Brilliance, contrast, colorfulness, and the perceived volume of device color gamut

With the advent of digital video and cinema media technologies, much more is possible in achieving brighter and more vibrant colors, colors that transcend our experience. The challenge is in the realization of these possibilities in an industry rooted in 1950s technology where color gamut is represented with little or no insight into the way an observer perceives color as a complex mixture of the observer’s intentions, desires, and interests. By today’s standards, five perceptual attributes – brightness, lightness, colorfulness, chroma, and hue - are believed to be required for a complete specification. As a compelling case for such a representation, a display system is demonstrated that is capable of displaying color beyond the realm of object color, perceptually even beyond the spectrum locus of pure color. All this begs the question: Just what is meant by perceptual gamut? To this end, the attributes of perceptual gamut are identified through psychometric testing and the color appearance models CIELAB and CIECAM02. Then, by way of demonstration, these attributes were manipulated to test their application in wide gamut displays. In concert with these perceptual attributes and their manipulation, Ralph M. Evans’ concept of brilliance as an attribute of perception that extends beyond the realm of everyday experience, and the theoretical studies of brilliance by Y. Nayatani, a method was developed for producing brighter, more colorful colors and deeper, darker colors with the aim of preserving object color perception – flesh tones in particular. The method was successfully demonstrated and tested in real images using psychophysical methods in the very real, practical application of expanding the gamut of sRGB into an emulation of the wide gamut, xvYCC encoding

Robust Chroma and Lightness Descriptors

New descriptors for lightness and chroma are presented that are based on properties of a wraparound Gaussian metameric to the given XYZ tristimulus coordinates. For the 1600 samples of the Munsell glossy set, both descriptors are found to correlate to Munsell value and chroma at least as well as the corresponding CIECAM02 descriptors when the Munsell samples are under the CIE C illuminant. However, when the illuminant is changed the new descriptors were found to be considerably more consistent under the second illuminant than those of CIECAM02

The New Colour Scales based on Saturation, Vividness, Blackness and Whiteness

This research project has two goals. One is to understand the third dimension of colour scales describing the extent of chromatic contents such as saturation, vividness, chromaticness and colourfulness, which are less widely used than the other dimensions, e.g. lightness and hue. With that in mind, the first aim of this work is to derive new models that may serve as an alternative to the third-dimension scale of colour appearance on the basis of colorimetric values. The second goal is to develop important scales, blackness and whiteness. They are widely used because of the popularity of the NCS system. To achieve the first goal, a psychophysical experiment for scaling 15 attributes (Korean corresponding words of “bright”, “light-heavy”, “active-passive”, “fresh-stale”, “clean-dirty”, “clear”, “boring”, “natural-not natural”, “warm-cool”, “intense-weak”, “saturated”, “vivid-dull”, “distinct-indistinct”, “full-thin” and “striking”) using the NCS colour samples was carried out with Korean observers. Each sample was presented in a viewing cabinet in a darkened room. Naive observers were asked to scale each sample using a categorical judgement method. From the results, two scales widely used to represent the third dimension were identified: saturation and vividness. The same samples were assessed by British observers using these two scales. There was a great similarity between the results of the British and Korean observers. Subsequently, more samples were included to scale not only the new third dimension scales (saturation and vividness) but also whiteness and blackness scales. In total, 120 samples were scaled for saturation, vividness and whiteness experiments, and 110 samples were scaled for a blackness experiment. Four sets of models were developed for each of the three colour spaces (CIELAB, CIECAM02 and CAM02-UCS). Type one was based on the ellipsoid equation. Type two was based on the hue-dependent model proposed by Adams (called “the hue-based model”). Each of the above two types was used to fit the present experimental (Cho) data and the NCS data, which were measured using a spectrophotometer. In total, 39 models were developed. The newly developed models were tested using the Cho and NCS datasets. The models that were based on the present visual data were tested using the NCS data. Similarly, the models developed from the NCS data were tested using the present visual data. The results showed that both types of models predicted visual data well. This means that the two sets of data showed good agreement. It is also proposed that the four scales (saturation, vividness, blackness and whiteness) based on CIECAM02 developed here are highly reliable

How well can people use different color attributes?

Two psychophysical experiments were conducted to analyze the role of color attributes in simple tasks involving color matching and discrimination. In Experiment I observers made color matches using three different adjustment control methods. The results showed that the Lightness, Chroma, Hue (LCH) and the Lightness, redness/greenness, blueness/yellowness ({L, r/g, y/b}) adjustment controls elicited significantly better performance than the display RGB controls in terms of both accuracy and time, but were not significantly different from each other. Expert observers performed significantly better than naive observers in terms of accuracy. Experiment II was a replication and extension of Melgosa, et al.’s experiment in which observers judged differences and similarities for color attributes in pairs of colored patches. At a 95% confidence level, the results from judging difference were significantly better than those from judging similarity. Hue and Lightness were significantly more identifiable than Chroma, r/g, and y/b. For all observers, lightness differences were more easily detected for less chromatic pairs than for higher chromatic ones. With respect to the size of the color differences, it was found that larger hue differences were more easily identifiable than smaller ones. Experts could more readily identify constant lightness and chroma for large color differences while constant hue was more identifiable for small color differences. There were no significant differences found between males and females. These results indicate that people do not have ready access to the lower level color descriptors such as the common attributes used to define color spaces and that higher level psychological processing involving cognition and language may be necessary for even apparently simple tasks involving color matching and describing color differences

The Effects of Neighboring Colors on Color Appearance

Department of Human and Systems EngineeringEvery day, people don???t perceive one color independently, but perceive many neighboring colors simultaneously. Most color studies regarding color appearance were done based on a single color. There are also earlier studies conducted on neighboring colors. However, it is not sufficient to focus on the effect of neighboring colors which color attribute affect the color appearance. Therefore, the effects of neighboring colors on color appearance need to be investigated. The research aimed to investigate how neighboring colors effect on color appearance. Color appearance experiment was carried out in the dark room by using a viewing booth. Total of 5 different neighboring color conditions were used in the experiment and those were ???Reference Condition???, ???Desaturated???, ???Saturated???, ???Dark???, and ???Light???. Total of 20 participants were invited to each neighboring color condition. Each participant evaluated Hue, Colorfulness, and Lightness of 22 test colors by using magnitude estimation method. To analyze the data, all participants??? responses were averaged by using arithmetic mean. Then the experiment results were analyzed according to neighboring color conditions. Furthermore the results were compared with the estimated results of two different color appearance models, CIELAB and CIECAM02, respectively. As for the findings of the experiment, Hue, Colorfulness, and Lightness tended to be affected by neighboring colors. First, Colorfulness was evaluated higher when neighboring colors were desaturated. Both Colorfulness and Lightness of test colors tended to be evaluated lower when neighboring colors were lighter. Hue was affected when neighboring colors were light. The results were compared with estimated color appearance values of CIELAB and CIECAM02. In overall, CIECAM02 showed better performance than CIELAB. The performances of both models tended to be worse as the neighboring color condition became extreme in a specific color attribute, especially when estimating Colorfulness and Lightness. The degree of color appearance changes was compared between experimental results and CIECAM02 values of ???Reference Condition??? and ???Light???. In the result, CIECAM02 model could not estimate the Colorfulness and Lightness changes according to neighboring color conditions sufficiently and it estimated the changes less than experimental results in both Colorfulness and Lightness. Therefore, further research regarding color appearance should be considered more in regards to surrounding environment.ope

Quantifying the colour appearance of displays.

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Color in scientific visualization: Perception and image-based data display

Visualization is the transformation of information into a visual display that enhances users understanding and interpretation of the data. This thesis project has investigated the use of color and human vision modeling for visualization of image-based scientific data. Two preliminary psychophysical experiments were first conducted on uniform color patches to analyze the perception and understanding of different color attributes, which provided psychophysical evidence and guidance for the choice of color space/attributes for color encoding. Perceptual color scales were then designed for univariate and bivariate image data display and their effectiveness was evaluated through three psychophysical experiments. Some general guidelines were derived for effective color scales design. Extending to high-dimensional data, two visualization techniques were developed for hyperspectral imagery. The first approach takes advantage of the underlying relationships between PCA/ICA of hyperspectral images and the human opponent color model, and maps the first three PCs or ICs to several opponent color spaces including CIELAB, HSV, YCbCr, and YUV. The gray world assumption was adopted to automatically set the mapping origins. The rendered images are well color balanced and can offer a first look capability or initial classification for a wide variety of spectral scenes. The second approach combines a true color image and a PCA image based on a biologically inspired visual attention model that simulates the center-surround structure of visual receptive fields as the difference between fine and coarse scales. The model was extended to take into account human contrast sensitivity and include high-level information such as the second order statistical structure in the form of local variance map, in addition to low-level features such as color, luminance, and orientation. It generates a topographic saliency map for both the true color image and the PCA image, a difference map is then derived and used as a mask to select interesting locations where the PCA image has more salient features than available in the visible bands. The resulting representations preserve consistent natural appearance of the scene, while the selected attentional locations may be analyzed by more advanced algorithms

Modelling of colour appearance of textured colours and smartphones using CIECAM02

The international colour committee recommended a colour appearance model, CIECAM02 in 2002, to help to predict colours under various viewing conditions from a colour appearance point of view, which has the accuracy of an averaged observer. In this research, an attempt is made to extend this model to predict colours on mobile telephones, which is not covered in the model. Despite the limited size and capacity of a mobile telephone, the urge to apply it to meet quotidian needs has never been unencumbered due to its appealing appearance, versatility, and readiness, such as viewing/taking pictures and shopping online. While a smartphone can act as a mini-computer, it does not always offer the same functionality as a desktop computer. For example, the RGB values on a smartphone normally cannot be modified nor can white balance be checked. As a result, performing online shopping using a mobile telephone can be difficult, especially when buying colour sensitive items. Therefore, this research takes an initiative to investigate the variations of colours for a number of smartphones while making an effort to predict their colour appearance using CIECAM02, benefiting both telephone users and makers. This thesis studies the Apple iPhone 5, LG Nexus 4, Samsung, and Huawei models, and compares their performance with a CRT colour monitor that has been calibrated using the D65 standard, to be consistent with the normal way of viewing online colours. As expected, all the telephones tested present more colourful images than a CRT. Work was also undertaken to investigate colours with a degree of texture. It was found that, on CRT monitors, a colour with a texture appears to be darker but more colourful to a human observer. Linear modifications have been proposed and implemented to the CIECAM02 model to accommodate these textured colours

Color Appearance Study under Two Lightings Having Different Illuminance Levels

Department of Human Factors EngineeringColor appearances of the objects are changing, depending on light sources. In everyday life, it is common to see a scene having two or more light sources together, or to look at an object that is shadowed by other objects. However, these situations might not be interpreted by current color appearance models, which are based on a single light source. With increasing interest in color reproduction of high dynamic scenes, color appearance research that can explain these multi illumination situations is necessary. In this research, it was intended to explain color appearance phenomena in the context where observers alternately saw two light sources having largely different illuminance levels (7005 lux and 376 lux, respectively) being present at the same time. This study also attempted to identify the observer's state of adaptation in the presence of multiple lightings, by exploring how color appearance in terms of hue, brightness and colorfulness changes in complex multiple lighting conditions, as opposed to single lighting conditions. Psychophysical experiment based on magnitude estimation technique was conducted to estimate color appearance and was composed of four sessions according to 1) illuminance of lighting either high or low, and 2) observer's adaptation to the lighting conditions for either single lighting or multiple lightings. Seven observers who were skillfully trained for color appearance estimation participated in the experiment and evaluated the color appearance of 50 color patches in terms of hue, colorfulness and brightness throughout the four sessions. As for the analyses of the results, human color perception data regarding hue, brightness and colorfulness of all observers were averaged and compared across sessions, based on the illuminance of lighting and the observer???s adaptation to the lighting conditions. Also, the color appearance model CIECAM02 performance was evaluated in terms of hue, brightness and colorfulness by comparing model prediction data with color perception data. As a result, through the color appearance study under two lightings with different illuminance levels, it turned out that hue appearance was not affected by the illuminance level of lighting and the observer???s adaptation to the lighting conditions. Perceived brightness and colorfulness were increased under higher illuminance level, but not affected by the observer's adaptation to the lighting conditions, explaining that observers locally adapted to the lighting where the color was directly shown. It was also found that the CIECAM02 H adeptly predicted hue appearance regardless of the illuminance level of lighting and the observer's adaptation to the lighting conditions. However, the CIECAM02 Q and the CIECAM02 M were overestimated under high illuminance lighting. The modification of the luminance-level adaptation factor, FL, by lowering the value from 1.20 to 0.67, helped the model not to overestimate Q and M. These results are based on color appearance perception when there are only two lightings having 19 times the illuminance difference. Consequently, it cannot be firmly concluded that these phenomena are common color appearance in multiple lighting environments. Therefore, it is necessary to conduct additional color appearance estimation research in multiple lighting conditions having more diverse illuminance level differences or having different configurations of lightings.clos