In low-light environments, light field (LF) images are often affected by various degradation factors, which impair the performance of subsequent visual tasks such as depth estimation. To address these challenges, although numerous light-field low-lig...
Insufficient light, uneven light, backlighting, and other problems lead to poor visibility of the image of an electric power operation site. Most of the current methods directly enhance the low-light image while ignoring local strong light that may a...
Images captured in a low-light environment are strongly influenced by noise and low contrast, which is detrimental to tasks such as image recognition and object detection. Retinex-based approaches have been continuously explored for low-light enhance...
Underground roadway support is a critical component for ensuring safety in mining operations. In recent years, with the rapid advancement of intelligent technologies, computer vision-based automatic rock bolt detection methods have emerged as a promi...
Segmenting low-light images, such as images showing cracks on tunnel walls, is challenging due to limited visibility. Hence, we need to combine image brightness enhancement and a segmentation algorithm. We introduce essential preliminaries, specifica...
Over the years, fluorescence microscopy has evolved and has become a necessary element of life science studies. Microscopy has elucidated biological processes in live cells and organisms, and also enabled tracking of biomolecules in real time. Develo...
Polarization imaging has achieved a wide range of applications in military and civilian fields such as camouflage detection and autonomous driving. However, when the imaging environment involves a low-light condition, the number of photons is low and...
Low-light images have low contrast and high noise, making them not easily readable. Most existing image-enhancement methods focus on color images. In the present study, an enhancement and denoising algorithm for single low-light grayscale images is p...
Here we document physiological and molecular attributes of three wheat cultivars (ZM9023, YM158 and FM1228) under low light intensity with advanced technologies, including non-standard quantitative technology and quantitative proteomics technology. W...
This study explores the development of luminescent wearables using machine embroidery with phosphorescent threads to enhance the visibility and safety of children in low-light environments, addressing the need for improved child protection in urban s...
Researchers working on image processing have had a hard time handling low-light images due to their low contrast, noise, and brightness. This paper presents an improved method that uses the Retinex theory to enhance low-light images, with a network m...
Low-light stress will lead to abnormal soybean growth and a subsequent yield reduction. Association mapping is a useful alternative to linkage mapping for the detection of marker–phenotype associations. This study aimed to evaluate low-light-re...
Accurate object tracking in low-light environments is crucial, particularly in surveillance, ethology applications, and biometric recognition systems. However, achieving this is significantly challenging due to the poor quality of captured sequences....
Images captured under poor lighting conditions often suffer from low brightness, low contrast, color distortion, and noise. The function of low-light image enhancement is to improve the visual effect of such images for subsequent processing. Recently...
Low-light image enhancement is an important task in computer vision. Deep learning-based low-light image enhancement has made significant progress. But the current methods also face the challenge of relying on a wide variety of low-light/normal-light...
Single image deblurring has achieved significant progress for natural daytime images. Saturation is a common phenomenon in blurry images, due to the low light conditions and long exposure times. However, conventional linear deblurring methods usually...
Object detection has a wide range of applications as the most fundamental and challenging task in computer vision. However, the image quality problems such as low brightness, low contrast, and high noise in low-light scenes cause significant degradat...
A key part of interpreting, visualizing, and monitoring the surface conditions of remote-sensing images is enhancing the quality of low-light images. It aims to produce higher contrast, noise-suppressed, and better quality images from the low-light v...
In low-light conditions, UAV localization faces substantial challenges due to reduced visibility, elevated noise levels, and diminished contrast. To address these issues, we propose a low-light-optimized visual localization framework that integrates...
In extremely dark conditions, low-light imaging may offer spectators a rich visual experience, which is important for both military and civic applications. However, the images taken in ultra-micro light environments usually have inherent defects such...
Due to the characteristics of low signal-to-noise ratio and low contrast, low-light images will have problems such as color distortion, low visibility, and accompanying noise, which will cause the accuracy of the target detection problem to drop or e...
Tomato (Solanum lycopersicum L.) plants, wild type Ailsa Craig, and carotenoid mutant tangerine that accumulates prolycopene instead of all-trans-lycopene were exposed to a combined treatment by low light and low temperature for 5 days. The ability o...
Object detection in low-light scenarios has been widely acknowledged as a significant research area in the field of computer vision, presenting a challenging task. Aiming at the low detection accuracy of mainstream single-stage object detection model...
To assess the current and future utility of low-light satellite data, this paper reviewed 1630 papers, presentations, theses, and dissertations using day/night band (DNB) data from the visible infrared imaging radiometer suite (VIIRS) imager and its...
Recent advances in deep learning have shown exciting promise in various artificial intelligence vision tasks, such as image classification, image noise reduction, object detection, semantic segmentation, and more. The restoration of the image capture...
The real-time monitoring and analysis system based on video images has been implemented to detect fire accidents on site. While most segmentation methods can accurately segment smoke areas in bright and clear images, it becomes challenging to obtain...
Low-light images are obtained in dark environments or in environments where there is insufficient light. Because of this, low-light images have low intensity values and dimmed features, making it difficult to directly apply computer vision or image r...
Background and Objectives: Evaporative dry eye disease is frequently associated with meibomian gland dysfunction. Patients are often unhappy because of daily drops, care burden, and suboptimal conventional treatments. In this study, we assessed the e...
Detecting pedestrians in low-light conditions is challenging, especially in the context of wearable platforms. Infrared cameras have been employed to enhance detection capabilities, whereas low-light cameras capture the more intricate features of ped...
Fog, as a common weather condition, severely affects the visual quality of images. Polarization-based dehazing techniques can effectively produce clear results by utilizing the atmospheric polarization transmission model. However, current polarizatio...
We propose restoring low-light images suffering from severe degradation using a deep-learning approach. A significant domain gap exists between low-light and real images, which previous methods have failed to address with domain alignment. To tackle...
In this paper, we propose a novel method to address dynamic blur and low-light issues in smart cabinets, which is named the MIMO-IMF (Multi-input Multi-output U-Net Integrated Motion Framework). This method combines a Frequency-Domain Adaptive Fusion...
Object detection in low-light conditions presents significant challenges due to issues such as weak contrast, high noise, and blurred boundaries. Existing methods often use image enhancement to improve detection, which results in a large amount of co...
Lane detection is a crucial task in the field of autonomous driving, as it enables vehicles to safely navigate on the road by interpreting the high-level semantics of traffic signs. Unfortunately, lane detection is a challenging problem due to factor...
Images captured under complex conditions frequently have low quality, and image performance obtained under low-light conditions is poor and does not satisfy subsequent engineering processing. The goal of low-light image enhancement is to restore low-...
Within low-light imaging environment, the insufficient reflected light from objects often results in unsatisfactory images with degradations of low contrast, noise artifacts, or color distortion. The captured low-light images usually lead to poor vis...
Object detection in low-light conditions is increasingly relevant across various applications, presenting a challenge for improving accuracy. This study employs the popular YOLOv7 framework and examines low-light image characteristics, implementing p...
Low-light image enhancement aims to improve the perceptual quality of images captured under low-light conditions. This paper proposes a novel generative adversarial network to enhance low-light image quality. Firstly, it designs a generator consistin...
We proposed the Retinex-based fast algorithm (RBFA) to achieve low-light image enhancement in this paper, which can restore information that is covered by low illuminance. The proposed algorithm consists of the following parts. Firstly, we convert th...
Images acquired in low-light conditions often have poor visibility. These images considerably degrade the performance of algorithms when used in computer vision and multi-media systems. Several methods for low-light image enhancement have been propos...
For the purpose of achieving long-range, high-resolution, and ultra-wide-swath airborne earth imaging at extremely low-light levels (0.01 Lux), a low-light imaging system built on multi-detector optical butting was researched. Having decomposed the s...
In general, the sensor lamps in the corridors, stairwells, or toilets of buildings will change from completely dark to full brightness when someone passes by. It will make the human eyes feel very uncomfortable, and when the sensor lamp is completely...
Dealing with low-light images is a challenging problem in the image processing field. A mature low-light enhancement technology will not only be conductive to human visual perception but also lay a solid foundation for the subsequent high-level tasks...
Unsupervised low-light image enhancement methods have gained attention and shown improvement with low data dependence. However, the lack of a ground truth presents challenges, notably in pronounced noise and color bias. This paper proposes a Self-Gui...
Low-light imaging capabilities are in urgent demand in many fields, such as security surveillance, night-time autonomous driving, wilderness rescue, and environmental monitoring. The excellent performance of SPAD devices gives them significant potent...
In recent years, Mamba has gained increasing importance in the field of image restoration, gradually outperforming traditional convolutional neural networks (CNNs) and Transformers. However, the existing Mamba-based networks mainly focus on capturing...
In the realms of the Internet of Things (IoT) and artificial intelligence (AI) security, ensuring the integrity and quality of visual data becomes paramount, especially under low-light conditions, where low-light image enhancement emerges as a crucia...
The effects of a five-day treatment with low light intensity on tomato plants—Ailsa Craig and tangerine mutant—at normal and low temperatures and after recovery for three days under control conditions were investigated. The tangerine toma...
In low-light optical imaging, the scarcity of incident photons and the inherent limitations of imaging sensors lead to challenges such as low signal-to-noise ratio, limited dynamic range, and degraded contrast, severely compromising image quality and...
Low-light images often exhibit reduced brightness, weak contrast, and color distortion. Consequently, enhancing low-light images is essential to make them suitable for computer vision tasks. Nevertheless, addressing this task is particularly challeng...
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