Methods for traceable and validated measurement of temporal light modulation (Objectives 1 and 2) Based on the models given in IEC TR 63158:2018 and IEC TR 61547-1:2020, uncertainty components, which affect TLM quantities for flicker and the stroboscopic effect, have been identified. To propagate uncertainties, from the time domain to PstLM and SVM, models have been built. Using these models, sensitivity coefficients for uncertainty propagation have been determined for various waveforms. This uncertainty analyses will be used for the calibration of TLM measurement devices. Further investigation into the models revealed shortcomings of the current definitions as well as of reference implementations of TLA metrics. In addition, the improved models have been implemented in a luminous flux measurement setup which has been used to measure a large number of light sources for TLM.
For validation of implementations of TLM models a dataset, containing discretised mathematically generated waveforms, named “MetTLM TLM waveform set 1”, has been released on Zenodo, an open access repository. A report accompanying the dataset will be released soon on the MetTLM community on Zenodo.
Typical performance of measurement devices can be expressed in quality indices, which characterise how a physical effect influences the instrument’s reading. For TLM measurement devices quality indices have been defined for frequency response and dynamic range of signal. With the aim of characterising TLM measurement devices an LED-based facility has been built which will be used to assess dynamic range. A laser-based facility has been realised, and procedures to measure the frequency response of TLM measurement devices have been tested. The frequency response of various commercially available TLM measurement devices has been characterised and compared against the developed TLM-models, for flicker and the stroboscopic effect. An approach for a quality index for frequency response has been tested and will be further developed. Quality indices can be used for instrument classification, helping prospective instrument buyers selecting suitable TLM measurement equipment.
To validate the traceable TLM measurement methods, developed in Objective 1, through an interlaboratory comparison, artefacts have been selected and evaluated. A protocol for the comparison has been drafted.
In an experimental study, conducted in an environment illuminated with multiple light sources, image sequences at frame rates of 8 kHz and 4 kHz have been taken with RGB cameras. For each colour channel of the cameras, (namely, red, green, and blue) the TLM waveforms have been extracted for a region of interest marked in the image sequences. The results reveal the operation principle of tuneable white LED-based lamps, which consist of various types of white LEDs or RGB-LEDs. The study underlined the need to evaluate TLM by (multi-)spectral and spatially resolved measurements. Vivid examples have been obtained by imaging TLM measurements of field scenes: a Christmas tree with different fairy lights; car headlights and daytime running lights; road lighting; a car dashboard with head-up display. Heat maps of SVM have been generated for relevant TLM metrics.
For multi-spectral TLM measurement a hyperspectral camera is used to measure LED luminaires in office scenes. In addition, a four-channel based tristimulus TLM-meter had been set up as a unique product which is currently being evaluated.
In lab-based measurements, a set of three TLM luminance sources with patterned transmissive filters have been used to generate luminance contrast patterns which are then measured by using cameras. Doing so, limitations identified regarding the sampling theorem, resulting from the charge accumulating principle as used in most pixel-based detectors, could be addressed. The linearity of the TLM luminance source in constant luminance mode and during transient operation (regarding the actual TLM waveform compared to the nominal one) was investigated which beside well-known droop effects attributed to the included LED strains itself revealed issues regarding modulation depth (offset) and small deviations resulting from internal decay time constants of the electrical circuit. This information is a prerequisite for facilitating these sources in a characterization of TLM measurement devices.
Measurements taken with an imaging luminance measurement device (ILMD), on different lamps and luminaires, demonstrated the feasibility of TLM measurements with such devices. Results from this feasibility demonstration resulted in an improvement of the measurement modes implemented in a commercial CMOS-based ILMDs which will be further developed and demonstrated. Also, the impact of TLM on ILMD measurements of the average luminance was demonstrated. Errors as encountered during measurement for glare assessment from artificial night at light cause by high-intensity discharge lamps (HID-lamps), or pulse-width-modulated LEDs have been studied. In addition, the possibilities of using conventional cameras that provide a high frame rate mode of up to 1000 Hz, such as compact cameras or smartphone cameras dedicated for slow motion recordings, are investigated. As such cameras are widely used, this is expected to increase the uptake of results.
The investigation of the visibility of the phantom array effect started with a literature review. Based on the literature review, the effect of temporal frequency, colour of the light source, saccade amplitude and velocity, and ambient illumination on the visibility of the phantom array effect will be studied. Three psychophysical experiments have been designed, and the experimental protocols have been approved by the Ethical Review Board (ERB) at Eindhoven University of Technology. All three experiments use a two-interval forced-choice (2IFC) task for the observers, in which observers need to indicate in which of the two sequentially presented stimuli the phantom array effect is visible to them. Changing the modulation depth in the pair of stimuli in combination with the QUEST+ method (a Bayesian adaptive psychometric testing method), enables adaptive collection of data, thus reducing the number of perceptual experiments needed. By doing so, the visibility threshold of the phantom array effect can be determined for the various lighting conditions.
Experiment 1 focuses on the effect of temporal frequency and the chromaticity of the light source on the visibility of the phantom array effect. The results of Experiment 1 show an inverted U-shaped bandpass sensitivity function for the phantom array effect as a function of temporal frequency for all three chromaticities (i.e., red, green, and warm white) used in the experiment. The 3rd-order polynomial fit indicates a peak sensitivity at a temporal modulation of 600 Hz in all three cases. This finding is in line with earlier results in literature. However, the peak we found differs from the provisional model presented in CIE 249:2022, in which the sensitivity peaks around 1000 Hz for an averaged luminance of 1000 cd/m². In our study, the luminance is 50 cd/m², which might partially explain the discrepancy.
The fitted curves look similar across the three chromaticities used. However, the peak sensitivity is higher for red than for green and white. The MD (Modulation Depth) visibility threshold is about 3% for red, whereas it is 6-7% for green and white. In addition, the low-frequency slope is not as steep for the red colour, compared with the green and warm white colours. This indicates the phantom array effect is more visible at low frequencies for the red colour than for green and white colours. The curve for the green chromaticity seems to fit the least with the data, since we measured, on average, a constant sensitivity between 300 Hz and 1200 Hz.
In addition, a 3rd-order polynomial fit is unlikely to reflect the underlying visual processing mechanism of observing the phantom array effect. As a result, other fitting functions, such as Barten’s model used in CIE 249:2022, will be carefully evaluated and compared in the coming modelling efforts. Since the phantom array effect is a spatiotemporal visual phenomenon, modelling its sensitivity as a function of temporal frequency alone clearly has its limitations; expressing the sensitivity as a function of a spatially transformed variable (i.e., when the saccade speed is known) seems more appropriate. Substantial individual differences in sensitivity to the phantom array effect are also found in Experiment 1.
Experiment 2 focuses on modelling the temporal contrast sensitivity function to the phantom array effect, while Experiment 3 focuses on the effect of saccade-related characteristics (i.e., saccade amplitude and velocity) and the effect of ambient illumination on the visibility of the phantom array effect. The use of eye-tracking technology for Experiment 3 would help us understand to what extent the differences in their saccade speeds can explain the individual differences. Experiment 1 and Experiment 2 were carried out at Eindhoven University of Technology, the Netherlands, while Experiment 3 was carried out at the Scientific and Technical Centre for Building (CSTB), France. A description of the setup (for Experiment 1 and 2) and methods were presented at the CIE Expert Tutorial and Symposium on the Measurement of Temporal Light Modulation in Athens, Greece, October 2022. The results of Experiment 1 will be presented at the CIE 2023 conference in Ljubljana, Slovenia, September 2023. The data collected for Experiment 2 and 3 will be analysed and modelled following the recommendations given in CIE249:2022. Two scientific papers will be written and submitted to peer-reviewed journals.
29 September 2023
23 February 2023