Truly form-factor-free industrially scalable system integration for electronic textile architectures with multifunctional fiber devices.

An integrated textile electronic system is reported here, enabling a truly free form factor system via textile manufacturing integration of fiber-based electronic components. Intelligent and smart systems require freedom of form factor, unrestricted design, and unlimited scale. Initial attempts to develop conductive fibers and textile electronics failed to achieve reliable integration and performance required for industrial-scale manufacturing of technical textiles by standard weaving technologies. Here, we present a textile electronic system with functional one-dimensional devices, including fiber photodetectors (as an input device), fiber supercapacitors (as an energy storage device), fiber field-effect transistors (as an electronic driving device), and fiber quantum dot light-emitting diodes (as an output device). As a proof of concept applicable to smart homes, a textile electronic system composed of multiple functional fiber components is demonstrated, enabling luminance modulation and letter indication depending on sunlight intensity.

Exposure to cyan or red light inhibits the axial growth of zebrafish eyes.

Myopia, or nearsightedness, is the most common type of refractive error and is characterized by a mismatch between the optical power and ocular axial length. Light, and more specifically the spectral composition of light, has been known to influence myopic axial growth. In this pilot study, we exposed zebrafish to illuminations that vary in spectral composition and screened for changes in axial length. The illumination spectra included narrow band ultra-violet A (UVA) (peak wavelength 369 nm), violet (425 nm), cyan (483 nm), green/yellow (557 nm), and red (633 nm) light, as well as broad band white light (2700 K and 6500 K), dim white light and broad spectrum (day) light. We found that rearing zebrafish in cyan or red light leads to a reduction of the ocular axial length. The results of this pilot study may contribute to new perspectives on the role of light and lighting as an intervention strategy for myopia control.

Smart textile lighting/display system with multifunctional fibre devices for large scale smart home and IoT applications.

Smart textiles consist of discrete devices fabricated from-or incorporated onto-fibres. Despite the tremendous progress in smart textiles for lighting/display applications, a large scale approach for a smart display system with integrated multifunctional devices in traditional textile platforms has yet to be demonstrated. Here we report the realisation of a fully operational 46-inch smart textile lighting/display system consisting of RGB fibrous LEDs coupled with multifunctional fibre devices that are capable of wireless power transmission, touch sensing, photodetection, environmental/biosignal monitoring, and energy storage. The smart textile display system exhibits full freedom of form factors, including flexibility, bendability, and rollability as a vivid RGB lighting/grey-level-controlled full colour display apparatus with embedded fibre devices that are configured to provide external stimuli detection. Our systematic design and integration strategies are transformational and provide the foundation for realising highly functional smart lighting/display textiles over large area for revolutionary applications on smart homes and internet of things (IoT).

Spectral Tuning of White Light Allows for Strong Reduction in Melatonin Suppression without Changing Illumination Level or Color Temperature.

Studies with monochromatic light stimuli have shown that the action spectrum for melatonin suppression exhibits its highest sensitivity at short wavelengths, around 460 to 480 nm. Other studies have demonstrated that filtering out the short wavelengths from white light reduces melatonin suppression. However, this filtering of short wavelengths was generally confounded with reduced light intensity and/or changes in color temperature. Moreover, it changed the appearance from white light to yellow/orange, rendering it unusable for many practical applications. Here, we show that selectively tuning a polychromatic white light spectrum, compensating for the reduction in spectral power between 450 and 500 nm by enhancing power at even shorter wavelengths, can produce greatly different effects on melatonin production, without changes in illuminance or color temperature. On different evenings, 15 participants were exposed to 3 h of white light with either low or high power between 450 and 500 nm, and the effects on salivary melatonin levels and alertness were compared with those during a dim light baseline. Exposure to the spectrum with low power between 450 and 500 nm, but high power at even shorter wavelengths, did not suppress melatonin compared with dim light, despite a large difference in illuminance (175 vs. <5 lux). In contrast, exposure to the spectrum with high power between 450 and 500 nm (also 175 lux) resulted in almost 50% melatonin suppression. For alertness, no significant differences between the 3 conditions were observed. These results open up new opportunities for lighting applications that allow for the use of electrical lighting without disturbance of melatonin production.

Spatio-chromatic sensitivity explained by post-receptoral contrast.

We measured and modeled visibility thresholds of spatial chromatic sine-wave gratings at isoluminance. In two experiments we manipulated the base color, direction of chromatic modulation, spatial frequency, the number of cycles in the grating, and grating orientation. In Experiment 1 (18 participants) we studied four chromatic modulation directions around three base colors, for spatial frequencies 0.15-5 cycles/deg. Results show that the location, size and orientation of fitted ellipses through the observer-averaged thresholds varied with spatial frequency and base color. As expected, visibility threshold decreased with decreasing spatial frequency, except for the lowest spatial frequency, for which the number of cycles was only three. In Experiment 2 (27 participants) we investigated the effect of the number of cycles at spatial frequencies down to 0.025 cycles/deg. This showed that the threshold elevation at 0.15 cycles/deg in Experiment 1 was at least partly explained by the small number of cycles. We developed two types of chromatic detection models and fitted these to the threshold data. Both models incorporate probability summation across spatially weighted chromatic contrast signals, but differ in the stage at which the contrast signal is calculated. In one, chromatic contrast is determined at the cone receptor level, the dominant procedure in literature. In the other model, it is determined at a postreceptoral level, that is, after cone signals have been transformed into chromatic-opponent channels. We applied Akaike's Information Criterion to compare the performance of the models and calculated their relative probabilities and evidence ratios. We found evidence in favor of the second model and conclude that postreceptoral contrast is the most accurate determinant for chromatic contrast sensitivity.

How psychophysical methods influence optimizations of color difference formulas.

For developing color difference formulas, there are several choices to be made on the psychophysical method used for gathering visual (observer) data. We tested three different psychophysical methods: gray scales, constant stimuli, and two-alternative forced choice (2AFC). Our results show that when using gray scales or constant stimuli, assessments of color differences are biased toward lightness differences. This bias is particularly strong in LCD monitor experiments, and also present when using physical paint samples. No such bias is found when using 2AFC. In that case, however, observer responses are affected by other factors that are not accounted for by current color difference formulas. For accurate prediction of relative color differences, our results show, in agreement with other works, that modern color difference formulas do not perform well. We also investigated if the use of digital images as presented on LCD displays is a good alternative to using physical samples. Our results indicate that there are systematic differences between these two media.

How color difference formulas depend on reference pairs in the underlying constant stimuli experiment.

For calculating color differences, the CIEDE2000 and CIE94 equations are widely used and recommended. These equations were derived more than a decade ago, based for a large part on the RIT-Dupont set of visual data. This data was collected from a series of psychophysical tests that use the method of constant stimuli. In this method, observers need to compare the color difference within a sample pair to that between a reference pair. In the current investigation, we show that the color difference equation significantly changes if reference pairs are chosen in the underlying visual experiments that differ from what was used when creating the RIT-Dupont dataset. The investigation is done using metallic paint samples representing two color centers, red and yellow-green. We show that the reproducibility differs for three different reference pairs, and that for modeling the visual data for the yellow-green color center, extra model terms are required as compared to the CIEDE2000 equation. Our results suggest that observers differ in their ability to mentally convert a color difference recognized in a sample pair into an equivalent color difference along the color difference direction represented by the reference pair. We also find that in these tests the tolerance to lightness differences is widened by a factor of 1.3 to 1.6, and that for the red color center the tolerance ellipsoid is rotated by 30° as compared to the CIEDE2000 equation. The latter observations are possibly due to the metallic texture in the samples used for the current experiment.

Effects of chromatic image statistics on illumination induced color differences.

We measure the color fidelity of visual scenes that are rendered under different (simulated) illuminants and shown on a calibrated LCD display. Observers make triad illuminant comparisons involving the renderings from two chromatic test illuminants and one achromatic reference illuminant shown simultaneously. Four chromatic test illuminants are used: two along the daylight locus (yellow and blue), and two perpendicular to it (red and green). The observers select the rendering having the best color fidelity, thereby indirectly judging which of the two test illuminants induces the smallest color differences compared to the reference. Both multicolor test scenes and natural scenes are studied. The multicolor scenes are synthesized and represent ellipsoidal distributions in CIELAB chromaticity space having the same mean chromaticity but different chromatic orientations. We show that, for those distributions, color fidelity is best when the vector of the illuminant change (pointing from neutral to chromatic) is parallel to the major axis of the scene's chromatic distribution. For our selection of natural scenes, which generally have much broader chromatic distributions, we measure a higher color fidelity for the yellow and blue illuminants than for red and green. Scrambled versions of the natural images are also studied to exclude possible semantic effects. We quantitatively predict the average observer response (i.e., the illuminant probability) with four types of models, differing in the extent to which they incorporate information processing by the visual system. Results show different levels of performance for the models, and different levels for the multicolor scenes and the natural scenes. Overall, models based on the scene averaged color difference have the best performance. We discuss how color constancy algorithms may be improved by exploiting knowledge of the chromatic distribution of the visual scene.

Emotional effects of dynamic textures.

This study explores the effects of various spatiotemporal dynamic texture characteristics on human emotions. The emotional experience of auditory (eg, music) and haptic repetitive patterns has been studied extensively. In contrast, the emotional experience of visual dynamic textures is still largely unknown, despite their natural ubiquity and increasing use in digital media. Participants watched a set of dynamic textures, representing either water or various different media, and self-reported their emotional experience. Motion complexity was found to have mildly relaxing and nondominant effects. In contrast, motion change complexity was found to be arousing and dominant. The speed of dynamics had arousing, dominant, and unpleasant effects. The amplitude of dynamics was also regarded as unpleasant. The regularity of the dynamics over the textures' area was found to be uninteresting, nondominant, mildly relaxing, and mildly pleasant. The spatial scale of the dynamics had an unpleasant, arousing, and dominant effect, which was larger for textures with diverse content than for water textures. For water textures, the effects of spatial contrast were arousing, dominant, interesting, and mildly unpleasant. None of these effects were observed for textures of diverse content. The current findings are relevant for the design and synthesis of affective multimedia content and for affective scene indexing and retrieval.

Saliency of color image derivatives: a comparison between computational models and human perception.

In this paper, computational methods are proposed to compute color edge saliency based on the information content of color edges. The computational methods are evaluated on bottom-up saliency in a psychophysical experiment, and on a more complex task of salient object detection in real-world images. The psychophysical experiment demonstrates the relevance of using information theory as a saliency processing model and that the proposed methods are significantly better in predicting color saliency (with a human-method correspondence up to 74.75% and an observer agreement of 86.8%) than state-of-the-art models. Furthermore, results from salient object detection confirm that an early fusion of color and contrast provide accurate performance to compute visual saliency with a hit rate up to 95.2%.

Perceptual analysis of distance measures for color constancy algorithms.

Color constancy algorithms are often evaluated by using a distance measure that is based on mathematical principles, such as the angular error. However, it is unknown whether these distance measures correlate to human vision. Therefore, the main goal of our paper is to analyze the correlation between several performance measures and the quality, obtained by using psychophysical experiments, of the output images generated by various color constancy algorithms. Subsequent issues that are addressed are the distribution of performance measures, suggesting additional and alternative information that can be provided to summarize the performance over a large set of images, and the perceptual significance of obtained improvements, i.e., the improvement that should be obtained before the difference becomes noticeable to a human observer.

Brightness and darkness as perceptual dimensions.

A common-sense assumption concerning visual perception states that brightness and darkness cannot coexist at a given spatial location. One corollary of this assumption is that achromatic colors, or perceived grey shades, are contained in a one-dimensional (1-D) space varying from bright to dark. The results of many previous psychophysical studies suggest, by contrast, that achromatic colors are represented as points in a color space composed of two or more perceptual dimensions. The nature of these perceptual dimensions, however, presently remains unclear. Here we provide direct evidence that brightness and darkness form the dimensions of a two-dimensional (2-D) achromatic color space. This color space may play a role in the representation of object surfaces viewed against natural backgrounds, which simultaneously induce both brightness and darkness signals. Our 2-D model generalizes to the chromatic dimensions of color perception, indicating that redness and greenness (blueness and yellowness) also form perceptual dimensions. Collectively, these findings suggest that human color space is composed of six dimensions, rather than the conventional three.

Edge integration and the perception of brightness and darkness.

How do induced brightness and darkness signals from local and remote surfaces interact to determine the final achromatic color percept of a target surface? An emerging theory of achromatic color perception posits that brightness and darkness percepts are computed by weighting and summing the induction signals generated at edges in a scene. This theory also characterizes how neighboring edges interact to modulate the gain of brightness and darkness signals induced from one another. Here we assess evidence for this edge integration theory by means of computational modeling and a psychophysical experiment. We quantitatively show how local and remote edge induction signals in disk-ring displays give rise to either contrast or assimilation effects. Spatial integration of same-polarity edge signals supports a contrast effect, whereas integration of opposite-polarity signals supports an assimilation effect, particularly when the remote induction signal is much stronger than the local induction signal. The results confirm a key prediction of edge integration theory, namely, that strong assimilation effects can lead subjects to ignore the polarity of local edge information when setting achromatic color matches. The conditions necessary for strong assimilation effects are also associated with greater difficulty in setting matches, suggesting that caution is required when interpreting matching data in terms of gain control. We describe several avenues for further study of contrast, assimilation, and gain control.

Do cortical neurons process luminance or contrast to encode surface properties?

On the one hand, contrast signals provide information about surface properties, such as reflectance, and patchy illumination conditions, such as shadows. On the other hand, processing of luminance signals may provide information about global light levels, such as the difference between sunny and cloudy days. We devised models of contrast and luminance processing, using principles of logarithmic signal coding and half-wave rectification. We fit each model to individual response profiles obtained from 67 surface-responsive macaque V1 neurons in a center-surround paradigm similar to those used in human psychophysical studies. The most general forms of the luminance and contrast models explained, on average, 73 and 87% of the response variance over the sample population, respectively. We used a statistical technique, known as Akaike's information criterion, to quantify goodness of fit relative to number of model parameters, giving the relative probability of each model being correct. Luminance models, having fewer parameters than contrast models, performed substantially better in the vast majority of neurons, whereas contrast models performed similarly well in only a small minority of neurons. These results suggest that the processing of local and mean scene luminance predominates over contrast integration in surface-responsive neurons of the primary visual cortex. The sluggish dynamics of luminance-related cortical activity may provide a neural basis for the recent psychophysical demonstration that luminance information dominates brightness perception at low temporal frequencies.