Light Artifacts Research Articles

Improvement of temporal light artefact effects in commercial LED lamps

Temporal light modulation and its potential adverse visual effects on human observers, collectively known as temporal light artefacts (TLAs), have been limited by the European Union Ecodesign regulation. Limitations on two key TLA metrics, flicker and stroboscopic effect, were introduced in September 2021. This study analyses the impact of this regulation on commercial LED lamps by measuring multiple different consumer-grade LED E27 retrofit lamps by several manufacturers before and after the regulation. The lamps purchased after the Ecodesign regulation seem to favour a certain type of LED driver that provides the best TLA behaviour of all lamp types. The regulation, with respect to TLA, has resulted in the replacement of ill-behaving lamp types in the market by newer lamps with better TLA characteristics.

Hypothesis Testing for Progressive Kernel Estimation and VCM Framework.

Identifying an appropriate radius for unbiased kernel estimation is crucial for the efficiency of radiance estimation. However, determining both the radius and unbiasedness still faces big challenges. In this paper, we first propose a statistical model of photon samples and associated contributions for progressive kernel estimation, under which the kernel estimation is unbiased if the null hypothesis of this statistical model stands. Then, we present a method to decide whether to reject the null hypothesis about the statistical population (i.e., photon samples) by the F-test in the Analysis of Variance. Hereby, we implement a progressive photon mapping (PPM) algorithm, wherein the kernel radius is determined by this hypothesis test for unbiased radiance estimation. Second, we propose VCM+, a reinforcement of Vertex Connection and Merging (VCM), and derive its theoretically unbiased formulation. VCM+ combines hypothesis testing-based PPM with bidirectional path tracing (BDPT) via multiple importance sampling (MIS), wherein our kernel radius can leverage the contributions from PPM and BDPT. We test our new algorithms, improved PPM and VCM+, on diverse scenarios with different lighting settings. The experimental results demonstrate that our method can alleviate light leaks and visual blur artifacts of prior radiance estimate algorithms. We also evaluate the asymptotic performance of our approach and observe an overall improvement over the baseline in all testing scenarios.

MetaHDR: single shot high-dynamic range imaging and sensing using a multifunctional metasurface.

We present MetaHDR, which is a single-shot high-dynamic range (HDR) imaging and sensing system using a multifunctional metasurface. The metasurface is capable of splitting an incident beam into multiple focusing beams with different amounts of power, simultaneously forming multiple low dynamic range (LDR) images with distinct irradiance on a photosensor. Then, the LDR images are jointly processed using a gradient-based HDR fusion algorithm, which is shown to be effective in attenuating the residual light artifacts incurred by the metasurface and the lens flare. MetaHDR achieves single-shot HDR photography and videography that increases the dynamic range by at least 50 dB compared to the original dynamic range of the photosensor. It can also perform single-shot HDR sensing, including reflectance calibration and surface curvature estimation of reflective materials. MetaHDR's demonstrated functionalities could be broadly applied in surveillance and security, microscopic imaging, advanced manufacturing, etc.

Observations of the Polarized Solar Corona During the Annular Eclipse of 14 October 2023

We present results of a dual eclipse expedition to observe the solar corona from two sites during the annular solar eclipse of 14 October 2023 using a novel coronagraph designed to be accessible for amateurs and students to build and deploy. The coronagraph (CATEcor) builds on the standardized eclipse observing equipment developed for the Citizen CATE 2024 experiment. The observing sites were selected for likelihood of clear observations, for historic relevance (near the Climax site in the Colorado Rocky Mountains), and for centrality to the annular eclipse path (atop Sandia Peak above Albuquerque, New Mexico). The novel portion of CATEcor is an external occulter assembly that slips over the front of a conventional dioptric telescope, forming a shaded-truss externally occulted coronagraph. CATEcor is specifically designed to be easily constructed in a garage or “makerspace” environment. We successfully observed some bright features in the solar corona to an altitude of approximately 2.25 R⊙ during the annular phases of the eclipse. Future improvements to the design, in progress now, will reduce both stray light and image artifacts; our objective is to develop a design that can be operated successfully by amateur astronomers at sufficient altitude even without the darkened skies of a partial or annular eclipse.

Analysis of Artifacts and Errors on Intraoral Phosphor Plate Radiographs: A Retrospective Study

Introduction. The advantages of phosphor plates (PPs), including their flexibility, thinness, and wireless connectivity, have contributed to their widespread use in dentistry alongside the advancement of digital radiography techniques. Continuous use of PPs and certain errors may lead to artifacts on the images. This retrospective study aimed to determine the frequency and types of intraoral PP artifacts.
 Methods. This study was conducted on 814 intraoral PP radiographs, including periapical and bitewing images. The errors and artifacts were classified into 4 main categories: technical errors, plate-related artifacts, scanner-induced artifacts, and ambient light artifacts.
 Results. A total of 656 periapical and 158 bitewing radiographs were examined. The most observed artifacts on the radiographs were plate-related artifacts, followed by technical errors (n=542, n=461, respectively). Within the category of plate-related artifacts, the most common artifacts were cracks or scratches (n=418, 77.1%), while within the category of technical errors, these were cone-cut errors (n=188, 40.7%). Parallel or zigzag radiopaque lines were the most common scanner-induced artifacts (n=313, 98.7%) and fading was the most common ambient light artefact (n=93, 49.2%). On more than half of the PPs, more than one artifact group was observed.
 Conclusions. Cone-cut, cracks/scratches, parallel zigzag radiopaque lines, and fading were common PP artifacts and errors in this study. The analysis revealed that over half of the PPs exhibited appearance of more than one artifact group. The high frequency of artifacts poses a risk of incorrect and incomplete diagnoses in radiographs, emphasizing the crucial importance of understanding the causes and developing effective prevention strategies for artifacts to enhance the reliability of diagnostic imaging and ensure the accuracy of patient assessments.

Ratiometric fiber optic fluorescent pH sensor for hydroxide diffusion measurements in concrete

This article delineates the development of an advanced ratiometric pH optode designed for protracted monitoring of pH dynamics in cementitious materials—a crucial aspect of structural management. The optode features a dual-layer Hydromed™ D4 polymer pellet incorporating a pH-sensitive Naphth-AlkyneOMe fluorescent probe (pKa ≈ 12) and CdSe quantum dots as an internal reference. The polymer matrix, optimized with diamond powder and carbon black, enhances the signal while minimizing light artifacts. Demonstrating a robust response to pH fluctuations, the optode, utilizing ratiometric measurements, enables steadfast monitoring for up to 75 days.The experimental setup includes a Delrin® sample compartment housing a glass slide with the optode connected to an optical fiber via an SMA connector. HydroMed™ D4 films, forming the pH-sensitive layer, are deposited on the glass slide and secured. The optode configuration is fine-tuned to optimize signal intensity by reducing its length. For optode-detector coupling, a 1000 µm core diameter optical fiber links the optode, and a 405 nm LED illuminates the sensing film. The emission signal is collected through the optical fiber, and signals are processed using computer-controlled lock-in amplifiers.In the investigation of hydroxide ion diffusion through a concrete sample, the optode's efficacy was validated, aligning with pH electrode measurements. Addressing long-term stability, a degradation model uncovered leisurely kinetics with commendable stability. Slow degradation kinetics, with a reaction rate coefficient of 1.6 × 10⁻⁷ s⁻¹ and a half-life of 1180 h, exceeded expectations.This pH optode, showcasing an accurate and resilient response to pH variations within the 10 to 12.5 range, stands as a promising tool for monitoring pH dynamics in low-pH cementitious materials. The incorporation of a degradation model underscores fidelity over prolonged durations and offers a blueprint for enduring surveillance of concrete structures.

DUTC Net: A novel deep ulcer tissue classification network with stage prediction and treatment plan recommendation

Background and objectivesThe Chronic injuries caused by the venous valve called as Varicose ulcers. The pressure in the veins is increased as the valves of the veins allows blood to flow in backward direction. Detecting and segmenting varicose ulcer wound region is a separate step prior to the classification operation. In this work the novel customized Deep Ulcer Tissue Classification Network is proposed and it is named as “DUTC Net”. The goal of the proposed DUTC Net is i) to classify the tissue type by generating tissue map using segmented ulcer wound image ii) to identify the stages of ulcer and iii) Percentage of affected tissues in the wound. MethodsThe dataset contains various stages of varicose ulcer wound images. The first step is to preprocess the ulcer wound image to remove light artifacts and noise. After preprocessing segmentation is done to isolate the region of the varicose ulcer using active contour algorithm. The segmented area can be fed into proposed DUTC Net to get the respective tissue map of the ulcer wound images. The tissue map images are assigned as input to DUTC Net at the phase II. In this phase II, DUTC Net learns the features from the tissue map of the phase I and classifies the stages and percentage of affected tissues in the varicose ulcer wound image. ResultsWhile experimental analysis, the proposed method DUTC Net results sensitivity 97.9%, specificity 98% and accuracy 97.2% for the average of tissue classification and sensitivity 97.1%, specificity 98% and accuracy 97.5% for the average of stage classification. ConclusionThe proposed work is mainly used to classify the varicose ulcer stages, tissues types and affected area using DUTC Net to investigate the patients status and treatment methods.

Optical tomography in a single camera frame using fringe-encoded deep-learning full-field OCT.

Optical coherence tomography is a valuable tool for in vivo examination thanks to its superior combination of axial resolution, field-of-view and working distance. OCT images are reconstructed from several phases that are obtained by modulation/multiplexing of light wavelength or optical path. This paper shows that only one phase (and one camera frame) is sufficient for en face tomography. The idea is to encode a high-frequency fringe patterns into the selected layer of the sample using low-coherence interferometry. These patterns can then be efficiently extracted with a high-pass filter enhanced via deep learning networks to create the tomographic full-field OCT view. This brings 10-fold improvement in imaging speed, considerably reducing the phase errors and incoherent light artifacts related to in vivo movements. Moreover, this work opens a path for low-cost tomography with slow consumer cameras. Optically, the device resembles the conventional time-domain full-field OCT without incurring additional costs or a field-of-view/resolution reduction. The approach is validated by imaging in vivo cornea in human subjects. Open-source and easy-to-follow codes for data generation/training/inference with U-Net/Pix2Pix networks are provided to be used in a variety of image-to-image translation tasks.

Digital implementations for determination of temporal light artefacts of LED luminaires

Flicker and stroboscopic effects caused by a temporally modulated light source may be harmful for the human visual system. Standardized measurement methods have been developed for the related temporal light artefacts of LED luminaires. It was found out that the performance of the International Electrotechnical Commission (IEC) recommended flickermeter implementation is highly dependent on sampling frequency. Novel digital implementations for the flickermeter and stroboscopic effect visibility measure (SVM) were created to remove any inaccuracies. The performance of the novel Aalto implementations does not depend on the sampling frequency when running the test waveforms of the IEC standard through the implementations. As compared with the IEC recommended digital implementations, Aalto flickermeter decreases the average error related to the test waveforms from −0.05 to +0.003, and Aalto SVM meter also decreases the average error by almost two orders of magnitude.

Saccadic eye movement speed is related to variations in phantom array effect visibility

The phantom array effect is one of the temporal light artefacts that can decrease performance and increase fatigue. The phantom array effect visibility shows large individual differences; however, the dominant factors that can explain these individual differences remain unclear. We investigated the relationship between saccadic eye movement speed and phantom array visibility at two different angles and four different directions of saccadic eye movement. The peak speed of saccadic eye movement and the phantom array effect visibility were measured at different modulation frequencies of the light source. Our results show that phantom array visibility increased as eye movement speed increased; the phantom array visibility was higher at a wide viewing angle with fast eye movement speed than at a narrow viewing angle. Moreover, when clustered into subgroups according to individual eye movement speed, the mean speed of the saccadic eye movement of each subgroup is related to the variations in the visibility of the phantom array effect of the subgroup. Therefore, saccadic eye movement speed is related to variations in phantom array effect visibility.

Quantitative Assessment of Dimensional Evaluation and Artefacts from Filling Materials with CBCT Using Standard Phantom Roots.

To investigate the accuracy of dimensional evaluation and representation of artefacts generated by different gutta-percha (GP) cones with or without sealer with CBCT using a reproducible, standardised phantom root methodology. The reproducible artificial phantom roots with six root canal sizes from #25 to #50 and 0.04 taper were aligned according to the jaw curvature in a stone model for dimensional measurements. Each root was scanned while empty and filled with four types of filling materials. The specimens were scanned using the CS 9300 3D (Carestream Dental, Rochester, NY, USA) (at two different resolutions), 3D Accuitomo (J Morita, Kyoto, Japan) and NewTom VGi (Verona, Italy) CBCT systems. The hyperdense and hypodense axial slice artefacts from root canal sizes #40, #45 and #50 were recorded. Dimensions were significantly smaller and more accurate with CS 9300/0.09 mm voxel size than with other protocols. The hypodense band was found mostly in the CS 9300 3D system with 0.18 mm voxel size, especially in the buccal-lingual (95%) and coronal (64%) sections. The 3D Accuitomo CBCT system showed the lowest presence of the hypodense band. Areas of both light and dark artefacts were significantly larger in the coronal third than in the apical and middle thirds. Artefacts in the coronal locations and in buccal-lingual sections were more evident in the CS 9300 3D system with a 0.18-mm voxel size.

Efficient FMT reconstruction based on L1-αL2 regularization via half-quadratic splitting and a two-probe separation light source strategy.

Fluorescence molecular tomography (FMT) can achieve noninvasive, high-contrast, high-sensitivity three-dimensional imaging in vivo by relying on a variety of fluorescent molecular probes, and has excellent clinical transformation prospects in the detection of tumors in vivo. However, the limited surface fluorescence makes the FMT reconstruction have some ill-posedness, and it is difficult to obtain the ideal reconstruction effect. In this paper, two different emission fluorescent probes and L 1-L 2 regularization are combined to improve the temporal and spatial resolution of FMT visual reconstruction by introducing the weighting factor α and a half-quadratic splitting alternating optimization (HQSAO) iterative algorithm. By introducing an auxiliary variable, the HQSAO method breaks the sparse FMT reconstruction task into two subproblems that can be solved in turn: simple reconstruction and image denoising. The weight factor α (α>1) can increase the weight of nonconvex terms to further promote the sparsity of the algorithm. Importantly, this paper combines two different dominant fluorescent probes to achieve high-quality reconstruction of dual light sources. The performance of the proposed reconstruction strategy was evaluated by digital mouse and nude mouse single/dual light source models. The simulation results show that the HQSAO iterative algorithm can achieve more excellent positioning accuracy and morphology distribution in a shorter time. In vivo experiments also further prove that the HQSAO algorithm has advantages in light source information preservation and artifact suppression. In particular, the introduction of two main emission fluorescent probes makes it easy to separate and reconstruct the dual light sources. When it comes to localization and three-dimensional morphology, the results of the reconstruction are much better than those using a fluorescent probe, which further facilitates the clinical transformation of FMT.

Provident vehicle detection at night for advanced driver assistance systems

In recent years, computer vision algorithms have become more powerful, which enabled technologies such as autonomous driving to evolve rapidly. However, current algorithms mainly share one limitation: They rely on directly visible objects. This is a significant drawback compared to human behavior, where visual cues caused by objects (e. g., shadows) are already used intuitively to retrieve information or anticipate occurring objects. While driving at night, this performance deficit becomes even more obvious: Humans already process the light artifacts caused by the headlamps of oncoming vehicles to estimate where they appear, whereas current object detection systems require that the oncoming vehicle is directly visible before it can be detected. Based on previous work on this subject, in this paper, we present a complete system that can detect light artifacts caused by the headlights of oncoming vehicles so that it detects that a vehicle is approaching providently (denoted as provident vehicle detection). For that, an entire algorithm architecture is investigated, including the detection in the image space, the three-dimensional localization, and the tracking of light artifacts. To demonstrate the usefulness of such an algorithm, the proposed algorithm is deployed in a test vehicle to use the detected light artifacts to control the glare-free high beam system proactively (react before the oncoming vehicle is directly visible). Using this experimental setting, the provident vehicle detection system’s time benefit compared to an in-production computer vision system is quantified. Additionally, the glare-free high beam use case provides a real-time and real-world visualization interface of the detection results by considering the adaptive headlamps as projectors. With this investigation of provident vehicle detection, we want to put awareness on the unconventional sensing task of detecting objects providently (detection based on observable visual cues the objects cause before they are visible) and further close the performance gap between human behavior and computer vision algorithms to bring autonomous and automated driving a step forward.

Experiments on Deep Single-Image Portrait Relighting

This work describes deep single-image portrait relighting, a method to change the lighting of an image. The method is based on an hourglass convolutional neural network, which encodes the image and its estimated original lighting features, then replaces the lighting features with the target light. We highlight the overall good results produced by this method, as well as its limitations and the lighting artifacts that sometimes appear on relighted images. **This is an MLBriefs article, the source code has not been reviewed!**<br> **The original source code is [[available here|https://zhhoper.github.io/dpr.html]] (last checked 2022/10/10).**

Self-initialized active contours for microscopic cell image segmentation

Level set models are suitable for processing topological changes in different regions of images while performing segmentation. Active contour models require an empirical setting for initial parameters, which is tedious for the end-user. This study proposes an incremental level set model with the automatic initialization of contours based on local and global fitting energies that enable it to capture image regions containing intensity corruption or other light artifacts. The region-based area and the region-based length terms use signed pressure force (SPF) to strengthen the balloon force. SPF helps to achieve a smooth version of the gradient descent flow in terms of energy minimization. The proposed model is tested on multiple synthetic and real images. Our model has four advantages: first, there is no need for the end user to initialize the parameters; instead, the model is self-initialized. Second, it is more accurate than other methods. Third, it shows lower computational complexity. Fourth, it does not depend on the starting position of the contour. Finally, we evaluated the performance of our model on microscopic cell images (Coelho et al., in: 2009 IEEE international symposium on biomedical imaging: from nano to macro, IEEE, 2009) to confirm that its performance is superior to that of other state-of-the-art models.

Design, analysis and optimization of a waveguide-type near-eye display using a pin-mirror array and a concaved reflector

Waveguides have become one of the most promising optical combiners for see-through near-eye displays due to the thickness, weight, and transmittance. In this study, we propose a waveguide-type near-eye display using a pin-mirror array and a concaved reflector with a compact outlook, optimized image uniformity and stray light. Issues have been discussed in detail, which include field of view (FOV), eye-box, resolution, depth of field (DOF), display uniformity and stray light artifacts. It can be shown that the DOF can be extended (when compared with traditional waveguide-type near-eye displays) to alleviate the vergence-accommodation conflict (VAC) problem, and the uniformity & stray light can be improved with an optimal structure. Moreover, reflective surfaces have been introduced as the input and output coupling with a compact outlook, an easy-processing structure and the achromatic performance. A prototype based on the proposed method have been successfully developed, and virtual images with an extended DOF can be shown along with the real-world.

Visibility of the phantom array effect at different LED colour temperatures under high-frequency temporal light modulation

LEDs are widely used for both general and automotive lighting since their brightness can be easily regulated by controlling their on/off time using methods such as pulse width modulation (PWM). However, lighting control using PWM can cause temporal light artefacts, such as the phantom array effect, which affect human visual perception. In this study, we determined the influence of different colour temperatures on the visibility of the phantom array effect using five LEDs with different spectral distributions (red, green, blue, warm white and cool white) and frequencies of temporal modulation ranging from 1 kHz to 11 kHz. The threshold of the warm white LED was between that of the green and red LEDs, and threshold of the cool white LED was between that of the red and blue LEDs. The experimental results revealed a difference in the threshold frequency of the visibility of the phantom array effect, in accordance with the spectral distribution and the colour temperature of the light source.

How to test blindsight without light scatter artefacts?

light scatter artefacts are a methodological problem in testing residual visual capacities (RVCs), for instance blindsight, in patients with homonymous visual field defects (HVFDs). The term light scatter artefact describes the phenomenon that light from targets directed towards the HVFD can stray into the sighted visual field. This might enable an observer to respond correctly to information directed at her blind field despite the fact that she is unable to process that information in the blind field itself. In this manuscript, we present a review of the relevance of light scatter in visual neuroscience, discuss factors that influence the impact of light scatter and evaluate means to test for light scatter artefacts. Furthermore, we present findings from an empirical study that was aimed at developing tests for RVCs that are free of light scatter artefacts. Previous studies on light scatter only used small sample sizes and equipment that is no longer in use. Hence, their results cannot be generalized to future experiments making it necessary to run laborious light scatter tests for every new study on RVCs. To avoid this, we hereby start a pool of stimuli and paradigms which demonstrably do not elicit light scatter artefacts. To this end, we investigated 21 healthy young participants in three frequently used RVC-paradigms: (1) temporal 2AFC task, (2) movement direction discrimination, and (3) redundant target paradigm. For each paradigm, we applied the blind-spot method. But first, we had to establish that our testing paradigm was sufficiently sensitive to detect light scatter artefacts. For this, we used conditions that are known to produce strong light scatter and a paradigm that is very sensitive to such effects. Specifically, we presented white targets on a black background in a dark room. The stimuli were presented to observers’ blind spot. To check for light scatter artefacts, we used a target-detection task in a temporal 2AFC format. We obtained clear light scatter artefacts. Participants produced reliably above-chance detection performance under these conditions. The other two luminance conditions, measured in an illuminated room, did not produce light scatter artefacts. Accuracy in the temporal 2AFC task was at chance level for white targets on a grey background at the blind-spot position. Additionally, black targets on a grey background avoided light scatter artefacts in all three RVC-paradigms. In future, researchers can apply these stimulus and illumination conditions when using one of the three above paradigms in their studies. Using these conditions, they will be able to avoid light scatter artefacts without having to perform their own blind-spot tests.

Collaborative Three-Tier Architecture Noncontact Respiratory Rate Monitoring Using Target Tracking and False Peaks Eliminating Algorithms

Monitoring respiratory rate is crucial for helping identify respiratory disorders. Devices for conventional respiratory monitoring are inconvenient and scarcely available. Recent research has demonstrated the ability of non-contact technologies, such as photoplethysmography and infrared thermography, to gather respiratory signals from face and monitor breathing. However, current non-contact respiratory monitoring techniques have poor accuracy because they are sensitive to environmental influences like lighting and motion artifacts. Furthermore, frequent contact between users and the cloud in real-world medical application settings might cause service request delays and potentially the loss of personal data. We proposed a non-contact respiratory rate monitoring system with a cooperative three-layer design to increase the precision of respiratory monitoring and decrease data transmission latency. To reduce data transmission and network latency, our three-tier architecture layer-by-layer decomposes the computing tasks of respiration monitoring. Moreover, we improved the accuracy of respiratory monitoring by designing a target tracking algorithm and an algorithm for eliminating false peaks to extract high-quality respiratory signals. By gathering the data and choosing several regions of interest on face, we were able to extract the respiration signal and investigate how different regions affected the monitoring of respiration. The results of the experiment indicate that when the nasal region is used to extract the respiratory signal, it performs experimentally best. Our approach performs better than baseline approaches while transferring fewer data.

Evaluation of an algorithm for optical pulse detection in children for application to the Pepper robot

Abstract To engage in socio-emotional interactions, children with autism spectrum conditions (ASC) need support to understand and convey emotions. In our approach, a humanoid robot (Pepper, Softbanks Robotics) acts as a tutor for the child within autism care. The robot, equipped with multimodal sensor technology to acquire the emotional feedback of the child, stimulates the child to perform tasks, adapted to its current arousal state. By in-, or decreasing the difficulties of implemented training modules, the child can be given the appropriate task according to its emotional state. The child’s arousal is measured with different techniques implemented in and on the robot: emotion detection based on audio recordings of the speech signal and camera detected facial expressions, or heart rate. To this end, the remote Photoplethysmography (rPPG) signal from camera recordings of the subjects’ face is acquired. While its unintrusive measurement is an advantage, a major drawback for rPPG is its proneness to motion and light artefacts requiring de-noising steps. A wavelet transform based on log-Gabor wavelets and a filter bank with 32 filters was implemented. The signal was filtered with a prior filter and afterwards with a Markov chain in order to extract the underlying pulse rate. Within an initial study, five children were observed watching videos with different co-notated emotions. As reference for the heart rate (HR), a wristband (empatica E4) was used. The captured emotions of all subjects were annotated to identify low and high arousal parts and positive and negative emotions. Extracted HR from rPPG-data indicated a correlation with the annotated emotions.