Hue linearity of color spaces for wide color gamut and high dynamic range media

Constant hue loci in different color spaces for stimuli in Rec. 2020 color gamut and HDR conditions

Hue is an important attribute for characterizing a color stimulus, which is also an output in various color spaces. The investigations on the hue linearity and constant hue loci for different color spaces were generally conducted using conventional CRT displays or surface color samples, in which the color stimuli were within small color gamuts and viewed under standard dynamic range conditions. With the development of imaging technologies, the hue linearity and constant hue loci need to be investigated for wide color gamuts and high dynamic range conditions, which is critically important for image processing (e.g., gamut mapping and tone mapping). In this study, we carefully carried out a hue matching experiment using high-power LED devices. The color stimuli almost reached Rec. 2020 color gamut with the luminance above the diffuse white luminance (i.e., a high dynamic range condition). The results suggested that the hue linearity of IC_TC_P color space was the best among the nine color spaces. Twenty-one constant hue loci were derived for each of these nine color spaces, which can be used for hue correction when performing image processing and to further revise the color spaces.

Estimation of the perceptual color gamut on displays

A new method was developed to evaluate the perceived gamut of a display. A multispectral image of a white gypsum sphere was projected onto various highly chromatic lights, producing a series of images with distinct hue perceptions at the gamut boundary of displays. These images were subsequently used in a psychophysical experiment to examine the perceived color gamut. Afterwards, the visual results were further compared with the prediction results from various uniform color spaces (UCSs) and color appearance models (CAMs). The present results demonstrate that CAM16-UCS provides the most accurate prediction across the entire color gamut, whereas the cyan-to-blue region is more poorly predicted than the other hue regions for all CAMs and UCSs investigated.

Evidence for human-centric in-vehicle lighting: Part 2-Modeling illumination based on color-opponents

Illumination preference models are usually defined in a static scenery, rating common-colored objects by a single scale or semantic differentials. Recently, it was reported that two to three illumination characteristics are necessary to define a high correlation in a bright office-like environment. However, white-light illumination preferences for vehicle-occupants in a dynamic semi- to full automated modern driving context are missing. Here we conducted a global free access online survey using VR engines to create 360° sRGB static in-vehicle sceneries. A total of 164 participants from China and Europe answered three levels in our self-hosted questionnaire by using mobile access devices. First, the absolute perceptional difference should be defined by a variation of CCT for 3,000, 4,500, and 6,000 K or combinations, and light distribution, either in a spot- or spatial way. Second, psychological light attributes should be associated with the same illumination and scenery settings. Finally, we created four driving environments with varying external levels of interest and time of the day. We identified three key results: (1) Four illumination groups could be classified by applying nMDS. (2) Combinations of mixed CCTs and spatial light distributions outperformed compared single light settings (p < 0.05), suggesting that also during daylight conditions artificial light supplements are necessary. (3) By an image transformation in the IPT and CAM16 color appearance space, comparing external and in-vehicle scenery, individual illumination working areas for each driving scenery could be identified, especially in the dimension of chroma-, partially following the Hunt-Effect, and lightness contrast, which synchronizes the internal and external brightness level. We classified our results as a starting point, which we intend to prove in a follow-up-controlled laboratory study with real object arrangements. Also, by applying novel methods to display high fidelity 360° rendered images on mobile access devices, our approach can be used in the future interdisciplinary research since high computational mobile devices with advanced equipped sensory systems are the new standard of our daily life.

Evaluation of the colour quality of display primary: Part I. Chromaticity based methods

It is a challenge to determine the RGB primaries when designing a display. A big issue is to estimate the colorimetric performance of the display. In this paper, a systematic method was proposed to determine the best RGB primaries for a display. Nine testing metrics were implemented and they were divided into two groups (the gamut metrics and the colour related metrics). They were adopted to evaluate the performance of 52 displays having different RGB primary combinations. The results verified the proposed method. Some of the testing metrics gave similar results and it should be sufficient to choose some of them to reveal the overall performance of a display.

Testing uniform colour spaces using colour differences of a wide colour gamut

An experimental dataset, WCG, was assembled. The set includes 416 pairs of samples that surround 28 colour centres and covers a wide colour gamut. The data were used to test the performance of seven colour-difference models, CIELAB, CIEDE2000, CAM16-UCS, DIN99d, OSAGP, and ICTCP, Jzazbz. Colour discrimination ellipses were also fitted to compare the uniformity of the colour spaces. Different versions of the models were derived to improve the fit to the data, including parametric factors, kL, kC, and a power factor. It was found that the kL optimised CAM16-UCS, DIN99d, OSAGP models significantly outperformed the other colour models. In addition, the magnitude of the colour difference had an impact on visual assessment.

ZCAM, a colour appearance model based on a high dynamic range uniform colour space

A colour appearance model based on a uniform colour space is proposed. The proposed colour appearance model, ZCAM, comprises of comparatively simple mathematical equations, and plausibly agrees with the psychophysical phenomenon of colour appearance perception. ZCAM consists of ten colour appearance attributes including brightness, lightness, colourfulness, chroma, hue angle, hue composition, saturation, vividness, blackness, and whiteness. Despite its relatively simpler mathematical structure, ZCAM performed at least similar to the CIE standard colour appearance model CIECAM02 and its revision, CAM16, in predicting a range of reliable experimental data.

How Good Are RGB Cameras Retrieving Colors of Natural Scenes and Paintings?-A Study Based on Hyperspectral Imaging

RGB digital cameras (RGB) compress the spectral information into a trichromatic system capable of approximately representing the actual colors of objects. Although RGB digital cameras follow the same compression philosophy as the human eye (OBS), the spectral sensitivity is different. To what extent they provide the same chromatic experiences is still an open question, especially with complex images. We addressed this question by comparing the actual colors derived from spectral imaging with those obtained with RGB cameras. The data from hyperspectral imaging of 50 natural scenes and 89 paintings was used to estimate the chromatic differences between OBS and RGB. The corresponding color errors were estimated and analyzed in the color spaces CIELAB (using the color difference formulas ΔE^*_ab and CIEDE2000), J_za_zb_z, and iCAM06. In CIELAB the most frequent error (using ΔE^*_ab) found was 5 for both paintings and natural scenes, a similarity that held for the other spaces tested. In addition, the distribution of errors across the color space shows that the errors are small in the achromatic region and increase with saturation. Overall, the results indicate that the chromatic errors estimated are close to the acceptance error and therefore RGB digital cameras are able to produce quite realistic colors of complex scenarios.

Color difference evaluation for wide-color-gamut displays

With the emerging demand for wide-color-gamut displays, an issue has been raised in which the commonly used color difference formulae or uniform color spaces that were derived based on the data produced in the relatively smaller color gamut could be unreliable for predicting color differences in the highly saturated color regions. A psychophysical experiment was carried out for evaluating color difference at a luminance level of 310cd/m² on a wide-color-gamut display with an approximate DCI-P3 color gamut. Twelve color centers were selected to cover the entire gamut boundary. There were 192 pairs of samples over 12 color centers judged by 18 observers using the greyscale psychophysical method. The data set was used to test the performance of six uniform color spaces and color difference equations, CIELAB, CIEDE2000, CAM02-UCS, J_za_zb_z, IC_TC_P, and nIC_TC_P, a newly revised IC_TC_P formula. The color discrimination ellipses were used to test local and global uniformity of color spaces and compared with previous studies. The results revealed that all formulae improved their performance to have a mean lightness parametric factor of about 0.5. CAM02-UCS significantly outperformed the others in overall, local, and global uniformity. The high-quality visual data set is recommended to evaluate or to derive color difference formulae for WCG applications in the future.