Passive Imaging Research Articles

Detection of atmospheric aerosols and terrestrial nanoparticles collected in a populous city in southern Brazil.

The main objective of this study is to analyze hazardous elements in nanoparticles (NPs) (smaller than 100nm) and ultrafine particles (smaller than 1µm) in Porto Alegre City, southern Brazil using a self-made passive sampler and Sentinel-3B SYN satellite images in 32 collection points. The Aerosol Optical Thickness proportion (T550) identification was conducted using images of the Sentinel-3B SYN satellite at 634 points sampled in 2019, 2020, 2021, and 2022. Focused ion beam scanning electron microscopy analyses were performed to identify chemical elements present in NPs and ultrafine particles, followed by single-stage cascade impactor to be processed by high-resolution transmission electron microscopy. This process was coupled with energy-dispersive X-ray spectroscopy and later analysis via secondary ion mass spectrometry. Data was acquired from Sentinel-3B SYN images, normalized to a standard mean of 0.83µg/mg, at moderate spatial resolution (260m), and modeled in the Sentinel Application Platform (SNAP) software v.8.0. Statistical matrix data was generated in the JASP software (Jeffreys's Amazing Statistics Program) v.0.14.1.0 followed by a K-means cluster analysis. The results demonstrate the presence of between 1 and 100nm particles of the following chemical elements: Si, Al, K, Mg, P, and Ti. Many people go through these areas daily and may inhale or absorb these elements that can harm human health. In the Sentinel-3B SYN satellite images, the sum of squares in cluster 6 is 168,265 and in cluster 7 a total of 21,583. The use of images from the Sentinel-3B SYN satellite to obtain T550 levels is of great importance as it reveals that atmospheric pollution can move through air currents contaminating large areas on a global scale.

Enhancing polarization 3D facial imaging: overcoming azimuth ambiguity without extra depth devices.

Polarization 3D imaging has been a research hotspot in the field of 3D facial reconstruction because of its biosafety, high efficiency, and simplicity. However, the application of this technology is limited by the multi-valued problem of the azimuth angle of the normal vector. Currently, the most common method to overcome this limitation is to introduce additional depth techniques at the cost of reducing its applicability. This study presents a passive 3D polarization facial imaging method that does not require additional depth-capturing devices. It addresses the issue of azimuth ambiguity based on prior information about the target image's features. Specifically, by statistically analyzing the probability distribution of real azimuth angles, it is found that their quadrant distribution is closely related to the positions of facial feature points. Therefore, through facial feature detection, the polarized normal azimuth angle of each pixel can be accurately assigned to the corresponding quadrant, thus determining a precise unique normal vector and achieving accurate 3D facial reconstruction. Finally, our azimuth angle correction method was validated by simulated polarization imaging results, and it achieved accurate correction for over 75% of the global pixels without using additional depth techniques. Experimental results further indicate that this method can achieve polarization 3D facial imaging under natural conditions without extra depth devices, and the 3D results preserve edge details and texture information.

Multi-band passive detection and imaging system for concealed weapon with dual assessment method

Technological advancements in the millimeter-wave (MMW) and terahertz (THz) frequency bands have seen rapid progress, especially in the field of concealed weapon detection. The capability to detect concealed objects under clothing without causing harm to individuals is of utmost importance. Because of this reason, the concept of the variable target ranges in a passive MMW/THz imaging system with the infrared band has been studied in detail. An imaging system, called multi-band passive detection and imaging system (MIS) in this study, with variable target ranges, was designed and tested. A passive MMW/THz imaging system is developed specifically for concealed weapon detection, with a primary focus on variable target ranges. In addition to this, an infrared imaging system has been incorporated into the concept of concealed weapon detection. To integrate these two imaging systems, image fusion techniques have been employed as a conjunction between them. Detailed analyses have been conducted to assess the concealed weapon detection capabilities of this integrated system. The image fusion results, combining infrared and passive MMW/THz bands, have been tested at variable target ranges, and the fused images have been compared in terms of structural similarity index (SSIM) and contrast levels (CL). The SSIM alone is an inadequate method in the concept of concealed weapon detection. The CL method, used with SSIM, eliminates the shortcoming of the SSIM alone. The outcomes of these tests demonstrate that MIS enhances the detectability of concealed weapons with the use of SSIM and CL together. As a result, this study lays a solid foundation for the future detection of concealed objects beneath clothing. The dual assessment method proposed in this study will enable the development of new methods that will increase the detection of specific objects under the clothes in the future.

Applications of Deep Learning-Based Super-Resolution Networks for AMSR2 Arctic Sea Ice Images

Studies have indicated that the decrease in the extent of Arctic sea ice in recent years has had a significant impact on the Arctic ecosystem and global climate. In order to understand the evolution of sea ice, it is becoming increasingly imperative to have continuous observations of Arctic-wide sea ice with high spatial resolution. Passive microwave sensors have the benefit of being less susceptible to weather, wider coverage, and higher temporal resolution. However, it is challenging to retrieve accurate parameters of sea ice due to the low spatial resolution of passive microwave images. Therefore, improving the spatial resolution of passive microwave images is beneficial for reducing the uncertainty of sea ice parameters. In this paper, four competitive multi-image super-resolution (MISR) networks are selected to explore the applicability of the networks on multi-frequency Advanced Microwave Scanning Radiometer 2 (AMSR2) images of Arctic sea ice. The upsampling factor is set to 4 in the experiment. Firstly, the optimal input lengths of the image sequence for the four MISR networks are found, and then the best network on different frequency band images is further identified. Furthermore, some factors, including seasons, sea ice motion, and polarization mode of images, that may affect the super-resolution (SR) results are analyzed. The experimental results indicate that utilizing images from winter yields superior SR results. Conversely, SR results are the worst during summer across all four MISR networks, exhibiting the largest difference in PSNR of 4.48 dB. Additionally, the SR performance is observed to be better for images with smaller magnitudes of sea ice motion compared to those with larger motions, with the maximum PSNR difference of 2.04 dB. Finally, the SR results for vertically polarized images surpass those for horizontally polarized images, showcasing an average advantage of 4.02 dB in PSNR and 0.0061 in SSIM. In summary, valuable suggestions for selecting MISR models for passive microwave images of Arctic sea ice at different frequency bands are offered in this paper. Additionally, the quantification of the various impact factors on SR performance is also discussed in this paper, which provides insights into optimizing MISR algorithms for passive microwave sea ice imagery.

Mapping the mantle transition zone discontinuities across South-Central Europe using body waves from seismic noise correlations

We map the mantle transition zone (MTZ) discontinuities beneath South-Central Europe using P-wave reflection phases recovered from noise correlations. We analyze up to four years of seismic noise recordings from 900 broadband stations in the study area. By stacking noise correlations in selected summer months, we significantly improved the retrieval of typically low-amplitude body-wave reflection phases in the light of a quiet surface-wave environment and sufficient noise body-wave illumination from deep paths. We obtain reliable P-wave reflections associated with the 410 km and 660 km discontinuities in the period band of 4–10 s. These short-period reflections reveal clear lateral depth variations of the two discontinuities, indicating complex MTZ structure under the greater Alpine region. This provides new important constraints on present and past mantle dynamics, and it shows the strong potential of passive seismic imaging for studying deep-Earth discontinuities.

Imaging the Crustal and Upper Mantle Structure of the North Anatolian Fault: A Transmission Matrix Framework for Local Adaptive Focusing

AbstractImaging the structure of major fault zones is essential for our understanding of crustal deformations and their implications on seismic hazards. Investigating such complex regions presents several issues, including the variation of seismic velocity due to the diversity of geological units and the cumulative damage caused by earthquakes. Conventional migration techniques are in general strongly sensitive to the available velocity model. Here we apply a passive matrix imaging approach which is robust to the mismatch between this model and the real seismic velocity distribution. This method relies on the cross‐correlation of ambient noise recorded by a geophone array. The resulting set of impulse responses form a reflection matrix that contains all the information about the subsurface. In particular, the reflected body waves can be leveraged to: (a) determine the transmission matrix between the Earth's surface and any point in the subsurface; (b) build a confocal image of the subsurface reflectivity with a transverse resolution only limited by diffraction. As a study case, we consider seismic noise (0.1–0.5 Hz) recorded by the Dense Array for Northern Anatolia that consists of 73 stations deployed for 18 months in the region of the 1999 Izmit earthquake. Passive matrix imaging reveals the scattering structure of the crust and upper mantle around the North Anatolian Fault zone over a depth range of 60 km. The results show that most of the scattering is associated with the Northern branch that passes throughout the crust and penetrates into the upper mantle.

Quantifying the Effect of Acoustic Parameters on Temporal and Spatial Cavitation Activity: Gauging Cavitation Dose.

Cavitation-enhanced delivery of therapeutic agents is under development for the treatment of cancer and neurodegenerative and cardiovascular diseases, including sonothrombolysis for deep vein thrombosis. The objective of this study was to quantify the spatial and temporal distribution of cavitation activity nucleated by Definity infused through the EKOS catheter over a range of acoustic parameters controlled by the EKOS endovascular system. Three insonation protocols were compared in an in vitro phantom mimicking venous flow to measure the effect of peak rarefactional pressure, pulse duration and pulse repetition frequency on cavitation activity energy, location and duration. Inertial and stable cavitation activity was quantified using passive cavitation imaging, and a metric of cavitation dose based on energy density was defined. For all three insonation protocols, cavitation was sustained for the entire 30min Definity infusion. The evolution of cavitation energy during each pulse duration was similar for all three protocols. For insonation protocols with higher peak rarefactional acoustic pressures, inertial and stable cavitation doses also increased. A complex relationship between the temporal behavior of cavitation energy within each pulse and the pulse repetition frequency affected the cavitation dose for the three insonation protocols. The relative predominance of stable or inertial cavitation dose varied according to insonation schemes. Passive cavitation images revealed the spatial distribution of cavitation activity. Our cavitation dose metric based on energy density enabled the impact of different acoustic parameters on cavitation activity to be measured. Depending on the type of cavitation to be promoted or suppressed, particular pulsing schemes could be employed in future studies, for example, to correlate cavitation dose with sonothrombolytic efficacy.

A Convolutional Neural Network for Beamforming and Image Reconstruction in Passive Cavitation Imaging.

Convolutional neural networks (CNNs), initially developed for image processing applications, have recently received significant attention within the field of medical ultrasound imaging. In this study, passive cavitation imaging/mapping (PCI/PAM), which is used to map cavitation sources based on the correlation of signals across an array of receivers, is evaluated. Traditional reconstruction techniques in PCI, such as delay-and-sum, yield high spatial resolution at the cost of a substantial computational time. This results from the resource-intensive process of determining sensor weights for individual pixels in these methodologies. Consequently, the use of conventional algorithms for image reconstruction does not meet the speed requirements that are essential for real-time monitoring. Here, we show that a three-dimensional (3D) convolutional network can learn the image reconstruction algorithm for a 16×16 element matrix probe with a receive frequency ranging from 256 kHz up to 1.0 MHz. The network was trained and evaluated using simulated data representing point sources, resulting in the successful reconstruction of volumetric images with high sensitivity, especially for single isolated sources (100% in the test set). As the number of simultaneous sources increased, the network's ability to detect weaker intensity sources diminished, although it always correctly identified the main lobe. Notably, however, network inference was remarkably fast, completing the task in approximately 178 s for a dataset comprising 650 frames of 413 volume images with signal duration of 20μs. This processing speed is roughly thirty times faster than a parallelized implementation of the traditional time exposure acoustics algorithm on the same GPU device. This would open a new door for PCI application in the real-time monitoring of ultrasound ablation.

Passive compressive ghost imaging with low-rank optimization

High-quality passive ghost imaging with a low sampling rate can effectively improve the channel capacity utilization of optical imaging systems, but the current ghost imaging methods generally suffer from the problem of insufficient channel capacity utilization. We take advantage of the property that the matrix composed of nonlocal similar blocks of an image has a low rank, combine it as a priori information with the compressed sampling model of ghost imaging, establish a ghost imaging model based on low-rank optimization, and propose an alternating minimization solution method for this model. According to the simulation and experimental verification of the ghost imaging camera, our proposed ghost imaging method outperforms similar imaging methods in PSNR, SSIM, as well as other objective evaluation indexes. Among them, for the reconstruction of a typical scene at a sampling rate of 6.25 %, our method outperforms peer methods by 20.6 % for PSNR and 68.7 % for SSIM. Furthermore, we analyze the confidence intervals and uncertainties of different ghost imaging methods in the process of optical field decoding, and the experimental results show that our imaging method has a higher confidence level.

Whole-body temperature measurement using a high-spatial resolution passive terahertz imager

Whole-body temperature measurement using a high-spatial resolution passive terahertz imager

Developing a focused ultrasound treatment for tendinopathies in a large animal model

Current treatments for tendinopathies produce mixed success rates, with 0-84% of patients showing improvement. Our prior work in rats suggests mild microdamage induced by focused ultrasound (fUS) may perform better than traditional treatments for tendinopathies, like dry needling. Here, we work to scale our work in rats to larger animal models and develop treatment monitoring. Ex vivo bovine digital flexor tendons were obtained and injected with collagenase to induce chronic tendinopathy. One day later, tendons were treated with focused ultrasound at 1.1–3.68 MHz, with 1–10ms pulses at pressures up to p + = 127 MPa/p− = 35 MPa repeated at 0.2–1 Hz for up to 20 min. Treatments were monitored with passive cavitation detection (PCD; Sonic Concepts Y-107) and Philips/ATL L7-4 controlled by the Verasonics research ultrasound system in passive cavitation imaging (PCI) mode. Samples were collected for histological analysis. Preliminary results suggest that lower pulse repetition frequencies produce mild mechanical microdamage with no evidence of thermal necrosis. PCI and PCD results show no consistent trends to indicate the intended mechanical microdamage bioeffect has been achieved. Work is continuing to determine the treatment parameters that produce the intended bioeffects in the smallest time and to develop a means to monitor treatment progress. [Work supported by NIHR01EB032860.]

The co-located arrangement of ECEI and MIR microwave imaging diagnostics on EAST tokamak

The co-located configuration of Passive Electron Cyclotron Emission Imaging (ECEI) and active Microwave Imaging Reflectometry (MIR) diagnostics systems has been successfully implemented on the EAST fusion reactor. These advanced 2D microwave diagnostic tools offer 10–20 mm poloidal spatial resolution through large aperture quasi optics. This arrangement not only optimizes the utilization of limited observation windows but also facilitates concurrent measurements of plasma density and electron temperature at specific toroidal positions. This co-located setup holds great promise for enhancing research into electron heat transport and other pivotal plasma phenomena.

Kalman Filter-Driven Blind Source Localization for Passive 3D ToF Imaging

Kalman Filter-Driven Blind Source Localization for Passive 3D ToF Imaging

Experimental investigation for multi-defect detection of industrial pipeline based on passive infrared thermal imaging analysis: A case study

Corrosion of pipe walls is a major hidden hazard for the safety of chemical enterprises; therefore, detection of the depth of pipe wall corrosion defects is extremely important. In this study, passive thermal imaging technology was used to detect and evaluate corrosion defects of different shapes in pipe walls and of different depths for the same shape. Three-dimensional finite element models of defects with different depths were established using COMSOL, and the thermal response mechanisms of defects with different depths and the effects of defect depth and shape on heat transfer were analyzed. The thermal response mechanism of defects with different shapes and depths (1–3 mm) was also analyzed experimentally and compared with that of defect-free parts to analyze the safety of the pipeline and verify the results of the numerical simulation analysis. The results indicated that the level of fluid temperature determined the accuracy of the test, and at the same temperature, the defects at a depth of 3 mm exhibited multiple peaks and a large peak area. However, defects with a depth of 2 mm exhibited the opposite behavior, and the heating rate of 3-mm deep defects during the temperature change was 1.08 times higher than that for 2 mm-deep defects. This study provides a reference for detecting leaks in chemical pipelines.

Broad fault zones enable deep fluid transport and limit earthquake magnitudes

Constraining the controlling factors of fault rupture is fundamentally important. Fluids influence earthquake locations and magnitudes, although the exact pathways through the lithosphere are not well-known. Ocean transform faults are ideal for studying faults and fluid pathways given their relative simplicity. We analyse seismicity recorded by the Passive Imaging of the Lithosphere-Asthenosphere Boundary (PI-LAB) experiment, centred around the Chain Fracture Zone. We find earthquakes beneath morphological transpressional features occur deeper than the brittle-ductile transition predicted by simple thermal models, but elsewhere occur shallower. These features are characterised by multiple parallel fault segments and step overs, higher proportions of smaller events, gaps in large historical earthquakes, and seismic velocity structures consistent with hydrothermal alteration. Therefore, broader fault damage zones preferentially facilitate fluid transport. This cools the mantle and reduces the potential for large earthquakes at localized barriers that divide the transform into shorter asperity regions, limiting earthquake magnitudes on the transform.

Low-Cost W-Band Dual-Mode SIW Bandpass Filters Using Commercially Available Printed-Circuit-Board Technology

W-band filters play a crucial role in modern millimeter-wave communication and radar systems, finding applications in 5G/6G networks, automotive radar, and passive imaging. With the growing demand for higher data rates and efficient wireless communication, W-band filter development has gained significant attention in recent years. Various design techniques and fabrication technologies have been explored for improved performance and integration possibilities. This paper presents a planar substrate-integrated waveguide (SIW) dual-mode cavity filter as a solution to the challenges faced by previous designs in terms of integration, size, and cost. The dual-mode cavity coupling principle and design parameters are analyzed to optimize the filter’s performance. A W-band 4th-order dual-mode filter prototype is designed and fabricated on a 0.127-mm-thick RO5880 substrate, and a finline waveguide-to-microstrip transition structure is employed for compatibility with the test instrument. Simulation and experimental results demonstrate that the proposed filter exhibits low insertion loss, good in-band standing wave performance, and improved out-of-band suppression. Moreover, a visible high-frequency out-of-band transmission zero is implemented to enhance the steep roll-off characteristics in the high-frequency out-of-band region.

Passive superresolution imaging of incoherent objects

The need to observe objects that are smaller than the diffraction limit has led to the development of various superresolution techniques. However, most such techniques require active interaction with the sample, which may not be possible in multiple practical scenarios. The recently developed technique of Hermite–Gaussian imaging (HGI) achieves superresolution by passively observing the light coming from an object. This approach involves decomposing the incoming field into the Hermite–Gaussian basis of spatial modes and measuring the amplitude or intensity of each component. From these measurements, the original object can be reconstructed. However, implementing HGI experimentally has proven to be challenging, and previous achievements have focused on coherent imaging or parameter estimation of simple objects. In this paper, we implement interferometric HGI in the incoherent regime and demonstrate a three-fold improvement in the resolution compared to direct imaging. We evaluate the performance of our method under different noise levels. Our results constitute a step towards powerful passive superresolution imaging techniques in fluorescent microscopy and astronomy.

Passive machine vision-based defect classification in tungsten inert gas welding on SS304 using AI-based gradient descent algorithm

In modern digitization, safety industries demand flaw-free and high-integrity welds, due to part localization on high uncertainty makes automation a challenging task. Integrating robotic welding with high-value manufacturing sector makes volume rise through pre-programmed repetitive performance on desired welding space. Further, the establishment of fully automated robotic-based welding operations with different configurations on controlled localization is the least available due to unviable cost. Hence, the proposed work concentrates on internet of things (IoT)-driven robotic tungsten inert gas (TIG) welding on stainless steel (SS) 304 by incorporating online programming (OP) with visual control schemes to classify the nature of weld quality using an artificial neural network. Continuous sensory-guided techniques with IoT high-level operator interface affords automated welding planning by using feature matching strategies. Area scan-based complementary metal oxide semiconductor (CMOS) cameras have been used to capture passive vision real-time images of the weld species for defect classification. In real-time, discrete reference workpiece and image feature extraction processes seem to be complicated in an unstructured welding environment. Hence, the present idea will enhance the efficiency of high product variance, but the accuracy of the automation relies on the weld image database. The proposed method (a) adaptively regulates its welding parameter variation on the welding trajectory path, (b) adapts and produces precise good weld workpieces with a 92% production rate with flaw-free welds and (c) initiates the automatic tuning of robot kinematics through IoT closed-loop online external control strategy. The proposed research experimental results confirm that fully automated IoT-driven robotic TIG welding affords good welding with an 88% improved quality rate through online passive vision-based image feature analysis.

Detection of aerosol and cloud features for the EarthCARE atmospheric lidar (ATLID): the ATLID FeatureMask (A-FM) product

Abstract. The EarthCARE satellite mission's objective is to retrieve profiles of aerosol and cloud physical and optical properties using the combination of cloud-profiling radar (CPR), high-spectral-resolution UV lidar (ATLID) and passive multi-spectral imager (MSI) data. Based on synergistic retrievals using data from these instruments, the 3D atmospheric cloud–aerosol state is estimated and then used to model the top-of-atmosphere (TOA) broadband radiances, which may then be compared to co-incident EarthCARE broadband radiometer (BBR) measurements. A high-spectral-resolution lidar enables the independent retrieval of extinction and backscatter but, being space based, suffers from relatively low signal-to-noise ratio (SNR) levels. The ATLID FeatureMask (A-FM) product provides a feature detection mask for the existence of atmospheric features within the lidar profiles based on a number of (statistical) image reconstruction techniques. Next to this, it also identifies those regions where the lidar beam has been fully attenuated and where the surface backscatter has impacted the measured lidar backscatter signals directly above the surface. From the pixels assigned as clear sky (with no features present above), the clear-sky-averaged profiles for the three ATLID channels, the co-polar Mie channel, the total cross channel and the co-polar Rayleigh channel are created. These feature-free or clear-sky profiles are useful for e.g., assessing the quality of the ATLID Level-1 (L1) attenuated backscatters. An important goal of the A-FM product is to guide smoothing strategies within downstream processors e.g., the ATLID profile retrieval (A-PRO) algorithm which directly follows A-FM within the EarthCARE Level-2 (L2) processing chain. Within the A-PRO algorithm, profiles of extinction, backscatter and linear depolarization ratio are retrieved. However, smoothing of the ATLID L1 attenuated backscatter is necessary since the SNR levels present at the ATLID native resolution are generally not sufficient for meaningful retrievals to be conducted. At the same time, to prevent biased retrievals, any smoothing procedure must respect the cloud–aerosol structure and avoid mixing strong features, e.g., clouds, and weak features, e.g., aerosol regions, together. The A-FM product provides the A-PRO algorithm with important information that is used to guide various smoothing procedures. To enable the processing of the large datasets from observation up to L2 retrievals, each EarthCARE orbit is separated into eight frames, divided at latitudes of 22.5∘ N and 22.5∘ S and 62.5∘ N and 62.5∘ S. As a secondary product, A-FM outputs can be used to conduct a frame-by-frame evaluation of the ATLID L1 cross-talk calibration, where an EarthCARE frame is one-eighth of a full orbit. This evaluation can be performed by comparing the retrieved clear-sky profiles to the expected channel profiles. The A-FM product has been applied to both synthetic data from the EarthCARE end-to-end simulator (ECSIM) and the L1 data from the Aeolus wind lidar mission. Comparisons against the ECSIM model truth indicate that A-FM has a percentage correctness > 90 % and is capable of reliably detecting aerosol and cloud regions within extinctions (> 10−5 m−1).

Performance Analysis and System Implementation for Energy-Efficient Passive UAV Radar Imaging System

Due to the superior flexibility and cost-efficiency, unmanned aerial vehicle (UAV) is becoming an indispensable platform for advanced remote sensing applications. In this paper, the performance and implementation of the energy-efficient passive UAV radar imaging system is investigated. Equipped with a synthetic aperture radar (SAR) receiver, the UAV platform passively reuses the backscattered signal of an external illuminator, and achieves SAR imaging and data communication. Firstly, we present the system concept and block diagram. Then, the imaging performance and feasibility are analyzed for the typical illuminators. It is found that the system can achieve distinct mission performance with different kinds of illuminators, which offers more alternatives for various mission requirements. A set of mission performance evaluators is established to comprehensively assess the capability of the system, including UAV navigation, passive SAR imaging and communication. An energy-efficient path planning method is then presented to generate a UAV path with optimized mission performance. Numerical simulations are conducted to verify the effectiveness of the performance evaluators and path planning method. Finally, a real implementation of the system is given. The imaging results of an airborne passive SAR experiment using external illuminator further validates the imaging capability and performance analysis of the system.