estimated.