Light Imaging Research Articles

Water vapor and soot spatial characteristics retrieve of axisymmetric optically-thin laminar diffusion flame based on visible and near-infrared multi-spectral light field imaging

The comprehension of the distribution of gaseous species and soot particles plays a pivotal role in investigating the combustion process of a flame. A highly effective method to accomplish this is by extracting visible and near-infrared emission information from flames. In this study, we present a novel near-infrared multi-spectral light field imaging model that enables the concurrent extraction of gas and soot property distributions within a flame. A synthetic test of ethylene diffusion flame is assessed using the proposed reconstruction method. The mole fraction of gaseous water, together with the flame temperature and soot volume fraction, are decoupled spectrally using near-infrared and visible wavelengths. The results demonstrate a reliably retrieved temperature range of 1400 K to 2050 K, accurately reconstructing the actual distributions of soot volume fraction and gaseous water mole fraction. Minor influences on the imaging results and property reconstruction are observed due to uncertainties arising from the reconstruction method, absorption function, reconstruction wavelength for H2O mole fraction, and signal-to-noise ratio. This study serves as a theoretical guide for the future development of practical near-infrared multi-spectral light field imaging techniques for rapid and robust flame diagnostic purposes related to soot and gas properties.

Clearing-enabled light sheet microscopy as a novel method for three-dimensional mapping of the sensory innervation of the mouse knee.

A major barrier that hampers our understanding of the precise anatomic distribution of pain sensing nerves in and around the joint is the limited view obtained from traditional two dimensional (D) histological approaches. Therefore, our objective was to develop a workflow that allows examination of the innervation of the intact mouse knee joint in 3D by employing clearing-enabled light sheet microscopy. We first surveyed existing clearing protocols (SUMIC, PEGASOS, and DISCO) to determine their ability to clear the whole mouse knee joint, and discovered that a DISCO protocol provided the optimal transparency for light sheet microscopy imaging. We then modified the DISCO protocol to enhance binding and penetration of antibodies used for labeling nerves. Using the pan-neuronal PGP9.5 antibody, our protocol allowed 3D visualization of innervation in and around the mouse knee joint. We then implemented the workflow in mice intra-articularly injected with nerve growth factor (NGF) to determine whether changes in the nerve density can be observed. Both 3D and 2D analytical approaches of the light sheet microscopy images demonstrated quantifiable changes in midjoint nerve density following 4 weeks of NGF injection in the medial but not in the lateral joint compartment. We provide, for the first time, a comprehensive workflow that allows detailed and quantifiable examination of mouse knee joint innervation in 3D.

Depth-resolved imaging through scattering media using time-gated light field tomography.

We present a novel, to the best of our knowledge, approach to overcome the limitations imposed by scattering media using time-gated light field tomography. By integrating the time-gating technique with light field imaging, we demonstrate the ability to capture and reconstruct images with different depths through highly scattering environments. Our method exploits the temporal characteristics of light propagation to selectively isolate ballistic photons, enabling enhanced depth resolution and improved imaging quality. Through comprehensive experimental validation and analysis, we showcase the effectiveness of our technique in resolving depth information with high fidelity, even in the presence of significant scattering. The resultant system can simultaneously acquire multi-angled projections of the object without requiring prior knowledge of the media or the target. This advancement holds promise for a wide range of applications, including non-invasive medical imaging, environmental monitoring, and industrial inspection, where imaging through scattering media is critical for an accurate and reliable analysis.

Diagnostic accuracy of linked color imaging and white light imaging for early gastric cancer and gastrointestinal metaplasia: a systematic review and meta-analysis

BackgroundConventional white light imaging (WLI) frequently misses gastric cancer, resulting in a high rate of undiagnosed cases. This study compares the effectiveness of linked color imaging (LCI) and WLI in detecting early gastric cancer and gastrointestinal metaplasia, aiming to improve clinical diagnostic practices through evidence-based medical insights.MethodsThe QUADAS-2 tool evaluated the quality of the studies. Additionally, methods like Split Component Synthesis (SCS) were utilized to evaluate the diagnostic performance of LCI and WLI.ResultsEleven studies involving a total of 7836 patients were included in the meta-analysis. Comparative analysis revealed that LCI demonstrated a statistically significant superiority over WLI in terms of the detection rates of EGC and GIM (detection rate of EGC: LCI vs WLI, 85% vs. 56.7%, p=0.004, OR 4.78, 95% CI 2.33-9.82, I2 = 71%; detection rate of GIM: LCI vs WLI, 88.9% vs. 40.1%, p=0.0003, OR 9.94, 95% CI 5.59-17.68, I2 = 71%). Additionally, LCI exhibited better sensitivity and specificity for the diagnosis of EGC and GIM compared to WLI. For the entire cohort, the sensitivity of LCI for EGC detection was 80% (95% CI 71%-86%) with a specificity of 82% (95% CI 63%-92%), while for GIM detection, the sensitivity was 87% (95% CI 81%-92%) with a specificity of 85% (95% CI 77%-91%).ConclusionsThe detection efficiency of LCI for EGC and GIM is better than that of WLI, and LCI is recommended as the main screening method for EGC and GIM.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/, identifier CRD42023452140.

Motion-induced phase shift for dynamic structured light measurement.

Structured light 3D shape measurement is extensively utilized in semiconductor inspection, smart manufacturing, and biomedical imaging due to its rapid measurement speed, high precision, and versatile applicability to different objects. However, the traditional implementations of this method often require that the object remains static while recording the phase-shifting structured light images, which limits the adaptability of dynamic measurement. Here, we propose a dynamic 3D shape measurement using structured light based on a motion-induced phase shift (MIPS). As the object moves, the surface features distort the fringe pattern, resulting in a phase-shifting effect. By employing the MIPS method, we can determine the phase even in the situations where the knowledge of phase-shifting conditions is not accurate. This enables the acquisition of the 3D topography of the object surface with a high level of precision. Experimental results demonstrate that the MIPS method can accurately measure the 3D shape of objects moving as fast as 100 mm/s, with a relative discrepancy of less than 0.23%.

Investigation on spontaneous fires regions in coal gangue hills using UAV thermal infrared images

ABSTRACT The spontaneous combustion of coal gangue hills is accompanied by the release of toxic gases and the infiltration of metal elements, posing a serious threat to the global ecological environment. The current temperature monitoring methods for coal gangue hills have certain limitations, hence advanced and timely temperature monitoring is crucial for the management of coal gangue hills. This paper takes Guojiahe coal gangue hill as an example, thousands of visible light and thermal infrared images are obtained by using an unmanned aerial vehicle, and the 3-D model of the surface temperature of the gangue hill is established with Gaussian kernel technique and Random Sampling Consensus Method (RANSAC). Furthermore, the high-temperature zone in the gangue hill is measured by handheld thermocouples. The results indicate that high-temperature areas are distributed in a circular pattern and mostly concentrated on the slope surface and the boundary line between the slope and the bench. The thermal images can reflect the temperature inside the gangue hill by comparing the results of thermocouple temperature measurement and UAV detection. Further, it is analyzed that the air leakage cracks formed on the slope of the gangue hill provide a channel for the combination of coal gangue and oxygen, accelerating the heat accumulation, and the three-field coupling mechanism of coal gangue spontaneous combustion is proposed. This study can provide technical and methodological support for the prevention and control of spontaneous combustion in coal gangue hills.

Image enhancement method for paint defects based on polarization fusion technique

The highly reflective nature of paint surfaces poses a challenge for defect detection. In this paper, a polarization fusion based image enhancement algorithm for paint defects is proposed to improve the image quality and complement the masked defect details. Firstly, the linearly polarized photometric (DOLP) image is initially fused with the angle of polarization (AOP) image. The light intensity images and polarization feature images were enhanced using a single scale Retinex algorithm and these images were decomposed and reconstructed using wavelet transform to integrate the low and high frequency subbands based on saliency maps and regional energy features. Experiments were performed on defects at different locations and compared with other classical methods. The results show that the proposed fusion algorithm improves the contrast while providing more complete defect information, clearer texture details and significant advantages over other algorithms.

SIFusion: Lightweight infrared and visible image fusion based on semantic injection.

The objective of image fusion is to integrate complementary features from source images to better cater to the needs of human and machine vision. However, existing image fusion algorithms predominantly focus on enhancing the visual appeal of the fused image for human perception, often neglecting their impact on subsequent high-level visual tasks, particularly the processing of semantic information. Moreover, these fusion methods that incorporate downstream tasks tend to be overly complex and computationally intensive, which is not conducive to practical applications. To address these issues, a lightweight infrared and visible light image fusion method known as SIFusion, which is based on semantic injection, is proposed in this paper. This method employs a semantic-aware branch to extract semantic feature information, and then integrates these features into the fused features through a Semantic Injection Module (SIM) to meet the semantic requirements of high-level visual tasks. Furthermore, to simplify the complexity of the fusion network, this method introduces an Edge Convolution Module (ECB) based on structural reparameterization technology to enhance the representational capacity of the encoder and decoder. Extensive experimental comparisons demonstrate that the proposed method performs excellently in terms of visual appeal and advanced semantics, providing satisfactory fusion results for subsequent high-level visual tasks even in challenging scenarios.

Effect of detachment on Magnum-PSI ELM-like pulses: direct observations and qualitative results

Abstract Conditions similar to those at the end of the divertor leg in a tokamak were replicated in the linear plasma machine Magnum-PSI. The neutral pressure in the target chamber is then increased to cause the target to transition from an attached to a detached state. Superimposed to this steady state regime, edge localised mode (ELM)-like pulses are reproduced, resulting in a sudden increase in plasma temperature and density, such that the heat flux increases transiently by half an order of magnitude. Visible light emission, target thermography, and Thomson scattering are used to demonstrate that the higher the neutral pressure the more energy is removed from the ELM-like pulse in the volume. If the neutral pressure is sufficiently high, the ELM-like pulse can be prevented from affecting the target and the plasma energy is fully dissipated in the volume instead (ID 4 in table 1). The visible light images allow the division of the ELM-plasma interaction process of ELM energy dissipation into 3 ‘stages’ ranging from no dissipation to full dissipation (the target plasma is detached). In the second publication related to this study, spectroscopic data is analysed with a Bayesian approach, to acquire insights into the significance of molecular processes in dissipating the plasma energy and particles.

Fast and light-efficient remote focusing for volumetric voltage imaging

Voltage imaging holds great potential for biomedical research by enabling noninvasive recording of the electrical activity of excitable cells such as neurons or cardiomyocytes. Camera-based detection can record from hundreds of cells in parallel, but imaging entire volumes is limited by the need to focus through the sample at high speeds. Remote focusing techniques can remedy this drawback, but have so far been either too slow or light-inefficient. Here, we introduce flipped image remote focusing, a remote focusing method that doubles the light efficiency compared to conventional beamsplitter-based techniques and enables high-speed volumetric voltage imaging at 500 volumes/s. We show the potential of our approach by combining it with light sheet imaging in the zebrafish spinal cord to record from >100 spontaneously active neurons in parallel.

Light field Laparoscope imaging model and calibration method based on flexible aperture-angular plane

With rapid developments in light field imaging, a great deal of attention has been given to its applications in industrial, medical and other fields due to its ability to perform three-dimensional reconstruction in single-shot. In these applications, Light field Laparoscope (LFL) is an important one, but it often suffers severe micro-lens image deformations that lead to incorrect LFL decoding, calibration and three-dimensional reconstruction. Based on the micro-lens image non-deformation constraint presented by us before, we propose the flexible aperture-angular plane to analyze the LFL imaging model, the modified microlens image non-deformation constraint for 3D LFL system and an advanced two-step calibration method to compute 3D LFL imaging parameters. Moreover, a 3D LFL imaging prototype is designed and calibrated. Experimental results show that microlens image deformations are avoided in this 3D LFL prototype, and the typical RMS re-projection error is about 0.06 pixels.

LEAFusion: An Infrared and Visible Light Image Fusion Network Resilient to Harsh Light Environment Interference Based on Harsh Light Environment Aware

LEAFusion: An Infrared and Visible Light Image Fusion Network Resilient to Harsh Light Environment Interference Based on Harsh Light Environment Aware

Analysis of clinicopathological factors associate with the visibility of early gastric cancer in endoscopic examination and usefulness of linked color imaging: A multicenter prospective study.

This study investigated clinicopathological factors associated with the visibility of early gastric cancer and the efficacy of linked color imaging. Patients with early gastric cancer who underwent endoscopic treatment between April 2021 and July 2022 were enrolled. All cases underwent white light imaging and linked color imaging. Three experts evaluated lesion visibility using a visual analog scale. A mean score ≥3 on white light imaging was defined as "good visibility", and <3 as "poor visibility". We extracted patient information and endoscopic and pathological data for the lesion and background mucosa, analyzed factors associated with the visibility of early gastric cancer, and compared visibility between white light imaging and linked color imaging. Ninety-seven lesions were analyzed, with good visibility in 49 and poor visibility in 48. Multivariate analysis revealed small lesion size (odds ratio 1.89) and presence of endoscopic intestinal metaplasia (odds ratio 0.49) as significantly associated with the poor visibility of early gastric cancer. Mean visibility score was significantly higher for linked color imaging (P<0.001). Mean score for linked color imaging was significantly higher in the poor visibility group (P<0.001), but not significantly different in the good visibility group (P = 0.292). Mean score was significantly higher with linked color imaging in cases with endoscopic intestinal metaplasia (P = 0.0496) and lesions <20 mm in diameter (<10 mm, P = 0.002; 10-20 mm, P = 0.004). Lesion size and endoscopic intestinal metaplasia are associated with the visibility of early gastric cancer in white light imaging. Linked color imaging improves visibility of gastric cancer with these factors.

Blue light reflectance imaging in non-perfusion areas detection: insights from multimodal analysis

DesignA retrospective, cross-sectional image analysis using a convenience sample.SubjectsFive cases selected based on the availability of comprehensive imaging data.MethodsThis study involved a retrospective review of images from five cases, focusing on the use of retinal monochromatic blue light reflectance (BLR) imaging to detect non-perfusion areas. Two cases of sickle-cell retinopathy demonstrated peripheral retinal non-perfusion identified through widefield fluorescein angiography. Three other cases—one with branch retinal vein occlusion, one with branch retinal artery occlusion, and one presenting paracentral acute middle maculopathy showed focal macular non-perfusion detected by structural OCT and OCTA. The areas of nonperfused retinal tissue, confirmed by fluorescein angiography, OCT, and OCTA, were then correlated with findings from the BLR image. This correlation aimed to identify any potential associations between these imaging modalities.Main outcome measuresEnhance understanding of the utilization of retinal monochromatic BLR images as a non-perfusion biomarker.ResultsThe perfusion defects identified through fluorescein angiography were qualitatively correlated with hypo-reflective regions observed in the BLR images. A notable correlation was also observed between the OCTA deep capillary plexus findings and the BLR images. Additionally, areas of retinal thinning identified on structural OCT thickness maps corresponded with the hypo-reflective regions in the BLR images. This indicates the potential of BLR in identifying non-perfused retinal areas.ConclusionsThis study reinforces the evidence, through OCT, OCTA, and angiographic correlation, that the BLR can effectively identify areas of retinal non-perfusion in a non-invasive manner. Further research is warranted to assess the method’s sensitivity, specificity, and limitations. While the interaction of blue light with the retina, leading to specular reflections and scattering, is established, this research represents a pioneering effort in suggesting which specific retinal structures may be implicated in this phenomenon. This novel insight opens avenues for deeper exploration into the underlying mechanisms and potential clinical applications of utilizing the BLR imaging technique for assessing retinal vascular abnormalities.

Increases in Night Lights Intensity Reveal Extreme Events: A Case of Study on the Ongoing Conflict in Ukraine

Abstract. Analyzing night lights images allows identifying and monitoring affected areas during conflicts, as an overall decrease in brightness indicates abandoned or destroyed buildings, curfews, or power shortages. While detecting decrease in lights intensity is an established technique to identify critical areas during conflicts, the causes of appearing bright lights have not been extensively studied. An increase in brightness may be related to extreme events, such as fires resulting from bombing. This paper shows several examples supporting this new use of these images, validated using high-resolution optical earth observation data and ancillary information sources in the frame of the conflict in Ukraine which has been ongoing since February 2022.

Super-resolution reconstruction of light field image based on dynamic adjustment of attention mechanism

Super-resolution reconstruction of light field image based on dynamic adjustment of attention mechanism

Edge enhancement and feature modulation based network for light field depth estimation

Estimating depth from light field images is a critical issue in light field applications. While learning-based methods have made significant strides in light field depth estimation, achieving high accuracy and speed simultaneously remains a major challenge. This paper proposes a light field depth estimation network based on edge enhancement and feature modulation, which significantly improves depth estimation results by emphasizing inter-view correlations while preserving image edge features. Specifically, to prioritize edge details, we introduce an Edge-Enhanced Cost Constructor (EECC) that integrates edge information with existing cost constructors to improve depth estimation performance in complex areas. Furthermore, most light field depth estimation networks utilize only sub-aperture images (SAIs) without considering the inherent angular information in macro-pixel image (MacPI). To address this limitation, we propose the MacPI-Guided Feature Modulation (MGFM) module, which leverages angular information between different views in MacPI to modulate features at each view. Experimental results show that our method not only performs excellently on synthetic datasets but also demonstrates outstanding generalization on real-world datasets, achieving a better balance between accuracy and computation speed.

Illuminating Causality: The Role of Light in Thomas Aquinas’s Metaphysics of Being

In this article, we hold a strong thesis, i.e., that light is the conceptual resource that best explains the creative act in Thomas Aquinas’s metaphysics. Thus, inasmuch as being is the luminous act of the Uncreated Being, it bears resemblance to the Uncreated Being in its very principle. In this sense, we seek to present the role of light, in its meaning as manifestation, as an act that belongs to being. Indeed, in contrast with some contemporary interpretations, which place light within the order of formal causality, we argue that light, in its belonging to Aquinas’s participatory metaphysics, pertains to the order of efficient causality. Therefore, we hold that light has strong explanatory pretensions in Aquinas’ thought. Accordingly, after an introduction (1), this article is divided into the following sections: (2) The Meaning of Divine Causality; (3) Being as Light; (4) The Manifestative Character of Light; (5) Light Images: Analogies and Metaphors; and (6) Conclusions.

Weak saliency ensemble network for person Re-identification using infrared light images

In recent years, person re-identification (re-id) has primarily been studied using visible light (VL) images. However, the challenges of employing VL images in nighttime environments have prompted research into using infrared light (IR) images. Yet, the utilization of both VL and IR images in person re-id has resulted in increased computational cost and processing time in multi-modality systems, leading to studies focusing solely on IR images. Nevertheless, IR images, lacking color and texture information, generally yield lower recognition performance in existing person re-id studies. In addition, previous studies have shown that person re-id performance suffers in the presence of complex background noise. To tackle these challenges, this study proposes a new weak saliency ensemble network (WSE-Net) for person re-id using IR images. WSE-Net incorporates a channel reduction of feature (CRF) method to reduce computational cost in the ensemble network, a technique for converting input images into group of patch images and feeding them into the ensemble model to enhance the reduced feature information, and a grouped convolution ensemble network (GCE-Net) that enables the fusion of features extracted from original and attention-guided ensemble models.The performance of person re-id using WSE-Net was evaluated on the Dongguk body-based person recognition database version 1 (DBPerson-Recog-DB1) and the Sun Yat-sen university multiple modality re-identification version 1 (SYSU-MM01). Experimental results demonstrated that on DBPerson-Recog-DB1, WSE-Net achieved 93.65% in rank 1, 95.28% in mean average precision (mAP), and 93.52% in the harmonic mean of precision and recall. Additionally, on SYSU-MM01, WSE-Net achieved 86.85% in rank 1, 44.58% in mAP, and 40.06% in the harmonic mean of precision and recall. Furthermore, the accuracy of WSE-Net on both datasets surpassed that of state-of-the-art methods.

TransImg: A Translation Algorithm of Visible-to-Infrared Image Based on Generative Adversarial Network

Infrared images of sensitive targets are difficult to obtain and cannot meet the design and training needs of target detection and tracking algorithms for mobile platforms such as aircraft. This paper proposes an image translation algorithm TransImg, which can achieve visible light image translation to the infrared domain to enrich the dataset. First, the algorithm designed a generator structure consisting of a deep residual connected encoder and a region perception feature fusion module to enhance feature learning, thereby avoiding issues such as generating infrared images with insufficient details in the transfer task. Afterward, a multi-scale discriminator and a composite loss function were designed to further improve the transfer effect. Finally, an automatic mixed-precision training strategy was designed for the overall migration algorithm architecture to accelerate the training and generation of infrared images. Experiments have shown that the image translation algorithm TransImg has good algorithm accuracy, and the infrared image generated by visible light image translation has richer texture details, faster generation speed, and lower video memory consumption, and the performance exceeds the mainstream traditional algorithm, and the generated images can meet the requirements of target detection and tracking algorithms design and training for mobile platforms such as aircraft.