Brightness perception under photopic conditions: experiments and modeling with contributions of S-cone and ipRGC.

In 1924, the CIE published and standardized the photopic luminous efficiency function. Based on the standardized curve, luminous flux in lumens, luminance in cd/m[Formula: see text], and illuminance in lux are determined by an integral of the curve and the incident light spectra in photometers and are considered physical brightness. However, human brightness perception is not only weighted by this simple determination, but is a more complicated combination of all L-cones, M-cones, S-cones, rods and later ipRGCs, which was partly described by the equivalent brightness of Fotios et al. with the correction factor [Formula: see text]. Recently, new research has demonstrated the role of ipRGCs in human light perception. However, it is still unclear how these signal components of the human visual system are involved in the overall human brightness perception. In this work, human brightness perception under photopic conditions was investigated by visual experiments with 28 subjects under 25 different light spectra. In this way, the contributions of the signal components can be investigated. An optimization process was then performed on the resulting database. The results show that not only the [Formula: see text] component, but also the S-cones and ipRGC play a role, although it is smaller. Thus, the visually scaled brightness model based on the database optimization was constructed using not only illuminance but also S-cones and ipRGC with [Formula: see text] of 0.9554 and RMSE of 4.7802. These results are much better than the brightness model after Fotios et al. using only S-cones ([Formula: see text] = 0.8161, RMSE = 9.7123) and the traditional model without S-cones and ipRGC ([Formula: see text] = 0.8121, RMSE = 9.8171).

Numerical correlation between non-visual metrics and brightness metrics-implications for the evaluation of indoor white lighting systems in the photopic range.

From the beginning of the [Formula: see text] century until today, the demand for lighting systems includes not only visual parameters (brightness, contrast perception, color quality), but also non-visual parameters. It is necessary to define the new non-visual parameters for the realization of the new concept of Human Centric Lighting (HCL) or Integrative Lighting. As a contribution to this approach, many international research groups have tried to quantify the non-visual parameters such as Circadian Stimulus by Rea et. al. in USA ([Formula: see text], [Formula: see text]), Melanopic Equivalent Daylight ([Formula: see text]) illuminance, mEDI of the CIE S 026/E:2018 or the latest formula by Giménez et al., for the nocturnal melatonin suppression. Therefore, it is necessary to analyze the correlation between these non-visual metrics and brightness metrics such as the equivalent luminance of Fotios et al., or the latest brightness model of TU Darmstadt so that scientists, lighting engineers and lighting system users can correctly apply them in their work. In this context, this paper attempts to investigate and analyze these correlations between the three metric groups based on the database of 884 light sources of different light source technologies and daylight spectra. The obtained results show that the latest Circadian Stimulus model of Rea et. al. [Formula: see text] with the improvement of Circadian Light [Formula: see text] ([Formula: see text]) has solved the disadvantage of [Formula: see text], especially for the interrupted point between warm and cold white (about [Formula: see text]) or the junction between negative and positive signal of the opponent channel ([Formula: see text]). Moreover, these three metrics of the three research groups contain a high correlation coefficient, so that one metric can be transformed by linear functions to the other two parameters.

Determination and Measurement of Melanopic Equivalent Daylight (D65) Illuminance (mEDI) in the Context of Smart and Integrative Lighting.

In the context of intelligent and integrative lighting, in addition to the need for color quality and brightness, the non-visual effect is essential. This refers to the retinal ganglion cells (ipRGCs) and their function, which were first proposed in 1927. The melanopsin action spectrum has been published in CIE S 026/E: 2018 with the corresponding melanopic equivalent daylight (D65) illuminance (mEDI), melanopic daylight (D65) efficacy ratio (mDER), and four other parameters. Due to the importance of mEDI and mDER, this work synthesizes a simple computational model of mDER as the main research objective, based on a database of 4214 practical spectral power distributions (SPDs) of daylight, conventional, LED, and mixed light sources. In addition to the high correlation coefficient R2 of 0.96795 and the 97% confidence offset of 0.0067802, the feasibility of the mDER model in intelligent and integrated lighting applications has been extensively tested and validated. The uncertainty between the mEDI calculated directly from the spectra and that obtained by processing the RGB sensor and applying the mDER model reached ± 3.3% after matrix transformation and illuminance processing combined with the successful mDER calculation model. This result opens the potential for low-cost RGB sensors for applications in intelligent and integrative lighting systems to optimize and compensate for the non-visual effective parameter mEDI using daylight and artificial light in indoor spaces. The goal of the research on RGB sensors and the corresponding processing method are also presented and their feasibility is methodically demonstrated. A comprehensive investigation with a huge amount of color sensor sensitivities is necessary in a future work of other research.

Preliminary measure for the characterization of the usefulness of light sources.

A preliminary usefulness metric is defined. The metric is intended to characterize the energy efficiency of light sources in a more comprehensive way than the luminous efficacy of a source by taking selected spectral aspects of human centric lighting into consideration. The presented version of the metric is a combination of well-established measures of color quality, brightness and the circadian effect derived from the spectral power distribution of the light source. The metric includes a limited application dependence: it yields different values for interior and exterior applications, static and dynamic as well as relaxing and activating light source spectra. Light source categories (A-G) with preliminary category limits were also computed in the two-dimensional diagram associated with the metric. The metric should be considered as a basis for further discussions and not as a final solution.

Long-term memory color investigation: culture effect and experimental setting factors.

Memory colors generated continuous interest in the color community. Previous studies focused on reflecting color chips and color samples in real scenes or on monitors. The cognitive effect of culture was rarely considered. In this paper, we performed a comprehensive investigation of the long-term memory colors of 26 familiar objects using the asymmetric color matching method among Chinese and German observers on a display. Three experiments were conducted to evaluate the variations introduced by culture, context-based gray image, and initial matching color. Memory colors of important objects were collected and representative memory colors were quantified in terms of CIELAB L*, a*, and b* values. The intra- and inter-observer variations were analyzed by mean-color-difference-from-mean values and chromatic ellipses. The effects of different cultural groups and experimental settings were also shown.

Robust Underestimation of Speed During Driving: A Field Study.

Traffic reports consistently identify speeding as a substantial source of accidents. Adequate driving speeds require reliable speed estimation; however, there is still a lack of understanding how speed perception is biased during driving. Therefore, we ran three experiments measuring speed estimation under controlled driving and lighting conditions. In the first experiment, participants had to produce target speeds as drivers or had to judge driven speed as passengers. Measurements were performed at daylight and at night. In the second experiment, participants were required to produce target speeds at dusk, under rapidly changing lighting conditions. In the third experiment, we let two cars approach and pass each other. Drivers were instructed to produce target speeds as well as to judge the speed of the oncoming vehicle. Here measurements were performed at daylight and at night, with full or dipped headlights. We found that passengers underestimated driven speed by about 20% and drivers went over the instructed speed by roughly the same amount. Interestingly, the underestimation of speed extended to oncoming cars. All of these effects were independent of lighting conditions. The consistent underestimation of speed could lead to potentially fatal situations where drivers go faster than intended and judge oncoming traffic to approach slower than it actually is.

Effect of chromatic mechanisms on the detection of mesopic incremental targets at different eccentricities.

Spectral sensitivity functions for the threshold detection of mesopic incremental targets were compared for different target eccentricities (10, 20, and 30 degrees ) and for different mesopic backgrounds (0.1, 0.5 and 1.0 cd m(-2)). Relative responsivities of achromatic mechanisms (L + M and rods) and chromatic mechanisms (S and /L-M/) were estimated for each eccentricity and background. Chromatic mechanisms contribute significantly to detection but their effect is lower at 30 degrees . A new contrast metric (C(CHC2)) is introduced to account for the selective adaptation of the photoreceptors and the effects of the chromatic mechanisms i.e. broadening of the range of spectral sensitivity with multiple local maxima and yellow sub-additivity of detection performance. The C(CHC2) metric is compared with the achromatic contrast metric of the MOVE model (C(MOVE)). For the same target, C(CHC2) generally predicts a higher visibility level than C(MOVE). However, in accordance with visual observations, for grey or yellowish incremental targets appearing at the eccentricities of 20 and 30 degrees , the visibility predicted by C(CHC2) is less than the visibility predicted by C(MOVE).

Mesopic spectral sensitivity functions based on visibility and recognition contrast thresholds.

Human vision works in a complex way in the mesopic luminance range which is not yet clearly understood, although several important visual tasks are performed at these luminance levels. In this study, spectral data for detection visibility and recognition contrast sensitivity were obtained in visual experiments. From our data it appears that chromatic channels also influence mesopic contrast sensitivity. An achromatic model of spectral sensitivity is fitted to our experimental data and the remaining chromatic components are discussed.

Characterizing luminous efficiency functions for a simulated mesopic night driving task based on reaction time.

The objective of this study is to test the luminous efficiency functions V(lambda), V'(lambda), V(10)(lambda) and their linear combinations on the basis of a data set gained from a simulated mesopic night-time driving experiment. Another aim is to provide 'real-world' data for the 'X framework' or 'linear combination model', and to find out its limits in a practical situation. Human performance was measured by the reaction time method. Results show that the single parameter of the linear combination of photopic and scotopic luminous efficiency functions can be determined analytically with little variation for a given mesopic background luminance level and a given visual target colour, but the computation leads to considerable deviations comparing all three target colours (red, green and blue) used in the experiment. The conclusion for the given experimental conditions is that the single parameter of the linear combination model has an increasing deviation for lower background luminance levels.