Multiple Light Sources Research Articles

Precomputed low-frequency lighting in cinematic volume rendering.

Cinematic Rendering (CR) employs physical models such as ray tracing and global illumination to simulate real-world light phenomena, producing high-quality images with rich details. In the medical field, CR can significantly aid doctors in accurate diagnosis and preoperative planning. However, doctors require efficient real-time rendering when using CR, which presents a challenge due to the substantial computing resources demanded by CR's ray tracing and global illumination models. Precomputed lighting can enhance the efficiency of real-time rendering by freezing certain scene variables. Typically, precomputed methods freeze geometry and materials. However, since the physical rendering of medical images relies on volume data rendering of transfer functions, the CR algorithm cannot utilize precomputed methods directly. To improve the rendering efficiency of the CR algorithm, we propose a precomputed low-frequency lighting method. By simulating the lighting pattern of shadowless surgical lamps, we adopt a spherical distribution of multiple light sources, with each source capable of illuminating the entire volume of data. Under the influence of these large-area multi-light sources, the precomputed lighting adheres to physical principles, resulting in shadow-free and uniformly distributed illumination. We integrated this precomputed method into the ray-casting algorithm, creating an accelerated CR algorithm that achieves more than twice the rendering efficiency of traditional CR rendering.

Spectral Reflectance Estimation from Camera Response Using Local Optimal Dataset and Neural Networks.

In this study, a novel method is proposed to estimate surface-spectral reflectance from camera responses that combine model-based and training-based approaches. An imaging system is modeled using the spectral sensitivity functions of an RGB camera, spectral power distributions of multiple light sources, unknown surface-spectral reflectance, additive noise, and a gain parameter. The estimation procedure comprises two main stages: (1) selecting the local optimal reflectance dataset from a reflectance database and (2) determining the best estimate by applying a neural network to the local optimal dataset only. In stage (1), the camera responses are predicted for the respective reflectances in the database, and the optimal candidates are selected in the order of lowest prediction error. In stage (2), most reflectance training data are obtained by a convex linear combination of local optimal data using weighting coefficients based on random numbers. A feed-forward neural network with one hidden layer is used to map the observation space onto the spectral reflectance space. In addition, the reflectance estimation is repeated by generating multiple sets of random numbers, and the median of a set of estimated reflectances is determined as the final estimate of the reflectance. Experimental results show that the estimation accuracies exceed those of other methods.

Enhanced Scratch Detection for Textured Materials Based on Optimized Photometric Stereo Vision and Fast Fourier Transform–Gabor Filtering

In the process of scratch defect detection in textured materials, there are often problems of low efficiency in traditional manual detection, large errors in machine vision, and difficulty in distinguishing defective scratches from the background texture. In order to solve these problems, we developed an enhanced scratch defect detection system for textured materials based on optimized photometric stereo vision and FFT-Gabor filtering. We designed and optimized a novel hemispherical image acquisition device that allows for selective lighting angles. This device integrates images captured under multiple light sources to obtain richer surface gradient information for textured materials, overcoming issues caused by high reflections or dark shadows under a single light source angle. At the same time, for the textured material, scratches and a textured background are difficult to distinguish; therefore, we introduced a Gabor filter-based convolution kernel, leveraging the fast Fourier transform (FFT), to perform convolution operations and spatial domain phase subtraction. This process effectively enhances the defect information while suppressing the textured background. The effectiveness and superiority of the proposed method were validated through material applicability experiments and comparative method evaluations using a variety of textured material samples. The results demonstrated a stable scratch capture success rate of 100% and a recognition detection success rate of 98.43% ± 1.0%.

Analysis of progress in research on technology for the detection and removal of foreign fibers

We focus in this review on the pre-processing devices used, the cotton pipeline, the rejection system, the acquisition and processing of information from images of raw cotton, and measurements of the rate of dynamic flow of the cotton stream. The results show that raw cotton fluffs into a material with a more uniform thickness, and adequately separating the cotton bunch can improve the subsequent detection and removal of foreign fibers in it. Moreover, research that combines the structure of the cotton pipeline with the optimization of the structure of the nozzle plate is important for improving the rejection of foreign fibers in cotton. Furthermore, a combination of multiple light sources and arrays of charge-coupled device cameras can improve the quality of images of raw cotton, but such key parameters as the power and wavelength of the source of light need to be optimized. As any single algorithm for image segmentation and feature extraction struggles to adapt to the identification of different kinds of foreign fibers, it is important to explore a combination of algorithms to this end, and to develop new techniques of foreign fiber detection based on deep learning. Finally, the structure and parameters of processing of the system for the identification and removal of foreign fibers are important, including the relative distance between the sensor and the nozzle, the width of the detection channel, and the rate of flow of the cotton stream.

LCD-Based Angle-of-Arrival Estimation of Multiple Light Sources: Paving the Road to Multiuser VLC

LCD-Based Angle-of-Arrival Estimation of Multiple Light Sources: Paving the Road to Multiuser VLC

DDFL: Dual-Domain Feature Learning for nighttime semantic segmentation

Nighttime semantic segmentation has been playing a critical role in intelligent transportation, building safety and urban management. However, nighttime scenes present some challenges such as complex structures, multiple light sources, uneven lighting and blurry image noise, which severely degrade the segmentation quality of nighttime images. To address these challenges, we propose a Dual-Domain Feature Learning (DDFL) model for nighttime semantic segmentation. Our approach introduces three innovative ideas. First, we establish an exposure correction module to address the impact of lighting differences on the model’s learning, so as to maximally restore the pixel distortion and blurry areas caused by artificial light in nighttime scenes. Second, we incorporate frequency domain information into the nighttime segmentation task to give the model stronger discrimination ability. Finally, we introduce a dual-domain fusion module to complement the information of learning from the spatial and frequency domains in a cross-fusion manner, enabling the network to perceive semantic information while preserving details. The proposed model was experimentally tested on the Nightcity, Nightcity+ and BDD100k datasets. Our results demonstrate that our model outperforms mainstream models, achieving mIoU scores of 56.73%, 57.41% and 28.97%, respectively, under different lighting, image exposure levels, and resolutions. These results show that our model is capable of segmenting nighttime scenes efficiently in a high-quality way.

Wide-field color imaging through multimode fiber with single wavelength illumination: plug-and-play approach.

Multimode fiber (MMF) is extensively studied for its ability to transmit light modes in parallel, potentially minimizing optical fiber size in imaging. However, current research predominantly focuses on grayscale imaging, with limited attention to color studies. Existing colorization methods often involve costly white light lasers or multiple light sources, increasing optical system expenses and space. To achieve wide-field color images with typical monochromatic illumination MMF imaging system, we proposed a data-driven "colorization" approach and a neural network called SpeckleColorNet, merging U-Net and conditional GAN (cGAN) architectures, trained by a combined loss function. This approach, demonstrated on a 2-meter MMF system with single-wavelength illumination and the Peripheral Blood Cell (PBC) dataset, outperforms grayscale imaging and alternative colorization methods in readability, definition, detail, and accuracy. Our method aims to integrate MMF into clinical medicine and industrial monitoring, offering cost-effective high-fidelity color imaging. It serves as a plug-and-play replacement for conventional grayscale algorithms in MMF systems, eliminating the need for additional hardware.

Optical Filter Design for Multi-Color VLC in Reflective Environments with Multiple Lighting Sources

Optical Filter Design for Multi-Color VLC in Reflective Environments with Multiple Lighting Sources

Measurement of Vertical Dispersion and Pollution Impact of Artificial Light at Night in Urban Environment

Excessive artificial light disrupts our lives and poses health risks. In mixed-use urban areas, commercial lighting conflicts with residential activities. Vertical towers exacerbate the issue, as lower-level lighting affects higher-level occupants, and more research is needed to understand the vertical dispersion of light and its impact on sleep disturbance. This work offers a simple mathematical model for height dependence of illuminance in an urban building. It correlates basic measurements to reduce the values of the Exponent (n) and Linear (Coeff2) coefficients in a standard power-law curve. The collection of only a few data points can help to investigate the extent of the lighting spread at various floors of the building. Even with the complex lighting environment in Hong Kong, the methodology is exercised in 8 sample buildings from 4 different neighbourhoods to show the insights from the testing results. The heights of the studied buildings range from 3 to 18 stories, and they are for residential and mixed use. While the average measured illuminance at the street level was between 37 lx and 303 lx for the 4 neighbourhoods, the average illuminance across building heights was 14 lx to 247 lx. The existence of multiple light sources on building facades disrupts the simple inverse-square relationship with a single light source. The power n values range from approximately -1.7 to -0.8, while the Coeff2 values range from 61 to 7603 for the measured buildings. These variations indicate deviations from the assumption of a single source and suggest higher luminance and the presence of light sources at higher heights. With the simple inverse-square relationship, the proposed methodology can help to determine the height where the recommended limit can be met given the light situation at the street level.

Lightbox: Sensor Attack Detection for Photoelectric Sensors via Spectrum Fingerprinting

Photoelectric sensors are utilized in a range of safety-critical applications, such as medical devices and autonomous vehicles. However, the public exposure of the input channel of a photoelectric sensor makes it vulnerable to malicious inputs. Several studies have suggested possible attacks on photoelectric sensors by injecting malicious signals. While a few defense techniques have been proposed against such attacks, they could be either bypassed or used for limited purposes. In this study, we propose Lightbox, a novel defense system to detect sensor attacks on photoelectric sensors based on signal fingerprinting. Lightbox uses the spectrum of the received light as a feature to distinguish the attacker’s malicious signals from the authentic signal, which is a signal from the sensor’s light source. We evaluated Lightbox against (1) a saturation attacker, (2) a simple spoofing attacker, and (3) a sophisticated attacker who is aware of Lightbox and can combine multiple light sources to mimic the authentic light source. Lightbox achieved the overall accuracy over 99% for the saturation attacker and simple spoofing attacker, and robustness against a sophisticated attacker. We also evaluated Lightbox considering various environments such as transmission medium, background noise, and input waveform. Finally, we demonstrate the practicality of Lightbox with experiments using a single-board computer after further reducing the training time.

Experimental evaluation of poly methyl methacrylate-acrylonitrile butadiene styrene transmission welding using mold-integrated simultaneous laser welding technology

Automotive lamps have not only functional roles but also highly esthetic purposes in the design of a car. As such, they use complex three-dimensional shapes to implement various designs. The main manufacturing challenge comes from the plastic bonding process of the complex components, which currently is done by thermal bonding, ultrasonic bonding, and laser welding. Laser welding processes with a narrow joint area are preferred since they require minimal joint area and produce no burr. In this study, an optimization study for simultaneous bonding of lamps is carried out using multiple light sources generated by connecting specially manufactured bundle optical fibers with a diode laser source. The diode laser beams with a wavelength of 915 nm and a power of 80 W, each, were simultaneously delivered through a 30-optical fibers bundle. The fibers were integrated within the mold that holds the lamp achieving transmission welding through the overlapped upper transparent polymer PMMA (IF850) and the lower nontransparent polymer ABS (HL121H). The process parameters investigated were the laser power, duration time, waveguide gap, and clamping pressure. We present optimized process parameters that achieved no pores and relatively uniform melting. In the shear test, the average load was approximately 1300 N, and the base sheet fractures along the welding joints were observed.

Indoor bifacial perovskite photovoltaics: Efficient energy harvesting from artificial light sources

Emerging bifacial photovoltaics (BPVs) have received tremendous attention due to their high efficacy and economical cost by harvesting more light energy in outdoor conditions. Although, the performance of BPVs in outdoor conditions is severely limited by the albedo light (light reflected from the surface, soil, clouds, etc.). Conversely, BPVs could also be utilize to efficiently harvest energy from indoor environments such as offices, homes, large gathering halls, stations, and more, where multiple artificial lighting sources are employed. In this work, we have designed an efficient indoor bifacial perovskite photovoltaics (i-BPPVs) with the capability of harvesting maximum light from both top and bottom sides. The i-BPPVs were designed and fabricated in a stack of organic–inorganic hybrid perovskite material amid a transparent bottom electrode (ITO), and top (Au/ITO) electrode. The fabricated i-BPPVs exhibited an efficiency of 30.3%, short circuit current density (JSC) of 148.3 µA cm−2, open circuit voltage (VOC) of 0.93 V, and fill factor (FF) of 71.7% when artificial LED light source of 1000 lx is exposed from the top side, whereas an efficiency of 22.1%, JSC of 116.2 µA cm−2, VOC of 0.89 V, and FF of 69.4% have been obtained from the bottom side. The champion bifacial i-BPPVs display an excellent bifaciality factor (Φ) of 0.73 and demonstrated superior operational stability when subjected to continuous illumination. Moreover, this work of designing i-BPPVs will be a pivotal step towards advancing cost-effective and efficient technology for harvesting more energy from artificial indoor light sources.

On-chip optical matrix-vector multiplier based on mode division multiplexing

A matrix-vector multiplication (MVM) optical signal processor based on mode division multiplexing (MDM) was proposed and demonstrated in the current work, which is composed of a mode multiplexer, a multimode beam splitter, a mode demultiplexer, a modulator array and combiners. In addition, the characteristics of MDM obviate the need for multiple wavelengths and therefore multiple laser light sources are unneeded, which greatly reduces the complexity and cost. A 4 × 4 MDM-MVM was realized on a standard silicon-on-insulator (SOI) platform. Combined with the off-chip light source and photodetectors (PDs), 4-level modulation has been demonstrated, and each level of the output signal could represent 2 bits of information.

Collimated Whole Volume Light Scattering in Homogeneous Finite Media.

Crepuscular rays form when light encounters an optically thick or opaque medium which masks out portions of the visible scene. Real-time applications commonly estimate this phenomena by connecting paths between light sources and the camera after a single scattering event. We provide a set of algorithms for solving integration and sampling of single-scattered collimated light in a box-shaped medium and show how they extend to multiple scattering and convex media. First, a method for exactly integrating the unoccluded single scattering in rectilinear box-shaped medium is proposed and paired with a ratio estimator and moment-based approximation. Compared to previous methods, it requires only a single sample in unoccluded areas to compute the whole integral solution and provides greater convergence in the rest of the scene. Second, we derive an importance sampling scheme accounting for the entire geometry of the medium. This sampling strategy is then incorporated in an optimized Monte Carlo integration. The resulting integration scheme yields visible noise reduction and it is directly applicable to indoor scene rendering in room-scale interactive experiences. Furthermore, it extends to multiple light sources and achieves superior converge compared to independent sampling with existing algorithms. We validate our techniques against previous methods based on ray marching and distance sampling to prove their superior noise reduction capability.

ALIVE: Adaptive-Chromaticity for Interactive Low-light Image and Video Enhancement

Ray tracing remains of interest to Computer Graphics community with its elegant framing of how light interacts with objects, being able to easily support multiple light sources, and simple framework of merging synthetic and real cameras. Recent trends to provide implementations at the chip-level means raytracing’s constant quest of realism would propel its usage in real-time applications. AR/VR, Animations, 3DGames Industry, 3D-large scale simulations, and future social computing platforms are just a few examples of possible major impact. Raytracing is also appealing to HCI community because raytracing extends well along the 3D-space and time, seamlessly blending both synthetic and real cameras at multiple scales to support storytelling. This presentation will include a few milestones from my work such as the Slicing Extent technique and Directed Safe Zones. Our recent applications of applying machine learning techniques creating novel synthetic views, which could also provide a future doorway to handle dynamic scenes with more compute power as needed, will also be presented. It is once again renaissance for ray tracing which for last 50+ years has remained the most elegant technique for modeling light phenomena in virtual worlds at whatever scale compute power could support.

Numerical and experimental investigations on the propagation property of a mid-infrared 7 × 1 multimode fiber combiner.

Mid-infrared fiber combiners have great potential in power and spectral combination. However, studies on mid-infrared transmission optical field distributions using these combiners are limited. In this study, we designed and fabricated a 7 × 1 multimode fiber combiner based on sulfur-based glass fibers and observed approximately 80% per-port transmission efficiency at 4.778 µm wavelength. We investigated the propagation properties of the prepared combiners and explored the effects of transmission wavelength, output fiber length, and fusion deviation on the transmitted optical field and beam quality factor M2. Additionally, we assessed the effect of coupling on the excitation mode and spectral combination of the mid-infrared fiber combiner for multiple light sources. Our results provide an in-depth understanding of the propagation properties of the mid-infrared multimode fiber combiners, which may find applications in high-beam-quality laser devices.

Shadow Effect of Human Obstacles on Indoor Visible Light Communication System with Multiple Light Sources

When the direct visible-light channel is affected by people walking or other obstacles, the shadow effect formed in the receiver space affects communication performance and can even lead to communication interruption. In this paper, two numerical methods for calculating the shadow area of the human body were proposed for an indoor multi-light communication system. The influence of shadows on system performance was analyzed using the mean square errors of illuminance and signal-to-noise ratio, as well as the interrupt probability, as parameters. The results showed that shadows had a great influence on the performance of the visible-light communication system. When the number of light sources was fixed, the shadow effect could be effectively reduced by optimizing the layout of the light sources. These research results can provide a theoretical basis for improving the stability of visible-light communication systems.

Evaluation of disinfection performance of a multiple wavelength EBE-UV light source and comparison with UV-LEDs

A new ultraviolet (UV) light source EBE-UV (electron beam excitation-UV) system was established in this study, which can emit UV light at four wavelengths (233/243/260/270 nm) simultaneously. The EBE-UV lamp emits deep ultraviolet light by electronically exciting the ultraviolet material YPO4:Pr3+. It has the advantage of being mercury-free and environmentally friendly, as well as higher photoelectric conversion efficiency. To evaluate the germicidal performance of the EBE-UV lamp, Gram-negative bacteria, Gram-positive bacteria, and fungi were selected for evaluation. The bactericidal efficiency of the EBE-UV lamp was tested and compared to the universal 255 nm and 275 nm UV-LEDs. As a result, the bactericidal effect of EBE-UV light was more effective than of single-wavelength UV-LEDs, especially against fungi. The level of Reactive Oxygen Species in the cells of the strain was increased to varying degrees by UV irradiation. There is a general weakening of energy metabolism, and DNA was damaged and fragmented. However, almost no significant cell membrane damage was found in this study. The EBE-UV light will show great potential due to its disinfection effect and device performance.

Reconstruction based on adaptive group least angle regression for fluorescence molecular tomography.

Fluorescence molecular tomography can combine two-dimensional fluorescence imaging with anatomical information to reconstruct three-dimensional images of tumors. Reconstruction based on traditional regularization with tumor sparsity priors does not take into account that tumor cells form clusters, so it performs poorly when multiple light sources are used. Here we describe reconstruction based on an "adaptive group least angle regression elastic net" (AGLEN) method, in which local spatial structure correlation and group sparsity are integrated with elastic net regularization, followed by least angle regression. The AGLEN method works iteratively using the residual vector and a median smoothing strategy in order to adaptively obtain a robust local optimum. The method was verified using numerical simulations as well as imaging of mice bearing liver or melanoma tumors. AGLEN reconstruction performed better than state-of-the-art methods with different sizes of light sources at different distances from the sample and in the presence of Gaussian noise at 5-25%. In addition, AGLEN-based reconstruction accurately imaged tumor expression of cell death ligand-1, which can guide immunotherapy.

An evacuation model considering the phototactic behavior of panic pedestrians under limited visual field

In the emergency evacuation process, pedestrians affected by their panic will have evacuation behavior that rushes toward the light. To study the impact of panic pedestrian phototactic behavior on the evacuation process, a multi-model coupled cellular automata model is proposed. First, a heterogeneous model of emotional contagion based on the OCEAN model and the SIS model is established, which considers the influence of individual characteristics such as personality, gender, and age on emotional contagion, and the increase and decay of pedestrian emotion are also correlated with their location. Next, the “guidance field”, “orienteering field”, “herding field” and “phototactic field” are introduced to build an extended cellular automata model, pedestrians in different areas have different movement modes, and pedestrians with different emotional states in the same area also differ. Finally, the phototactic behavior of pedestrians in evacuation is reproduced by simulation, and the effects of factors such as emotional threshold, information transfer, visual field distance, light source position, and multiple light sources interference on the evacuation process are discussed. The results show that whether phototactic behavior is favorable or unfavorable to evacuation depends on the position of the light source. When the light source is located at the exit can guide pedestrians to escape, while located in other places will trigger local congestion. Increases in the emotional threshold, information transfer, and visual field distance can effectively mitigate the adverse effects of phototactic behavior. Additionally, the light sources in other positions will cause some interference with the light sources at the exit when multiple light sources exist, prolonging the evacuation time. Our research can provide some guidance for designing building structures and developing evacuation strategies in emergency situations.