Search Results (228)

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-light enhancement methods have been proposed, they generally overlook the importance of frequency-domain information in modeling light field features, thereby limiting their noise suppression capabilities. Moreover, these enhancement methods mainly rely on pixel- or semantic-level cues without explicitly incorporating disparity information for structural modeling, thereby overlooking the stereoscopic spatial structure of light field images and limiting enhancement performance across different depth levels. To address these issues, we propose a light field low-light enhancement method named DDPNet. The method integrates a depth-guided mechanism to jointly restore light field images in both the spatial and frequency domains, employing a multi-stage progressive strategy to achieve synergistic improvements in illumination and depth. Specifically, we introduce a Dual-Domain Feature Extraction (DDFE) module, which incorporates spatial-frequency analysis to efficiently extract both global and local light field features. In addition, we propose a Depth-Aware Enhancement (DAE) module, which utilizes depth maps to guide the enhancement process, effectively restoring edge structures and luminance information. Extensive experimental results demonstrate that DDPNet significantly outperforms existing methods. Full article

Increasing the lighting luminance in the diverging zone of interchange in highway tunnels can generally enhance driving safety. However, it creates a bright–dark luminance contrast with the adjacent road. A pronounced contrast can induce new driving risks. This underlying mechanism remains unclear. Three key factors, i.e., the luminance of the dark environment, the bright–dark luminance ratio, and the position of the small target, are identified in this paper, which affect drivers’ visual recognition abilities. Based on fundamental tunnel lighting design rules, a series of naturalistic driving tests on the visual recognition distance for small targets with 132 conditions were designed. It combined three dark environment luminance levels (1.5~3.5 cd/m²), four bright–dark luminance ratios (2~5), and eleven small target positions (−50~+50 m). Twenty-four drivers were randomly selected and drove vehicles under the different scenarios. Their visual recognition distances for small targets were recorded and analyzed. The results show that visual recognition distances for small target visuals under different bright–dark lighting environments vary significantly, and the shortest distances occur exactly at the luminance boundary. Both decreasing the bright–dark luminance ratio and proportionally increasing the luminance levels of the bright and dark environments can markedly improve the visual recognition distance. A multi-parameter regression model was developed to correlate the visual recognition distance at the bright–dark luminance boundary with the luminance of the dark environment and the bright–dark luminance ratio. Based on drivers’ required safe sight distance, a method for setting lighting luminance in the diverging zone of interchange was proposed. The methodology and findings offer technical support for lighting design and safety management in the diverging zone of interchange in highway tunnels. Full article

The visual performance and photobiological effects of white LED systems based on spectral compensation are discussed, specifically focusing on the total optical power, the ratio of scotopic vision luminous flux to photopic vision luminous flux (S/P), the blue light hazard (BLH), and the circadian action factor (CAF). Theoretical models are established by integrating the spectral power distribution (SPD) with spectral sensitivity functions associated with the human visual system, and meanwhile, the impacts of LEDs’ electro-thermal characteristics on the mixed spectral structure and optical properties are analyzed. As experimental results demonstrate, an excellent agreement is shown between the calculated and measured values of the total optical power, S/P, BLH, and CAF, in terms of both values and variation trends. These proposed models are expected to serve as effective tools for understanding the visual perception and non-visual biological effects in specific illumination environments. Moreover, they can offer valuable reference frameworks for the development of lighting solutions that are more human-centered and health-oriented. Full article

The gastrointestinal tract is affected by multiple ailments that manifest with similar chemical, subcellular, and cellular changes, such as those in intestinal ischemia–reperfusion injury (IRI). The main chemical changes that are described under IRI conditions include the depletion of oxygen available for normal metabolism and the abundant production and increase in intracellular and extracellular concentrations of hydrogen peroxide and other reactive oxygen species (ROS). The enzymes causing this accumulation are xanthine dehydrogenase turning into xanthine oxidase, nicotinamide adenine dinucleotide phosphate oxidase, and nitric oxide synthase. The cellular changes revolve around an oxygen-sensing system that is responsive to varying oxygen levels, which has Hypoxia-Inducible Factors (HIFs) at its base. HIFs are transcription factors, the intracellular concentrations of which significantly increase under hypoxic conditions. Upon activation, they alter the expression of gene sets to ensure appropriate cellular adjustment to the hypoxic and IRI environment. Despite the primary regulation of the system involving oxygen, it is interconnected with multiple other subcellular and cellular functions. Thus, it represents a linchpin control mechanism of cellular adaptation. The effect of HIF activation in intestinal cells aims at preserving the structural integrity of the intestinal lining. The effect in different subtypes of leucocytes aims at immune system activation to protect against previously luminally located and subsequently invading pathogens and toxins. All in all, the HIF system is an integral part of cellular and tissue compensation against intestinal IRI. Full article

Postpartum uterine involution in cattle involves complex morphological and immunological changes essential for restoring uterine health and fertility. This study evaluated endometrial biopsies collected at four postpartum time points to characterize tissue remodeling and immune cell dynamics during involution. Histology revealed intact luminal columnar epithelium in 92.98% of samples, with stable stromal architecture. Stromal edema decreased by Day 7 but increased again by Day 35, while endometrial gland numbers significantly rose at Day 35, suggesting glandular recovery linked to resumed cyclicity. Subepithelial collagen deposition peaked on Day 21, indicating active extracellular matrix remodeling. Immunologically, early postpartum was marked by increased PMNs and macrophages, whereas Day 21 showed peak infiltration of natural killer (NK) cells and T and B lymphocytes, sometimes forming lymphoid aggregates. Manual and automated immune cell quantifications correlated well. These findings demonstrate a dynamic shift from acute neutrophil-dominated inflammation to a lymphocyte-rich environment during uterine involution. This immune modulation may contribute to the earlier diagnosis of subclinical endometritis, typically identified at later stages of postpartum period. Overall, this study provides insight into the temporal immunomorphological events supporting uterine recovery, with potential implications for reproductive management in dairy cattle. Full article

This study examined how different lighting characteristics of conventional and eco-friendly lighting and environmental conditions, particularly snow cover, influenced the luminous environment and, in relation to that, pedestrian perception of faces on footpaths. The analysis was based on a dataset comprising both subjective evaluations and objective measurements. The spatial and directional light field above a footpath was measured for the two types of road lighting, of which the “eco-centric” luminaire had a lumen output of 4820 lm and reduced blue-light component (correlated color temperature (CCT) of 2200 K) compared to the conventional luminaire with 14,000 lm and 4000 K. The luminaires were analyzed under snowy and non-snowy conditions. Snow cover significantly increased light diffuseness and density (directionally averaged illuminance at a point), resulting in more uniform light and higher subjective ratings. Also, face visibility ratings were generally higher and more uniform, while non-snowy conditions led to more pronounced differences between positions and luminaire types. Regression analysis revealed that vertical illuminance at eye height was the strongest predictor of perceived facial friendliness and well-lighted-ness and contributed to more favorable ratings for the environment lighting too. The eco-centric luminaire was found to positively influence face lighting ratings but received lower ratings for environmental visibility. Increased horizontal illuminance did not consistently result in enhanced subjective evaluations, which points to limitations of traditional illuminance-based lighting standards, often considering horizontal illuminance at ground level as one of the main metrics. The “social light field” concept emphasizes a holistic approach to urban lighting design that integrates social perception and environmental sustainability by considering the distribution of the actual, resulting light throughout the urban space, especially vertical illuminance at the face and its effects on visual appearance, as well as contributing interactions with the environment and materials in it. Full article

Macrobrachium nipponense represents a commercial decapod species that predominantly inhabits freshwater ecosystems or environments with low salinity. However, the species exhibits normal survival and reproductive capacity in natural aquatic habitats with salinity levels up to 10 parts per thousand (ppt). The present study aimed to elucidate the molecular mechanisms underlying salinity acclimation in M. nipponense by investigating alterations in oxidative stress, morphological adaptations, and hepatopancreatic gene expression profiles following exposure to a salinity level of 10 ppt. The present study demonstrates that glutathione peroxidase and Na⁺/K⁺-ATPase play critical roles in mitigating oxidative stress induced by elevated salinity in M. nipponense. Furthermore, histological analysis revealed distinct pathological alterations in the hepatopancreas of M. nipponense following 7-day salinity exposure, including basement-membrane disruption, luminal expansion, vacuolization, and a marked reduction in storage cells. Transcriptomic profiling of M. nipponense hepatopancreas suggested coordinated activation of both immune (lysosome and protein processing in endoplasmic reticulum pathways) and energy (pyruvate metabolism, glycolysis/gluconeogenesis, and citrate cycle) metabolic processes during salinity acclimation in M. nipponense. Quantitative real-time PCR validation confirmed the reliability of RNA-seq data. This study provides molecular insights into the salinity adaptation mechanisms in M. nipponense, offering potential applications for improving cultivation practices in brackish water environments. Full article

As part of contemporary urban culture, murals support place making and city identity. While much attention has been paid to their role in activating public space during daylight hours, their presence after dark remains largely unexamined. This paper analyzes how mural content interacts with night-time illumination. The research draws on case studies, photographs, luminance measurements, and lighting simulations. It evaluates how existing lighting systems support or undermine the legibility and impact of commercial murals in urban environments. It explores whether standardized architectural lighting guidelines suit murals, how color and surface affect visibility, and which practices improve night-time legibility. The study identifies a gap in existing lighting strategies, noting that uneven lighting distorts intent and reduces public engagement. In response, a new design tool—the Floodlighting Content Readability Map—is proposed to support artists and planners in creating night-visible murals. This paper situates mural illumination within broader debates on creative urbanism and argues that lighting is not just infrastructure, but a cultural and aesthetic tool that extends the reach and resonance of public art in the 24 h city. It further emphasizes the need for interdisciplinary collaboration and a multi-contextual perspective—encompassing visual, social, environmental, and regulatory dimensions—when designing murals in cities. Full article

The Roman public library of Timgad (Algeria) constituted the study object of several extensive research works, particularly during the French colonial era. Following a virtual restitution-focused research work, this investigation aims to quantitatively characterize the daylighting conditions inside Timgad Public Library. Here, it must be remembered that the luminous environment inside libraries is a main design parameter and a main environmentalfactor. In addition, it must be highlighted that the Timgad region’s luminous climate differs from where Rome’s designers and builders practiced. Hence, at a first step, a comparison is carried out between the precepts of Vitruvius, the pioneer of ancient Roman architecture, and the outcomes of previous studies related to Roman libraries. Then, as a second step, a double approach combining both 3D geometric modeling and numerical simulation using Radiance (2.0Beta) software. These simulations are mainly elaborated for the case of the large reading room, including most of the building’s main activities—consulting, reading, and storing books. Finally, this inner luminous environment’s characterization highlights that the Timgad Roman antic library was not uniformly daylit and suggests that its use varied spatially and temporally with respect to this environmental parameter. Full article

Underwater inspection images of hydraulic structures often suffer from haze, severe color distortion, low contrast, and blurred textures, impairing the accuracy of automated crack, spalling, and corrosion detection. However, many existing enhancement methods fail to preserve structural details and suppress noise in turbid environments. To address these limitations, we propose a compact image enhancement framework called Wavelet Fusion with Sobel-based Weighting (WWSF). This method first corrects global color and luminance distributions using multiscale Retinex and gamma mapping, followed by local contrast enhancement via CLAHE in the L channel of the CIELAB color space. Two preliminarily corrected images are decomposed using discrete wavelet transform (DWT); low-frequency bands are fused based on maximum energy, while high-frequency bands are adaptively weighted by Sobel edge energy to highlight structural features and suppress background noise. The enhanced image is reconstructed via inverse DWT. Experiments on real-world sluice gate datasets demonstrate that WWSF outperforms six state-of-the-art methods, achieving the highest scores on UIQM and AG while remaining competitive on entropy (EN). Moreover, the method retains strong robustness under high turbidity conditions (T ≥ 35 NTU), producing sharper edges, more faithful color representation, and improved texture clarity. These results indicate that WWSF is an effective preprocessing tool for downstream tasks such as segmentation, defect classification, and condition assessment of hydraulic infrastructure in complex underwater environments. Full article

The underwater environment severely degrades image quality by absorbing and scattering light. This causes significant challenges, including non-uniform illumination, low contrast, color distortion, and blurring. These degradations compromise the performance of critical underwater applications, including water quality monitoring, object detection, and identification. To address these issues, this study proposes a detail-oriented hybrid framework for underwater image enhancement that synergizes the strengths of traditional image processing with the powerful feature extraction capabilities of unsupervised deep learning. Our framework introduces a novel multi-scale detail enhancement unit to accentuate structural information, followed by a Latent Low-Rank Representation (LatLRR)-based simplification step. This unique combination effectively suppresses common artifacts like oversharpening, spurious edges, and noise by decomposing the image into meaningful subspaces. The principal structural features are then optimally combined with a gamma-corrected luminance channel using an unsupervised MU-Fusion network, achieving a balanced optimization of both global contrast and local details. The experimental results on the challenging Test-C60 and OceanDark datasets demonstrate that our method consistently outperforms state-of-the-art fusion-based approaches, achieving average improvements of 7.5% in UIQM, 6% in IL-NIQE, and 3% in AG. Wilcoxon signed-rank tests confirm that these performance gains are statistically significant (p < 0.01). Consequently, the proposed method significantly mitigates prevalent issues such as color aberration, detail loss, and artificial haze, which are frequently encountered in existing techniques. Full article

Hydraulic concrete is a critical infrastructure material, with its surface condition playing a vital role in quality assessments for water conservancy and hydropower projects. However, images taken in complex hydraulic environments often suffer from degraded quality due to low lighting, shadows, and noise, making it difficult to distinguish defects from the background and thereby hindering accurate defect detection and damage evaluation. In this study, following systematic analyses of hydraulic concrete color space characteristics, we propose a Dual-Branch Luminance–Chrominance Attention Network (DBLCANet-HCIE) specifically designed for low-light hydraulic concrete image enhancement. Inspired by human visual perception, the network simultaneously improves global contrast and preserves fine-grained defect textures, which are essential for structural analysis. The proposed architecture consists of a Luminance Adjustment Branch (LAB) and a Chroma Restoration Branch (CRB). The LAB incorporates a Luminance-Aware Hybrid Attention Block (LAHAB) to capture both the global luminance distribution and local texture details, enabling adaptive illumination correction through comprehensive scene understanding. The CRB integrates a Channel Denoiser Block (CDB) for channel-specific noise suppression and a Frequency-Domain Detail Enhancement Block (FDDEB) to refine chrominance information and enhance subtle defect textures. A feature fusion block is designed to fuse and learn the features of the outputs from the two branches, resulting in images with enhanced luminance, reduced noise, and preserved surface anomalies. To validate the proposed approach, we construct a dedicated low-light hydraulic concrete image dataset (LLHCID). Extensive experiments conducted on both LOLv1 and LLHCID benchmarks demonstrate that the proposed method significantly enhances the visual interpretability of hydraulic concrete surfaces while effectively addressing low-light degradation challenges. Full article

The luminous environment, shaped by daylight and electric light, significantly influences visual performance, physiological responses, and perceptual experiences. While these light sources are often perceived as distinct due to their differing effects on occupants’ cognition and well-being, the underlying mechanisms remain unclear. Nine lighting conditions were evaluated, combining three spectral types—daylight (DL), conventional LED (CLED), and daylight LED (DLED)—with three horizontal illuminance levels (300 lx, 500 lx, and 1000 lx). Twelve healthy subjects completed visual performance tasks (2-back working memory test), physiological measurements (heart rate variability and critical flicker frequency), and subjective evaluations. The results revealed that 500 lx consistently yielded the most favorable outcomes: 2-back task response speed improved by 6.2% over 300 lx and 1000 lx, and the critical flicker frequency difference was smallest, indicating reduced fatigue. DLED lighting achieved cognitive and physiological levels comparable to daylight. Heart rate variability analyzes further confirmed higher alertness levels under 500 lx DLED lighting (LF/HF = 3.31). Subjective ratings corroborated these findings, with perceived alertness and comfort highest under DLED and 500 lx conditions. These results demonstrate that DLED, which offers a balanced spectral composition and improved uniformity, may serve as an effective lighting configuration for supporting both visual and non-visual performance in indoor settings lacking daylight. Full article

This study evaluates the optical and thermal performance of near-infrared (NIR)-blocking spectacle lenses at luminous transmittance grades of 0, 2, and 3. Ten lens types were tested, including clear, tinted, and NIR-blocking spectacle lenses (NIBSL). The NIR blocking rate was measured across 780–1100 nm and 1100–1400 nm wavelength bands. Color reproduction was assessed using sharpness (MTF 50), point spread function (PSF), and color accuracy (ΔE₀₀) under 1000 lux outdoor illumination. Thermal insulation was analyzed by monitoring porcine skin temperature at 36 °C and 60 °C under each lens type. As a result, the NIBSL showed better near-infrared blocking performance than other types of lenses in both wavelength ranges, and the coated NIBSL blocked near-infrared more effectively than the polymerized lenses. Compared with other types of lenses, NIBSL showed no difference in object identification, color recognition, and reproducibility, so there is no problem in using them together. Strong correlations were observed between lens surface temperature and underlying pig skin temperature, and inverse correlations between NIR blocking rate and pig skin temperature gradient. These findings confirm that NIBSL offer enhanced protection against NIR-induced thermal effects without compromising optical performance, supporting their use in daily environments for ocular and skin safety. Full article

The accurate identification of coal and rock at the mining face is often hindered by adverse underground imaging conditions, including poor lighting and strong reflectivity. To tackle these issues, this work introduces a recognition framework specifically designed for underground environments, leveraging joint migration and enhancement of multidimensional and full-scale visual representations. A Transformer-based architecture is employed to capture global dependencies within the image and perform reflectance component denoising. Additionally, a multi-scale luminance adjustment module is integrated to merge features across perceptual ranges, mitigating localized brightness anomalies such as overexposure. The model is structured around an encoder–decoder backbone, enhanced by a full-scale connectivity mechanism, a residual attention block with dilated convolution, Res2Block elements, and a composite loss function. These components collectively support precise pixel-level segmentation of coal–rock imagery. Experimental evaluations reveal that the proposed luminance module achieves a PSNR of 21.288 and an SSIM of 0.783, outperforming standard enhancement methods like RetinexNet and RRDNet. The segmentation framework achieves a MIoU of 97.99% and an MPA of 99.28%, surpassing U-Net by 2.21 and 1.53 percentage points, respectively. Full article