A Comparison of Two Different Light Booths for Measuring Color Difference of Metameric Pairs

A standardized source of light is essential for visual color assessments, which is why lighting booths were developed. For the best results in visual assessment, it is important to consider the right choice of light source, the right viewing conditions, and the variability of the viewer. To date, many light booth technologies have been introduced to meet user demands. Since most of the light sources on the market are characterized by the designer or manufacturer, the resulting variations from booth-to-booth remain. In this study, we compared the performance of two standard light booths to assess the color difference of eleven metameric pairs. In this study, we checked an earlier technology-based light booth that is still used in the textile industry and contains illuminant A (Tungsten lamp) with CCT 2700 K, TL84 (tri-band fluorescent tube) with CCT 4000 K, and simulator D65 (CCT 6500 K) with a different light booth whose original light sources have been replaced by currently available LED retro kits from equivalent CCTs. As an inexperienced customer or industrial user, our question was, how important is this replacement? The results revealed that two different standard lighting technologies with similar CCTs cannot reproduce the same estimates because the light sources produced different SPDs. It is illustrating that caution is necessary when comparing results obtained from two different light booths containing light sources with similar CCTs but different SPDs. This comparative study suggested that the variability of the light sources’ SPDs or the observer or the sample should be modeled considering light booth’s technology to estimate its contribution to the overall variability. The close relationship between perceived and CAM02-UCS suggests that if both booths are used after the light sources have been calibrated, a formula based on color appearance models must be used to predict color appearance. To obtain better agreement between perceived and calculated color difference, one must need to avoid light booths with nominally white light sources.

Color Appearance Shifts Depending on Surface Roughness, Illuminants, and Physical Colors

Texture is an important synesthetic design element used in textile products. The three-dimensional surface of texture changes the amount and angle of reflected light causing a color appearance change from its original color. In this work, for a wide range of colors, it was quantitatively analyzed how the color appearances change depending on different textures and illumination, such as CIE standard illuminants A, F11, F2, and D65. It was found that strong-textured fabrics (with a surface roughness Ra of 0.46 mm) had larger hue appearance changes and consequent overall color appearance changes from their true colors due to illuminants than non-textured papers (with a surface roughness Ra of 0.03 mm). Between two types of fabrics with different textures of 0.25 and 0.46 mm, however, there was no significant difference in the magnitude of color appearance changes, indicating that the difference in surface roughness greater than 0.43 mm can produce significant differences in color appearance changes induced by illumination. It was also found that the magnitude and direction of color appearance changes under different CIE illuminants differed significantly according to the physical chroma and hue of the surface.

A Digital Test Chart for Visual Assessment of Color Appearance Scales

A digital color appearance test chart, akin to a ColorChecker® Chart for human perception, was developed and evaluated both perceptually and computationally. The chart allows an observer to adjust the appearance of a limited number of color patches to allow a quick evaluation of perceived brightness, colorfulness, lightness, saturation, and hue on a display. The resulting data can then be used to compared observed results with the predictions of various color appearance models. Analyses in this paper highlight some known shortcomings of CIELAB, CIECAM02, and CAM16. Differences between CIECAM02 and CAM16 are also highlighted. This paper does not provide new psychophysical data for model testing, it simply describes a technique to generate such data and a computational comparison of models.

Evaluation of anthocyanin corn under various agro-environment in Indonesia

In the last decade, purple corn gain more attention mainly due to its high nutritional value and attractive color appearance. Purple corn contain anthocyanin 350% higher than normal corn. Based on its excellence, the research was conducted to find out of high yield purple opv corn with good resistance to downy mildew. The experiment was conducted by using randomized block design with three replication. The variable observed including agronomic character like vegetative, generative and scored disease of downy meldows. The result showed that two opve candidate were PMU(S1).Synth.F.C1 and PMU(S1).Synth.D.C1 have the highest yield6,80-6,85 t/ha, higher 50% than PLU. C0 (check). PMU(S1).Synth.F.C1 showed moderate resistence to downy meldows (20%-35%) and PMU(S1).Synth.D.C1 susceptible (>60%).

G0 Revisited as Equally Bright Reference Boundary

Brilliance and zero grayness (denoted as G0) and are two terms coined by Ralph Evans. Nayatani, Heckaman and Fairchild have done series of work to incorporate them into comprehensive color appearance models. In this work, those concepts were reexamined to scale lightness/brightness across the chromaticity diagram. Specifically, observers, mostly with a color science background, were asked to adjust the luminance of a color patch to appear with no grayness, or equivalently just about/cease to glow. The hypothesis was that lightness can be equalized across those chromaticities and the Helmholtz-Kohlrausch effect is automatically incorporated. This hypothesis was verified in a follow-up experiment where another group of observers completed paired comparisons of the brightness between the collected G0 results. The G0 task was also repeated under another two levels of adaption backgrounds, based on which different absolute brightness results for a given chromaticity might be derived. In addition, high correlations between the G0 results (as a perceptual boundary between appearance modes) and different physical gamut boundaries including MacAdam's optimal colors were found for possible computational proxies and ecologically meaningful implications.

Comparison of remote and in-person tutorials of color appearance phenomena

Accurately describing the effect of lighting on color appearance phenomena is critical for color science education. While it is ideal to conduct in-person tutorials to demonstrate the color appearance fundamentals, laboratory tutorials have been limited due to COVID-19. The limitation of in-person gatherings and the increase popularity of remote teaching help evoke alternative methods to demonstrate color appearance phenomena. Here, a remote tutorial method is described, and results are compared to in-person tutorials. While the remote tutorial had weaker result in representing observers' color experience compared to the in-person lab tutorial, remote demonstrations can be used to demonstrate and discuss the limitations of color imaging, and the difference between the human visual system and digital imaging systems.

A new corresponding color dataset covering a wide luminance range under high dynamic range viewing condition

An experiment was carried out to investigate the change of color appearance for 13 surface stimuli viewed under a wide range of illuminance levels (15-32000 lux) using asymmetrical matching method. Addition to the above, in the visual field, observers viewed colours in a dark (10 lux) and a bright (200000 lux) illuminance level at the same time to simulate HDR viewing condition. The results were used to understand the relationship between the color changes under HDR conditions, to generate a corresponding color dataset and to verify color appearance model, such as CIECAM16.

Color Layer Scissioning in See-Through Augmented Reality

Color appearance of transparent objects is not adequately described by colorimetry or color appearance models. Despite the fact that the retinal projection of a transparent object is a combination of its color and the background, measurements of this physical combination fail to predict the saliency with which we perceive the object's color. When the perceive color forms in the mind, awareness of their physical relationship separates the physical combination into two unique perceptions. This is known as color scissioning. In this paper a psychophysical experiment utilizing a seethrough augmented reality display to compare virtual transparent color samples to real color samples is described and confirms the scissioning effect for lightness and chroma attributes. A previous model of color scissioning for AR viewing conditions is tested against this new data and does not satisfactorily predict the observers' perceptions. However, the model is still found to be a useful tool for analyzing the color scissioning and provides valuable insight on future research directions.