Chromatic adaptation to illumination investigated with adapting and adapted color

The state of chromatic adaptation was investigated by using the two‐room technique. This technique involves a subject in a room who looks a white board in a separate test room through a window and judges the color of the window using the elementary color naming method. When the subject room is illuminated with a colored light and the test room with a white light, the window appears to be a very vivid color, for which the apparent hue depends on the color of the subject room. The color is referred to as the adapted color. The subject also evaluated the appearance of the illumination color of the subject room, which is called the adapting color. Two types of illuminating light in the subject room, fluorescent lamps with 7 colors and LED lamps with 19 colors, were employed. The adapting and the adapted colors were plotted on a polar diagram that was used in the opponent color theory, from which the hue angles were obtained. The hue angle difference between the two colors did not appear to be 180° except for one pair of adapting and the adapted colors, which implies that chromatic adaptation does not follow the opponent color concept. An improvement was achieved to explain the results by introducing complementary colors relation between the adapting and adapted color.     

Color appearance of afterimages compared to the chromatic adaptation to illumination

The color appearance of negative afterimages was measured by the elementary color naming method, and the results were compared with those obtained by the two‐room technique. Twenty adapting stimuli were presented on a display sequentially. Subjects first assessed the color appearance of the stimuli. After looking at the adapting stimulus for 10 seconds, the subjects assessed color of the afterimage. Apparent hue of the afterimage was in general not opponent color to the adapting color. The relation between the adapting stimuli and the afterimages was analyzed by the angle difference Δθ, when apparent hues are expressed by the angles of the points on the polar diagram of the opponent color theory. The relation relationship of Δθ to the angle of the adapting color θ_ing was quite similar to the results obtained by the two‐room technique, implying that the chromatic adaptation shown by the afterimage also occurs in the brain rather than in the retina.     

Prediction of simultaneous contrast between map colors with Hunt's model of color appearance

The objective of this research was development of a quantitative model of simultaneous contrast (induction) to aid selection of sets of easily identified map colors. The model is an extension of R. W. G. Hunt's model of color appearance. Contrasts between central and proximal colors were used to adjust Hunt's lightness, relative redness-greenness, and relative yellowness-blueness measures. Human subject responses to CRT displays in an experiment were analyzed to produce a set of rules for selecting map colors. Rather than predict average perceptions for central/proximal color combinations, acknowledgment was made of the inherent variability in map readers' perceptions of color by developing generalized perception buffers that accounted for at least 90% of test subject responses. The task of selecting colors that will not be confused once they appear with numerous proximal colors on a map thus becomes a task of selecting colors that do not have buffers that overlap in color space. © 1996 John Wiley & Sons, Inc.     

Quantifying colour appearance. part V. simultaneous contrast

Experiments were carried out to investigate the effect of simultaneous contrast on colour appearance by varying the lightness, colourfulness, and hue of an induction field surrounding a test colour. A total of 814 test/surround combinations were displayed on high-resolution colour displays. Each was assessed by a panel of five to six observers using a magnitude estimation technique. the results indicate that colours presented on a computer display are affected by simultaneous contrast in a similar way to surface colours. All three colour appearance parameters studied (i.e., lightness, colourfulness, and hue) are affected and these effects are summarized. In general, the results support and add to the findings of the other studies. the Hunt colour appearance model was tested and gave a somewhat poor prediction to this data set. Further modifications are required to improve its performance. © 1995 John Wiley & Sons, Inc.     

A shift of the perceptual attributes of color due to the manifestation of the simultaneous contrast effect on a display

This research shows the effect of simultaneous contrast on a design solution that generates it, and it also shows how its manifestation affects the shift of perception attributes of the observer's color. In the conducted research, 55 subjects had to harmonize the primary stimuli from the reproduction obtained with the help of digital printing technology, with the primary stimuli presented on two computer screens. As a visual harmonization technique, simultaneous binocular harmonization was used. The primary stimuli were made achromatic, with a 50% Raster Tone value (RTV), and are surrounded by achromatic secondary stimuli whose values increase in steps from 10% RTV up to 100% RTV. A shift in the perceptual attributes of color has been shown with the help of the CIEDE2000 system. Using ANOVA with repeated-measures and Fisher's post hoc analysis, statistically significant differences were found between the perceived means of shift in the ΔC₀₀ chroma and ΔL₀₀ lightness on defined samples on both computer screens, while in the case of the ΔH₀₀ hue, no statistically significant differences were observed. The research also determined colorimetric differences in the ΔE₀₀ color difference. Moreover, the student's t test was used to determine that the effect is stronger when manifested on the Lenovo computer than on the Asus computer screen (P < .05).     

Recognized visual space of illumination: A new account of center‐surround simultaneous color contrast

Appearances of an object color in a space are determined by a cortical representation of illuminant for a space or the recognized visual space of illumination (RVSI). The simultaneous color contrast phenomenon on a simple center‐surround configuration can be explained by RVSI. It is hypothesized that our visual system constructs an RVSI on the surround and then that RVSI determines color appearance of the center test. If this is correct, the color contrast can be quite strong when the surround is enlarged to be an enclosed space. To support the hypothesis, color appearance of a physical gray test was measured in a green surround of various sizes. Observers were asked to do elementary color naming in the first experiment. The results showed same tendency for all observers: once the surround was extended to walls, a ceiling, and a floor of a box, perceived chromaticness abruptly increased. In other words, three‐dimensional surround evoked strong simultaneous color contrast. In the second experiment the matching method was employed with the green and other three surround colors: red, blue, and yellow. The results were consistent with the first experiment. The well‐known color contrast is thought to be a weak version of this color change. It suggested that RVSI plays an important role in the well‐known color contrast demonstration on two‐dimensional planes. © 2004 Wiley Periodicals, Inc. Col Res Appl, 29, 255–260, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20019     

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     

Remote adaptation effect on perceived subjective color: A model approach

An elaborated subjective color model is presented that includes the predictions of emulated Benham disk results and additional predictions that refer to local and remote achromatic illuminations on perceived subjective color shifts. A computer emulated Benham disk pattern was used as a stimulus to test the effects of remote illumination on its color sensation. An analytical model and its predictions are proposed in order to account for the results of the perceived hue shift, when changing either the remote illumination area or the stimulus illumination. This model is based on previous retinal color‐coded cells responses which yield the subjective color, and on local and remote adaptation mechanisms. The similarity between the role and mechanism of remote illumination (achromatic or chromatic) in subjective and perceived color is also discussed. © 2003 Wiley Periodicals, Inc. Col Res Appl, 28, 197–208, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.10145     

A comparison of lightness contrast effects in CRT and surface colours

The simultaneous contrast effect is investigated in this article. A total of 174 and 154 test/induction combinations were studied for CRT and surface colours respectively. Each combination was assessed by nine observers using a matching technique. The test and induction colours used for CRT colours were similar to surface colours using fabric samples. The results indicated a strong lightness contrast effect for both CRT and surface media; that is, the lightness of a test colour surrounded by a lighter induction colour was reduced for both CRT and surface colours. However, the effect in CRT medium was more pronounced than in the surface medium. © 2004 Wiley Periodicals, Inc. Col Res Appl, 30, 13–20, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20074     

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     

An algorithm for the selection of high‐contrast color sets

Nominal color coding is the aesthetic and functional use of color to convey qualitative information in graphical environments. The specification of high‐contrast color sets is a fundamental step in this process. We formulate the color‐coding problem here as a combinatorial optimization problem on graphs and present an algorithm that performs well and does not require that the function used to code the similarity between colors be a distance function. © 1999 John Wiley & Sons, Inc. Col Res Appl, 24, 132–138, 1999     

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.     

The relationship between visual acuity and color contrast in the OSA uniform color space

OSA uniform color space was used to study the relationship between visual acuity and OSA color contrast. Visual acuity is characterized by 50% minimal separable visual angle using Landolt-C. The OSA color contrast is characterized by the distance between colors in OSA color space. Twenty subjects with normal color vision were tested on 342 test sheets printed with colored Landolt-Cs and background. These results demonstrated that MSVA is approximately inverse log-linearly related to OSA color contrast (R² = 80.4%). Although luminance contrast (R² = 54.2%) is more salient than chromatic contrast (R² = 16.4%), both contrasts can induce very high visual acuity provided that they are sufficiently high. There is also evidence of an additive interaction between chromatic contrast and luminance contrast. Based on these findings, the OSA uniform color space and its color difference formula can be used as a scale for quantifying color contrast to accurately predict the size of colored text or symbols. © 1996 John Wiley & Sons, Inc.     

Effects of luminance,wavelength and purity on the color attributes: Brief review with new data and perspectives

A color stimulus may be characterized by three psychophysical dimensions (luminance, dominant wavelength, and purity), whose corresponding color attributes are lightness, hue, and chroma/colorfulness. The 3 × 3 matrix gives nine basic effects of the psychophysical dimensions on the color attributes (e.g. the effect of luminance on hue), but there are 49 possible combinations as more complex effects (e.g. the effect of luminance on hue and chroma, i.e. on chromaticity). Researching and quantifying such effects enables modelling of the underlying neural mechanisms and of color appearance. Using a simple nomenclature to identify the effects (e.g. Ph denotes the effect of Purity on hue), this paper briefly reviews and interrelates 15 of the commonest effects, giving new data or new graphical perspectives to clarify or fill gaps in the literature. Contrast and no‐contrast effects (stimuli viewed simultaneously or singly, respectively) are differentiated. © 2007 Wiley Periodicals, Inc. Col Res Appl, 32, 208–222, 2007     

Evaluation of color matching performances for SPEM and other models

We performed subjective experiments to evaluate color matching performance of the Spectral Properties Estimation Model (SPEM) and six other models (von Kries, CIELAB, LLAB, RLAB, Nayatani, and CIECAM97s) between two CRT monitors whose whites were quite different. Moreover, we evaluated color matching of these models between a CRT monitor and a printed image set in a dark room. The SPEM we developed is a new chromatic adaptation model based on hypothetical spectral properties estimation. This article describes the subjective experiments and the results obtained. The SPEM produced good color matching performance in the experiments. The detailed algorithm of the SPEM is given in the Appendix. © 2003 Wiley Periodicals, Inc. Col Res Appl, 28, 445–453, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.10197     

Changes in contrast thresholds with mean luminance for chromatic and luminance gratings: A reexamination of the transition from the DeVries–Rose to Weber regions

We have examined the influence of the mean luminance level on the detection thresholds for luminance and red–green chromatic gratings for three different spatial frequencies. The changes in detection thresholds according to the mean luminance level reflect the two different regions, the DeVries–Rose and Weber ranges, found in previous studies. The results for luminance gratings suggest that the transition luminance is proportional to the spatial frequency of the grating. Predictions based on the constant‐flux hypothesis indicate, however, that the transition luminance is proportional to the square of the spatial frequency of the grating and so do not describe the distributions of luminance contrast thresholds adequately. For chromatic gratings, we obtained the same transition luminance for the two lowest spatial frequencies, showing that luminance and chromatic mechanisms behave differently as far as the dependence of the transition luminance on spatial frequency is concerned. Our results suggest that the transition luminance is related to the peak spatial frequency of visual mechanisms that respond to luminance and chromatic gratings. © 2004 Wiley Periodicals, Inc. Col Res Appl, 29, 177–182, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20003     

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     

Optimization of color reproduction on CRT‐color monitors

In the present experimental study, we quantify the influence of the brightness and contrast levels of a CRT‐color monitor in the color reproduction of 60 Munsell chips distributed throughout the chromatic diagram. The images were captured by two CCD cameras, and the color differences were evaluated after reproducing the chips on a color monitor (the experiment was performed with 3 different monitors) for 9 combinations of brightness‐contrast levels. We evaluated the color differences with 3 different formulas: CIELAB, CIELUV, and CIE94. The results indicate that the optimal settings of a monitor, to minimize the color differences, is a medium or minimum brightness level in combination with a maximum contrast level. This combination ensures a more faithful color reproduction with respect to the original image. © 1999 John Wiley & Sons, Inc. Col Res Appl, 24, 207–213, 1999