Wide Range Of Lighting Conditions Research Articles

High‐Bandgap Perovskites for Efficient Indoor Light Harvesting

The use of metal‐halide perovskites in photovoltaic applications has become increasingly attractive due to their low‐temperature manufacturing processes and long charge‐carrier lifetimes. High‐bandgap perovskite solar cells have potential for indoor applications due to their efficient absorption of the spectrum of light‐emitting diodes (LEDs). This study investigates the performance of high‐bandgap perovskite solar cells under a wide range of lighting conditions, including a commercially available white LED lamp with a 5–40 000 lx illuminance range and a standard 1 sun reference. The performance of CH3NH3PbI3‐based perovskite solar cells to CH3NH3Pb(I0.8,Br0.2)3 solar cells with varying electron transport layers (ETL), including PCBM, PCBM:CMC, and CMC:ICBA fullerene combinations, is compared. Because the spectral response of perovskite solar cells covers the white LED spectrum very well, the major performance difference is related to the open‐circuit voltage and fill factor. The cells with the CH3NH3Pb(I0.8,Br0.2)3 absorber layer and the CMC:ICBA ETL demonstrate superior open‐circuit voltage and therefore a high efficiency above 29% at 200–500 lx, typical for indoor lighting.

Method for removing haze from images, captured under a wide range of lighting conditions

The presence of haze on images degrades the quality of perception and automatic analysis of scenes. One of the most popular methods of haze removal is the dark channel prior method, which is based on the Koschmieder atmospheric scattering model. However, its underlying assumptions are not met for nighttime, since localized light sources make a significant, if not the main, contribution to lighting. We propose here to use the degree of belonging of an image element to a localized light source, determined based on a one-class classifier, as a value that characterizes the confidence of the corresponding element of the estimated transmission map during its rectifi-cation based on the gamma-normal model, which makes it possible to increase the accuracy of dehazing when processing images, captured in low-light or nighttime conditions.

Effect of the Light Environment on Image-Based SPAD Value Prediction of Radish Leaves

This study aims to clarify the influence of photographic environments under different light sources on image-based SPAD value prediction. The input variables for the SPAD value prediction using Random Forests, XGBoost, and LightGBM were RGB values, HSL values, HSV values, light color temperature (LCT), and illuminance (ILL). Model performance was assessed using Pearson’s correlation coefficient (COR), Nash–Sutcliffe efficiency (NSE), and root mean squared error (RMSE). Especially, SPAD value prediction with Random Forests resulted in high accuracy in a stable light environment; CORRGB+ILL+LCT and CORHSL+ILL+LCT were 0.929 and 0.922, respectively. Image-based SPAD value prediction was effective under halogen light with a similar color temperature at dusk; CORRGB+ILL and CORHSL+ILL were 0.895 and 0.876, respectively. The HSL value under LED could be used to predict the SPAD value with high accuracy in all performance measures. The results supported the applicability of SPAD value prediction using Random Forests under a wide range of lighting conditions, such as dusk, by training a model based on data collected under different illuminance conditions in various light sources. Further studies are required to examine this method under outdoor conditions in spatiotemporally dynamic light environments.

Light-dependent changes in the outer plexiform layer of the mouse retina.

The ability of the visual system to relay meaningful information over a wide range of lighting conditions is critical to functional vision, and relies on mechanisms of adaptation within the retina that adjust sensitivity and gain as ambient light changes. Photoreceptor synapses represent the first stage of image processing in the visual system, thus activity-driven changes at this site are a potentially powerful, yet under-studied means of adaptation. To gain insight into these mechanisms, the abundance and distribution of key synaptic proteins involved in photoreceptor to ON-bipolar cell transmission were compared between light-adapted mice and mice subjected to prolonged dark exposure (72 hours), by immunofluorescence confocal microscopy and immunoblotting. We also tested the effects on protein abundance and distribution of 0.5-4 hours of light exposure following prolonged darkness. Proteins examined included the synaptic ribbon protein, ribeye, and components of the ON-bipolar cell signal transduction pathway (mGluR6, TRPM1, RGS11, GPR179, Goα). The results indicate a reduction in immunoreactivity for ribeye, TRPM1, mGluR6, and RGS11 following prolonged dark exposure compared to the light-adapted state, but a rapid restoration of the light-adapted pattern upon light exposure. Electron microscopy revealed similar ultrastructure of light-adapted and dark-adapted photoreceptor terminals, with the exception of electron dense vesicles in dark-adapted but not light-adapted ON-bipolar cell dendrites. To assess synaptic transmission from photoreceptors to ON-bipolar cells, we recorded electroretinograms after different dark exposure times (2, 16, 24, 48, 72 hours) and measured the b-wave to a-wave ratios. Consistent with the reduction in synaptic proteins, the b/a ratios were smaller following prolonged dark exposure (48-72 hours) compared to 16 hours dark exposure (13-21%, depending on flash intensity). Overall, the results provide evidence of light/dark-dependent plasticity in photoreceptor synapses at the biochemical, morphological, and physiological levels.

Detachable image decomposition and illumination mapping search for low-light image enhancement

Low-light image enhancement is a fundamental low-level computer vision task that has a wide range of applications, such as night monitoring, all-weather automatic driving, back-light imaging, and so on. In this paper, we propose a novel four-stage detachable framework for low-light image enhancement, where each module can be trained and fine-tuned separately. More importantly, the proposed framework can effectively be adapted to unseen datasets. In the first stage, we propose an image decomposition network that can extract a pair of a reflectance map and an illumination map given an image with arbitrary lighting conditions. The proposed loss function ensures that images of the same scene with different lighting conditions share the same reflectance map. Instead of using gamma correction, we establish an automatic searching scheme in the second stage to find an explicit mapping relationship between illumination maps in different lighting conditions. In the third stage, we use an efficient and effective unsupervised training method to find the best parameter set for the mapping. Finally, a normal-light image is obtained by composing together its reflectance map and transformed illumination map. A series of experiments are conducted on several popular datasets, and the results demonstrate the superiority of our proposed method on unseen datasets. Our framework surpasses other state-of-the-art methods and is applicable to enhance images in a wide range of lighting conditions.

Facial Feature Extraction Using a Symmetric Inline Matrix-LBP Variant for Emotion Recognition.

With a large number of Local Binary Patterns (LBP) variants being currently used today, the significant and importance of visual descriptors in computer vision applications are prominent. This paper presents a novel visual descriptor, i.e., SIM-LBP. It employs a new matrix technique called the Symmetric Inline Matrix generator method, which acts as a new variant of LBP. The key feature that separates our variant from existing counterparts is that our variant is very efficient in extracting facial expression features like eyes, eye brows, nose and mouth in a wide range of lighting conditions. For testing our model, we applied SIM-LBP on the JAFFE dataset to convert all the images to its corresponding SIM-LBP transformed variant. These transformed images are then used to train a Convolution Neural Network (CNN) based deep learning model for facial expressions recognition (FER). Several performance evaluation metrics, i.e., recognition accuracy rate, precision, recall, and F1-score, were used to test mode efficiency in comparison with those using the traditional LBP descriptor and other LBP variants. Our model outperformed in all four matrices with the proposed SIM-LBP transformation on the input images against those of baseline methods. In comparison analysis with the other state-of-the-art methods, it shows the usefulness of the proposed SIM-LBP model. Our proposed SIM-LBP variant transformation can also be applied on facial images to identify a person's mental states and predict mood variations.

A stochastic oscillator model simulates the entrainment of vertebrate cellular clocks by light

The circadian clock is a cellular mechanism that synchronizes various biological processes with respect to the time of the day. While much progress has been made characterizing the molecular mechanisms underlying this clock, it is less clear how external light cues influence the dynamics of the core clock mechanism and thereby entrain it with the light–dark cycle. Zebrafish-derived cell cultures possess clocks that are directly light-entrainable, thus providing an attractive laboratory model for circadian entrainment. Here, we have developed a stochastic oscillator model of the zebrafish circadian clock, which accounts for the core clock negative feedback loop, light input, and the proliferation of single-cell oscillator noise into population-level luminescence recordings. The model accurately predicts the entrainment dynamics observed in bioluminescent clock reporter assays upon exposure to a wide range of lighting conditions. Furthermore, we have applied the model to obtain refitted parameter sets for cell cultures exposed to a variety of pharmacological treatments and predict changes in single-cell oscillator parameters. Our work paves the way for model-based, large-scale screens for genetic or pharmacologically-induced modifications to the entrainment of circadian clock function.

Calibration of Visible Light Positioning Systems with a Mobile Robot

Most indoor positioning systems require calibration before use. Fingerprinting requires the construction of a signal strength map, while ranging systems need the coordinates of the beacons. Calibration approaches exist for positioning systems that use Wi-Fi, radio frequency identification or ultrawideband. However, few examples are available for the calibration of visible light positioning systems. Most works focused on obtaining the channel model parameters or performed a calibration based on known receiver locations. In this paper, we describe an improved procedure that uses a mobile robot for data collection and is able to obtain a map of the environment with the beacon locations and their identities. Compared to previous work, the error is almost halved. Additionally, this approach does not require prior knowledge of the number of light sources or the receiver location. We demonstrate that the system performs well under a wide range of lighting conditions and investigate the influence of parameters such as the robot trajectory, camera resolution and field of view. Finally, we also close the loop between calibration and positioning and show that our approach has similar or better accuracy than manual calibration.

Ex vivo electroretinograms made easy: performing ERGs using 3D printed components.

Rod and cone photoreceptors convert light into electrochemical signals that are transferred to second order cells, initiating image-forming visual processing. Electroretinograms (ERGs) can detect the associated light-induced extracellular transretinal events, allowing for physiological assessment of cellular activity from morphologically intact retinas. We outline a method for economically configuring a traditional patch-clamp rig for performing high signal-to-noise ex vivo ERGs. We accomplish this by incorporating various 3D printed components and by modifying existing light pathways in a typical patch-clamp rig. This methodology provides an additional set of tools to labs interested in studying the physiological function of neuronal populations in isolated retinal tissue. Rod and cone photoreceptors of the retina are responsible for the initial stages in vision and convey sensory information regarding our visual world across a wide range of lighting conditions. These photoreceptors hyperpolarize in the presence of light and subsequently transmit signals to second-order bipolar and horizontal cells. The electrical components of these events are experimentally detectable, and in conjunction with pharmacological agents, can be further separated into their respective cellular contributions using electroretinograms (ERGs). Extracellular activity from populations of rods and cones generate the negative-going a-wave, while ON-bipolar cells generate positive-going b-waves. ERGs can be performed in vivo or alternatively using an ex vivo configuration, where retinas are isolated and transretinal photovoltages are recorded at high signal-to-noise ratios. However, most ERG set-ups require their own unique set of tools. We demonstrate how, at low cost, to reconfigure a typical patch-clamp rig for ERG recordings. The bulk of these modifications require implementation of various 3D printed components, which can alternatively aid in generating a stand-alone ERG set-up without a patch-rig. Further, we discuss how to configure an ERG system without a patch-clamp rig. Compared to in vivo ERGs, these are superior when measuring small responses, such as those that are cone-evoked or those from immature mouse retinae. This recording configuration provides high signal-to-noise detection of a-waves (300-600 µV) and b-waves (1-3 mV), and is ultimately capable of discerning small (1-2 µV) photovoltages from noise. These quick and economical modifications allow researchers to equip their technical arsenal with an interchangeable patch-clamp/ERG system.

A model of lightness perception guided by probabilistic assumptions about lighting and reflectance.

Lightness perception is the ability to perceive black, white, and gray surface colors in a wide range of lighting conditions and contexts. This ability is fundamental for any biological or artificial visual system, but it poses a difficult computational problem, and how the human visual system computes lightness is not well understood. Here I show that several key phenomena in lightness perception can be explained by a probabilistic graphical model that makes a few simple assumptions about local patterns of lighting and reflectance, and infers globally optimal interpretations of stimulus images. Like human observers, the model exhibits partial lightness constancy, codetermination, contrast, glow, and articulation effects. It also arrives at human-like interpretations of strong lightness illusions that have challenged previous models. The model's assumptions are reasonable and generic, including, for example, that lighting intensity spans a much wider range than surface reflectance and that shadow boundaries tend to be straighter than reflectance edges. Thus, a probabilistic model based on simple assumptions about lighting and reflectance gives a good computational account of lightness perception over a wide range of conditions. This work also shows how graphical models can be extended to develop more powerful models of constancy that incorporate features such color and depth.

What image features guide lightness perception?

Lightness constancy is the ability to perceive black and white surface colors under a wide range of lighting conditions. This fundamental visual ability is not well understood, and current theories differ greatly on what image features are important for lightness perception. Here we measured classification images for human observers and four models of lightness perception to determine which image regions influenced lightness judgments. The models were a high-pass-filter model, an oriented difference-of-Gaussians model, an anchoring model, and an atmospheric-link-function model. Human and model observers viewed three variants of the argyle illusion (Adelson, 1993) and judged which of two test patches appeared lighter. Classification images showed that human lightness judgments were based on local, anisotropic stimulus regions that were bounded by regions of uniform lighting. The atmospheric-link-function and anchoring models predicted the lightness illusion perceived by human observers, but the high-pass-filter and oriented-difference-of-Gaussians models did not. Furthermore, all four models produced classification images that were qualitatively different from those of human observers, meaning that the model lightness judgments were guided by different image regions than human lightness judgments. These experiments provide a new test of models of lightness perception, and show that human observers' lightness computations can be highly local, as in low-level models, and nevertheless depend strongly on lighting boundaries, as suggested by midlevel models.

HCN1 Channels Enhance Rod System Responsivity in the Retina under Conditions of Light Exposure.

PurposeVision originates in rods and cones at the outer retina. Already at these early stages, diverse processing schemes shape and enhance image information to permit perception over a wide range of lighting conditions. In this work, we address the role of hyperpolarization-activated and cyclic nucleotide-gated channels 1 (HCN1) in rod photoreceptors for the enhancement of rod system responsivity under conditions of light exposure.MethodsTo isolate HCN1 channel actions in rod system responses, we generated double mutant mice by crossbreeding Hcn1-/- mice with Cnga3-/- mice in which cones are non-functional. Retinal function in the resulting Hcn1-/- Cnga3-/- animals was followed by means of electroretinography (ERG) up to the age of four month. Retinal imaging via scanning laser ophthalmoscopy (SLO) and optical coherence tomography (OCT) was also performed to exclude potential morphological alterations.ResultsThis study on Hcn1-/- Cnga3-/- mutant mice complements our previous work on HCN1 channel function in the retina. We show here in a functional rod-only setting that rod responses following bright light exposure terminate without the counteraction of HCN channels much later than normal. The resulting sustained signal elevation does saturate the retinal network due to an intensity-dependent reduction in the dynamic range. In addition, the lack of rapid adaptational feedback modulation of rod photoreceptor output via HCN1 in this double mutant limits the ability to follow repetitive (flicker) stimuli, particularly under mesopic conditions.ConclusionsThis work corroborates the hypothesis that, in the absence of HCN1-mediated feedback, the amplitude of rod signals remains at high levels for a prolonged period of time, leading to saturation of the retinal pathways. Our results demonstrate the importance of HCN1 channels for regular vision.

P‐37: Readability of Displays in Bright Outdoor Surroundings

AbstractReadability of displays in bright outdoor surroundings is a problem for many types of visual displays. The wide range of lighting conditions that these displays should be able to operate in, makes the design of the test set‐up very challenging. Mobile displays of today usually have LCDs with LED backlight or OLEDs, which gives the possibility to control the light levels from very low luminance or even zero luminance to very high luminance levels with good contrast and color rendering. There are many displays that can show high luminance (>1000 cd/m2) and with that are considered or claimed to have daylight or sunlight readability. However, these statements are rarely supported by scientific tests with test subjects. This paper will discuss and analyze the conditions for performing such experiments. Experimental results that the visual acuity is negatively affected by strong illuminance are presented.

Using a depth-sensing infrared camera system to access and manipulate medical imaging from within the sterile operating field

As surgical procedures become increasingly dependent on equipment and imaging, the need for sterile members of the surgical team to have unimpeded access to the nonsterile technology in their operating room (OR) is of growing importance. To our knowledge, our team is the first to use an inexpensive infrared depthsensing camera (a component of the Microsoft Kinect) and software developed inhouse to give surgeons a touchless, gestural interface with which to navigate their picture archiving and communication systems intraoperatively. The system was designed and developed with feedback from surgeons and OR personnel and with consideration of the principles of aseptic technique and gestural controls in mind. Simulation was used for basic validation before trialing in a pilot series of 6 hepatobiliary-pancreatic surgeries. The interface was used extensively in 2 laparoscopic and 4 open procedures. Surgeons primarily used the system for anatomic correlation, real-time comparison of intraoperative ultrasound with preoperative computed tomography and magnetic resonance imaging scans and for teaching residents and fellows. The system worked well in a wide range of lighting conditions and procedures. It led to a perceived increase in the use of intraoperative image consultation. Further research should be focused on investigating the usefulness of touchless gestural interfaces in different types of surgical procedures and its effects on operative time.

Retinas of the Diurnal RodentArvicanthis ansorgeiAre Highly Resistant to Experimentally Induced Stress and Degeneration

Environmentally induced stress plays a significant role in retinal degeneration and blindness both in animals and in humans. Among such sources of stress, phototoxicity is well studied and has been shown to lead to photoreceptor-specific loss in a number of species. However, the vast majority of studies have been conducted in nocturnal, albino rod-dominant rat and mouse strains, and the pertinence of such findings to human pathology and cone loss is debatable. The authors examined retinal vulnerability to damage in the diurnal murid rodent Arvicanthis ansorgei, a pigmented species with a large number of cones. The authors used established protocols for exposing animals to a wide range of lighting conditions (variable intensity, duration, spectrum, previous light history, and time of exposure) and injecting N-methyl-N-nitrosourea (MNU); each procedure is reported to produce rapid and complete photoreceptor-specific damage. Animals then underwent electroretinography to record rod and cone function and were subsequently euthanized and used for immunohistochemical analysis of retinal structure and quantification of free fatty acids. These standard regimens produced no detectable detrimental effects on A. ansorgei retinal phenotype, function, or structure. Partial retinal damage in A. ansorgei was induced by very intense blue light or elevated doses of MNU. This resistance was not attributable to differences in lipid composition (specifically, docosahexaenoic acid) between A. ansorgei and susceptible strains of mice and rats. The retina of this species exhibits exceptionally high resistance to damage from light and toxins such as MNU.

Modulation of rod photoreceptor output by HCN1 channels is essential for regular mesopic cone vision

Retinal photoreceptors permit visual perception over a wide range of lighting conditions. Rods work best in dim, and cones in bright environments, with considerable functional overlap at intermediate (mesopic) light levels. At many sites in the outer and inner retina where rod and cone signals interact, gap junctions, particularly those containing Connexin36, have been identified. However, little is known about the dynamic processes associated with the convergence of rod and cone system signals into ON- and OFF-pathways. Here we show that proper cone vision under mesopic conditions requires rapid adaptational feedback modulation of rod output via hyperpolarization-activated and cyclic nucleotide-gated channels 1. When these channels are absent, sustained rod responses following bright light exposure saturate the retinal network, resulting in a loss of downstream cone signalling. By specific genetic and pharmacological ablation of key signal processing components, regular cone signalling can be restored, thereby identifying the sites involved in functional rod-cone interactions.

A NOVEL METHOD FOR HORIZONTAL EYE LINE DETECTION UNDER VARIOUS ENVIRONMENTS

The eye line is defined to be a horizontal line passing the two eyes of a human face. It can be used to help locate the true positions of eyes and face. In this paper, we propose a method to extract the horizontal eye line of a face under various environments. Based on the facts that the eye color is very different from skin color and the gray level variance of an eye is high, some eye-like regions are first located. Then the horizontal eye line is extracted based on the located eye-like regions and some geometric properties in a face. Experimental results are given to show that the proposed method is robust under a wide range of lighting conditions, different poses and races. The detection rate for HHI face database is 95.63%. For Champion face database, the detection rate is 94.27%.

Novel face-detection method under various environments

We propose a method to detect a face with different poses under various environments. On the basis of skin color information, skin regions are first extracted from an input image. Next, the shoulder part is cut out by using shape information and the head part is then identified as a face candidate. For a face candidate, a set of geometric features is applied to determine if it is a profile face. If not, then a set of eyelike rectangles extracted from the face candidate and the lighting distribution are used to determine if the face candidate is a nonprofile face. Experimental results show that the proposed method is robust under a wide range of lighting conditions, different poses, and races. The detection rate for the HHI face database is 93.68%. For the Champion face database, the detection rate is 95.15%.

Automated people-counting by using low-resolution infrared and visual cameras

Non-contact counting of people in a specified area has many applications for safety, security and commercial purposes. Visible sensors have inherent limitations for this task, being sensitive to variations in ambient lighting and colours in the scene. Infrared imaging can overcome many of these problems, but normally hardware costs are prohibitively expensive. A system for counting people in a scene using a combination of low cost, low-resolution visual and infrared cameras is presented in this paper. The aim of this research was to assess the potential accuracy and robustness of systems using low-resolution images. This approach results in considerable savings on hardware costs, enabling the development of systems which may be implemented in a wide range of applications. The results of 18 experiments show that the system can be accurate to within 3% over a wide range of lighting conditions.

Acquiring linear subspaces for face recognition under variable lighting

Previous work has demonstrated that the image variation of many objects (human faces in particular) under variable lighting can be effectively modeled by low-dimensional linear spaces, even when there are multiple light sources and shadowing. Basis images spanning this space are usually obtained in one of three ways: A large set of images of the object under different lighting conditions is acquired, and principal component analysis (PCA) is used to estimate a subspace. Alternatively, synthetic images are rendered from a 3D model (perhaps reconstructed from images) under point sources and, again, PCA is used to estimate a subspace. Finally, images rendered from a 3D model under diffuse lighting based on spherical harmonics are directly used as basis images. In this paper, we show how to arrange physical lighting so that the acquired images of each object can be directly used as the basis vectors of a low-dimensional linear space and that this subspace is close to those acquired by the other methods. More specifically, there exist configurations of k point light source directions, with k typically ranging from 5 to 9, such that, by taking k images of an object under these single sources, the resulting subspace is an effective representation for recognition under a wide range of lighting conditions. Since the subspace is generated directly from real images, potentially complex and/or brittle intermediate steps such as 3D reconstruction can be completely avoided; nor is it necessary to acquire large numbers of training images or to physically construct complex diffuse (harmonic) light fields. We validate the use of subspaces constructed in this fashion within the context of face recognition.