Impact of the adapted white point and the cultural background on memory color assessments

With their inherent ability of serving as an internal reference, memory colors provide a very powerful concept in the evaluation of color rendering properties of white light sources with respect to visual appreciation. Recent results for example suggest fairly good correlations between memory‐based color quality metrics and the observers' general color preferences. However, due to technical limitations in the design of the underlying psychophysical experiments, they generally lack the explicit inclusion of realistic viewing and adaptation conditions, which is supposed to have a nonnegligible impact on the model prediction performance. In addition, intercultural effects might play a crucial role in the context of memory colors. For these reasons, the current article investigates the impact of both the adapted white point and the observers' cultural background on memory color assessments in order to contribute to a better understanding of these dependencies and their interactions. For this purpose, the color appearance rating results of Chinese and German observers were collected for a selection of 12 different familiar test objects assessed under two different adaptation conditions at 3200 K and 5600 K, respectively. From the statistical analysis of the experimental data, it is shown, in accordance to previous studies, that the impact of the observed intercultural deviations is likely to be of no practical importance even though significance is found. Despite considerably larger effect sizes, the same must be concluded for the two tested adaptation conditions

High‐resolution depth measurements in digital microscopic surgery

Fully digital microscopes are becoming more and more common in surgical applications. In addition to high‐resolution stereoscopic images of the operating field, which can be transmitted over long distances or stored directly, these systems offer further potentials by supporting the surgical workflow based on their fully digital image processing chain. For example, the image display can be adapted to the respective surgical scenario by adaptive color reproduction optimization or image overlays with additional information, such as the tissue topology. Knowledge of this topology can be used for computer‐assisted or augmented‐reality‐guided microsurgical treatments and enables additional features such as spatially resolved spectral reconstruction of surface reflectance. In this work, a new method for high‐resolution depth measurements in digital microsurgical applications is proposed, which is based on the principle of laser triangulation. Part of this method is a sensor data fusion procedure to properly match the laser scanner and camera data. In this context, a strategy based on radial basis function interpolation techniques is presented to handle missing or corrupt data, which, due to the measuring principle, can occur on steep edges and through occlusion. The proposed method is used for the acquisition of high‐resolution depth profiles of various organic tissue samples, proving the feasibility of the proposed concept as a supporting technology in a digital microsurgical workflow

Processing RGB Color Sensors for Measuring the Circadian Stimulus of Artificial and Daylight Light Sources

The three main tasks of modern lighting design are to support the visual performance, satisfy color emotion (color quality), and promote positive non-visual outcomes. In view of large-scale applications, the use of simple and inexpensive RGB color sensors to monitor related visual and non-visual illumination parameters seems to be of great promise for the future development of human-centered lighting control systems. In this context, the present work proposes a new methodology to assess the circadian effectiveness of the prevalent lighting conditions for daylight and artificial light sources in terms of the physiologically relevant circadian stimulus (CS) metric using such color sensors. In the case of daylight, the raw sensor readouts were processed in such a way that the CIE daylight model can be applied as an intermediate step to estimate its spectral composition, from which CS can eventually be calculated straightforwardly. Maximal CS prediction errors of less than 0.0025 were observed when tested on real data. For artificial light sources, on the other hand, the CS approximation method of Truong et al. was applied to estimate its circadian effectiveness from the sensor readouts. In this case, a maximal CS prediction error of 0.028 must be reported, which is considerably larger compared to daylight, but still in an acceptable range for typical indoor lighting applications. The use of RGB color sensors is thus shown to be suitable for estimating the circadian effectiveness of both types of illumination with sufficient accuracy for practical applications

Energy Efficient Lighting in Plant Factories: Addressing Utilance

Vertical farming is considered to play a crucial role in future food supply. Until today, the high amount of electrical energy required for artificial lighting has been problematic in this context. Various possibilities for increasing efficiency through adapted lighting conditions have been and are being investigated. However, comparably little attention is paid to increasing utilance, i.e., the amount of photons that can effectively be used by the plant. In this work, a novel targeted lighting strategy is therefore proposed that allows for a dynamic adaptation of the luminaires’ light distribution to match the effective crop size at each stage of plant growth in a fully-automated manner. It is shown that the resulting utilance can significantly be increased compared to standard full-coverage lighting. Moreover, it is found that the proposed strategy is likely to consume less than half of the electrical energy usually required for the latter. An additional increase in system efficiency can be prognosticated and the potential energy savings are estimated based on assumptions of future LED generations derived from literature

Measurement of Circadian Effectiveness in Lighting for Office Applications

Featured Application: In-field spatially resolved light measurements for the characterization of non-visual effects and proper prediction of the circadian effectiveness for human-centric lighting design. Abstract: As one factor among others, circadian effectiveness depends on the spatial light distribution of the prevalent lighting conditions. In a typical office context focusing on computer work, the light that is experienced by the office workers is usually composed of a direct component emitted by the room luminaires and the computer monitors as well as by an indirect component reflected from the walls, surfaces, and ceiling. Due to this multi-directional light pattern, spatially resolved light measurements are required for an adequate prediction of non-visual light-induced effects. In this work, we therefore propose a novel methodological framework for spatially resolved light measurements that allows for an estimate of the circadian effectiveness of a lighting situation for variable field of view (FOV) definitions. Results of exemplary in-field office light measurements are reported and compared to those obtained from standard spectral radiometry to validate the accuracy of the proposed approach. The corresponding relative error is found to be of the order of 3–6%, which denotes an acceptable range for most practical applications. In addition, the impact of different FOVs as well as non-zero measurement angles will be investigated

Unsupervised Clustering Pipeline to Obtain Diversified Light Spectra for Subject Studies and Correlation Analyses

Featured Application: Selection of most diverse light spectra from a larger set of possible candidates to be used in subject studies or for machine learning to find correlations between photometric and other parameters such as psychological, physiological, or preference-based outcome measures. Abstract: Current subject studies and data-driven approaches in lighting research often use manually selected light spectra, which usually exhibit a large bias due to the applied selection criteria. This paper, therefore, presents a novel approach to minimize this bias by using a data-driven framework for selecting the most diverse candidates from a given larger set of possible light spectra. The spectral information per wavelength is first reduced by applying a convolutional autoencoder. The relevant features are then selected based on Laplacian Scores and transformed to a two-dimensional embedded space for subsequent clustering. The low dimensional embedding, from which the required diversity follows, is done with respect to the locality of the features. In a second step, photometric parameters are considered and a second clustering is performed. As a result of this algorithmic pipeline, the most diverse selection of light spectra complying with a given set of relevant photometric parameters can be extracted and used for further experiments or applications

Determination of Speed-Dependent Roadway Luminance for an Adequate Feeling of Safety at Nighttime Driving

The purpose of this work is to determine as a function of velocity the minimal roadway luminance that is required to be judged as being bright enough for a driver to perform a nighttime driving task with an adequate feeling of safety. In this context, it shall also be evaluated which areas of the vehicle forefield are most crucial for the driver’s general brightness perception. A field study with 23 subjects and dimmable LED headlights was conducted, in which the subjects were given the task to assess their perceived brightness for different luminance levels caused by the headlights’ low-beam distribution in the vehicle’s forefield on a 5-step rating scale. The experiments were repeated for three different driving velocities of 0kmh⁻¹ (static case), 30kmh⁻¹, and 60kmh⁻¹, respectively. Results for the static case indicate that, for the roadway to be perceived as bright enough by 50% of the subjects, an average roadway luminance of 0.88 cdm⁻² is required in an area up to 32m in front of the vehicle. Furthermore, a significant effect of driving speed is observed. For example, at 60kmh⁻¹, the luminance must be increased to 1.54 cdm⁻² to be still perceived as sufficiently bright by 50% of the subjects

On the Color Rendition of White Light Sources in Relation to Memory Preference

Due to their potential use as an internal reference, memory colors have proven to provide an excellent conceptional approach for the color rendition evaluation of white light sources in terms of predicting visual appreciation. However, there are still some major drawbacks that can be identified in the principal design of existing memory-based or memory-related color quality metrics, of which the most severe is most likely that none of them were devised under realistic adaptation and viewing conditions. With the aim of contributing to a more comprehensive understanding of the nature of memory colors, a new experimental approach based on the color appearance rating of real familiar test objects perceived in a more realistic contextual viewing environment should therefore be presented as a main part of the current thesis trying to overcome the shortcomings of previous work. Besides attempting to draw universally valid conclusions about the memory colors' general characteristics, additional focus should be on the investigation of the impact of both the white point of adaptation and the observers' cultural background on the memory color assessments. By providing a comprehensive statistical analysis of the experimental data, it is shown that a significant effect on the observers' color appearance ratings can be reported for these two potential impact factors. With the corresponding dependencies being eventually known, a further goal of the current work should be the development of an improved memory-based color quality metric providing a superior tool for developers and manufacturers that can be used for the optimization of state-of-the-art lighting solutions in cases where visual appreciation and high user acceptability are more important than color fidelity. In order to validate the excellent predictive performance of this new metric proposal, the results of a comprehensive meta-correlation analysis based on the data of several different psychophysical studies are additionally reported. From this evaluation, it can be concluded that the newly proposed color quality metric outperforms all alternative approaches considered in the analysis making it an excellent choice to finally replace the CIE general color rendering index (Ra) in its use as an optimization criterion for modern light sources to achieve high visual appreciation and observer preference for which the latter has actually not been intended at all