Near-infrared Camera Research Articles

The Real-Time Monitoring of the Laser-Induced Functionalization of Transparent Conductive Oxide Films.

Laser-induced functionalization using excimer laser irradiation has been widely applied to transparent conductive oxide films. However, exploring suitable irradiation conditions is time-consuming and cost-ineffective as there are numerous routine film fabrication and analytical processes. Thus, we herein explored a real-time monitoring technique of the laser-induced functionalization of transparent conductive oxide films. We developed two types of monitoring apparatus, electrical and optical, and applied them to magnetron-sputtered, Sn-doped In2O3 films grown on glass substrates and hydrogen-doped In2O3 films on glass or plastic substrates using a picosecond Nd:YAG pulsed laser. Both techniques could monitor the functionalization from a change in the properties of the films on glass substrates via laser irradiation, but electrical measurement was unsuitable for the plastic samples because of a laser-induced degradation of the underlying plastic substrate, which harmed proper electrical contact. Instead, we proposed that the optical properties in the near-infrared region are more suitable for monitoring. The changes in the optical properties were successfully detected visually in real-time by using an InGaAs near-infrared camera.

A Near-infrared-faint, Far-infrared-luminous Dusty Galaxy at z ∼ 5 in COSMOS-Web

A growing number of far-infrared (FIR) bright sources completely invisible in deep extragalactic optical surveys hint at an elusive population of z > 4 dusty, star-forming galaxies. Cycle 1 JWST surveys are now detecting their rest-frame optical light, which provides key insight into their stellar properties and statistical constraints on the population as a whole. This work presents the JWST Near Infrared Camera (NIRCam) counterpart from the COSMOS-Web survey to an FIR SCUBA-2 and Atacama Large Millimeter/submillimeter Array (ALMA) source, AzTECC71, which was previously undetected at wavelengths shorter than 850 μm. AzTECC71, among the reddest galaxies in COSMOS-Web with F277W − F444W ∼ 0.9, is undetected in NIRCam/F150W and F115W and fainter in F444W than other submillimeter galaxies identified in COSMOS-Web by 2–4 magnitudes. This is consistent with the system having both a lower stellar mass and higher redshift than the median dusty, star-forming galaxy. With deep ground- and space-based upper limits combined with detections in F277W, F444W, and the FIR including ALMA Band 6, we find a high probability (99%) that AzTECC71 is at z > 4 with . This galaxy is massive () and infrared-luminous (), comparable to other optically undetected but FIR-bright dusty, star-forming galaxies at z > 4. This population of luminous, infrared galaxies at z > 4 is largely unconstrained but comprises an important bridge between the most extreme dust-obscured galaxies and more typical high-redshift star-forming galaxies. If further FIR-selected galaxies that drop out of the F150W filter in COSMOS-Web have redshifts z > 4 like AzTECC71, then the volume density of such sources may be ∼3–10 × greater than previously estimated.

Selective enrichment strategy induces ultra-broadband NIR emission in Cr3+-doped multi-phase glass-ceramics for NIR spectroscopy applications

Near-infrared (NIR) spectroscopy has gained widespread application in food analysis, disease diagnosis, fingerprint analysis, and security monitoring. However, the lack of efficient, broadband NIR luminescent materials hinders the full potential of this technology. Here, an ultra-broadband and high-efficiency Cr3+-doped multi-phase glass-ceramics containing MgAl2O4, Al2SiO5, and SiO2 nanocrystals was discovered, which exhibited an ultra-broadband NIR emission (λem ∼ 900 nm) with a full width at half maximum more than 300 nm and a high internal quantum yield of 50.9% under the excitation of 465 nm blue light. Moreover, the integrated emission intensity at 100 °C and 150 °C can keep 88% and 77% of that at room temperature. The ultra-broadband, high efficiency, and thermally robust luminescence of this Cr3+-doped multi-phase glass-ceramics can be attributed to the selective enrichment of Cr3+ ions into different nanocrystals with octahedral sites, and medium electron-photon coupling effect. The NIR glass-ceramics-converted light-emitting diode constructed by the glass-ceramics combined with 465 blue LED chip produced an excellent NIR output and photoelectric conversion efficiency of 274 mW/1007 mW and 3.43%/2.79% at 100 mA/320 mA drive current, which demonstrated superior overall performance to the NIR device built by using the well-known NIR phosphors. Additionally, the NIR camera can capture the image of license plate and nectarine, as well as identify the residual drug content in the bottle under the irradiation of the NIR device constructed by the glass-ceramics. This work not only presented an ultra-broadband and high-efficiency NIR material but also highlights a design strategy to effectively enhance the efficiency and broadband characteristics of NIR glass-ceramics.

JWST/NIRCam Coronagraphy of the Young Planet-hosting Debris Disk AU Microscopii

High-contrast imaging of debris disk systems permits us to assess the composition and size distribution of circumstellar dust, to probe recent dynamical histories, and to directly detect and characterize embedded exoplanets. Observations of these systems in the infrared beyond 2–3 μm promise access to both extremely favorable planet contrasts and numerous scattered-light spectral features—but have typically been inhibited by the brightness of the sky at these wavelengths. We present coronagraphy of the AU Microscopii (AU Mic) system using JWST’s Near Infrared Camera (NIRCam) in two filters spanning 3–5 μm. These data provide the first images of the system’s famous debris disk at these wavelengths and permit additional constraints on its properties and morphology. Conducting a deep search for companions in these data, we do not identify any compelling candidates. However, with sensitivity sufficient to recover planets as small as ∼0.1 Jupiter masses beyond ∼2″ (∼20 au) with 5σ confidence, these data place significant constraints on any massive companions that might still remain at large separations and provide additional context for the compact, multiplanet system orbiting very close-in. The observations presented here highlight NIRCam’s unique capabilities for probing similar disks in this largely unexplored wavelength range, and they provide the deepest direct imaging constraints on wide-orbit giant planets in this very well-studied benchmark system.

Carbon Nanotube-Based Sensors for Intelligent Packaging

Aim: The aim of this project is to develop a gas-phase optical sensor for oxygen detection in intelligent packaging. The optical sensor will be based on near-infrared light that can penetrate through visibly opaque materials, including plastics, paper, and cardboard. An automated near-infrared camera will be used to precisely and quickly inform the user of any change in the integrity of packages that are vacuum-sealed or atmospherically modified. Method: The optical sensor is based on near-infrared fluorescence that is emitted from carbon nanotubes (CNTs). CNTs exhibit a sensitive and photostable fluorescence that is well suited for sensing applications. The CNTs are wrapped by one of two types of DNA, AT(15) and GT(15), through sonication. These wrappings control the responsivity of the CNTs to different gases while also solubilizing them for further processing. The resulting solutions are then drop-casted into a film. We subsequently investigate the response of the film in the presence of the target gas, oxygen, at different concentrations. Finally, we evaluate the selectivity of the sensor in the presence other gases including carbon dioxide, ethylene, and ammonia. Results: Our results reveal that the fluorescence intensity of the AT(15) and GT(15)-wrapped CNTs quenches upon the exposure of oxygen. Interestingly, we observe that the different CNT chiralities respond distinctly to the presence of oxygen. In particular, whereas some chiralities undergo an irreversible loss in fluorescence after several oxygen exposure cycles, the (8,6) chirality demonstrates stability over multiple cycles for both AT(15) and GT(15)-wrapped CNTs. Finally, our results show a concentration-dependent and selective response of both the AT(15)- or GT(15)-wrapped CNT sensors to the oxygen, as we observed no significant response to the other studied gases. Conclusion: We developed an optical, gas-phase sensor based on CNT fluorescence for intelligent food packaging. The sensor is selective to oxygen and demonstrates reversibility over multiple oxygen exposure cycles. These sensors can be used to monitor the integrity of packages that are vacuum-sealed or otherwise atmospherically modified. This technology can thus provide consumers and manufactures a means of preventing early spoilage and ensuring food quality.

Wide dynamic range and real-time reagent identification and imaging using multi-wavelength terahertz parametric generation and machine learning

In this study, we propose a technique for identifying and imaging reagents through shielding over a wide dynamic range using a real-time terahertz (THz) spectroscopy system with multi-wavelength THz parametric generation/detection and machine learning. To quickly identify reagents through shielding, the spectral information of the “detection Stokes beam” is used for reagent recognition via machine learning. In general THz wave-based reagent identification, continuous spectra are acquired and analyzed quantitatively by post-processing. In actual applications, however, such as testing for illicit drugs in mail, the technology must be able to quickly identify reagents as opposed to quantifying the amount present. In multi-wavelength THz parametric generation/detection, THz spectral information can be measured instantly using a “multi-wavelength detection Stokes beam” and near-infrared (NIR) camera. Moreover, machine learning enables reagent identification in real-time and over a wide dynamic range. Furthermore, by plotting the identification results as pixel values, the spatial distribution of reagents can be imaged at high speed without the need for post-processing.

Dynamic Wisp Removal in JWST NIRCam Images

The James Webb Space Telescope (JWST) near-infrared camera has been found to exhibit serious wisp-like structures in four of its eight short-wavelength detectors. The exact structure and strength of these wisps is highly variable with the position and orientation of JWST, so the use of static templates is non-optimal. Here we investigate a dynamic strategy to mitigate these wisps using long-wavelength reference images. Based on a suite of experiments where we embed a worst-case scenario median-stacked wisp into wisp-free images, we define suitable parameters for our wisp removal strategy. Using this setup we re-process wisp-affected public Prime Extragalactic Areas for Reionization and Lensing Science data in the North Ecliptic Pole Time Domain Field, resulting in significant visual improvement in our detector frames and reduced noise in the final stacked images.

Adaptive Resolution Enhancement for Visual Attention Regions Based on Spatial Interpolation.

Resolution enhancement is crucial for human vision. However, it can be resource-consuming in the display pipeline. Therefore, there is a need to develop a lightweight resolution improvement algorithm specifically targeting visual attention regions. This paper presents a spatial-interpolation-based algorithm to improve the resolution of the visual attention area. The eye-tracking system consists of a near-infrared camera and an event camera is proposed to obtain the 3D gaze vector and eye moving trajectory. Secondly, the observation coordinates are obtained by gaze vectors, and the visual attention region is defined by the sensitive field-of-view angle. Then, interpolation-based adaptive spatial resolution enhancement and contrast enhancement adjustment are performed in the visual attention area. Finally, the feasibility of the proposed method is tested on both qualitative and quantitative dimensions. The experimental results demonstrate that the proposed method can significantly improve the visual effects.

Deep-learning blurring correction of images obtained from NIR single-pixel imaging.

In challenging scenarios characterized by low-photon conditions or the presence of scattering effects caused by rain, fog, or smoke, conventional silicon-based cameras face limitations in capturing visible images. This often leads to reduced visibility and image contrast. However, using near-infrared (NIR) light within the range of 850-1550nm offers the advantage of reduced scattering by microparticles, making it an attractive option for imaging in such conditions. Despite NIR's advantages, NIR cameras can be prohibitively expensive. To address this issue, we propose a vision system that leverages NIR active illumination single-pixel imaging (SPI) operating at 1550nm combined with time of flight operating at 850nm for 2D image reconstruction, specifically targeting rainy conditions. We incorporate diffusion models into the proposed system to enhance the quality of NIR-SPI images. By simulating various conditions of background illumination and droplet size in an outdoor laboratory scenario, we assess the feasibility of utilizing NIR-SPI as a vision sensor in challenging outdoor environments.

Two Filters for Acquiring the Profiles from Images Obtained from Weak-Light Background, Fluorescence Microscope, Transmission Electron Microscope, and Near-Infrared Camera.

Extracting the profiles of images is critical because it can bring simplified description and draw special attention to particular areas in the images. In our work, we designed two filters via the exponential and hypotenuse functions for profile extraction. Their ability to extract the profiles from the images obtained from weak-light conditions, fluorescence microscopes, transmission electron microscopes, and near-infrared cameras is proven. Moreover, they can be used to extract the nesting structures in the images. Furthermore, their performance in extracting images degraded by Gaussian noise is evaluated. We used Gaussian white noise with a mean value of 0.9 to create very noisy images. These filters are effective for extracting the edge morphology in the noisy images. For the purpose of a comparative study, we used several well-known filters to process these noisy images, including the filter based on Gabor wavelet, the filter based on the watershed algorithm, and the matched filter, the performances of which in profile extraction are either comparable or not effective when dealing with extensively noisy images. Our filters have shown the potential for use in the field of pattern recognition and object tracking.

The JWST PEARLS View of the El Gordo Galaxy Cluster and of the Structure It Magnifies

The massive galaxy cluster El Gordo (z = 0.87) imprints multitudes of gravitationally lensed arcs onto James Webb Space Telescope Near-Infrared Camera (NIRCam) images. Eight bands of NIRCam imaging were obtained in the “Prime Extragalactic Areas for Reionization and Lensing Science” (“PEARLS”) program. Point-spread function–matched photometry across Hubble Space Telescope and NIRCam filters supplies new photometric redshifts. A new light-traces-mass lens model based on 56 image multiplicities identifies the two mass peaks and yields a mass estimate within 500 kpc of (7.0 ± 0.30) × 1014 M ⊙. A search for substructure in the 140 cluster members with spectroscopic redshifts confirms the two main mass components. The southeastern mass peak that contains the brightest cluster galaxy is more tightly bound than the northwestern one. The virial mass within 1.7 Mpc is (5.1 ± 0.60)×1014 M ⊙, lower than the lensing mass. A significant transverse velocity component could mean the virial mass is underestimated. We contribute one new member to the previously known z = 4.32 galaxy group. Intrinsic (delensed) positions of the five secure group members span a physical extent of ∼60 kpc. 13 additional candidates selected by spectroscopic/photometric constraints are small and faint, with a mean intrinsic luminosity ∼2.2 mag fainter than L *. NIRCam imaging admits a fairly wide range of brightnesses and morphologies for the group members, suggesting a more diverse galaxy population in this galaxy overdensity.

The JWST Early Release Science Program for Direct Observations of Exoplanetary Systems I: High-contrast Imaging of the Exoplanet HIP 65426 b from 2 to 16 μm

We present JWST Early Release Science coronagraphic observations of the super-Jupiter exoplanet, HIP 65426b, with the Near-Infrared Camera (NIRCam) from 2 to 5 μm, and with the Mid-Infrared Instrument (MIRI) from 11 to 16 μm. At a separation of ∼0.″82 (87 au), HIP 65426b is clearly detected in all seven of our observational filters, representing the first images of an exoplanet to be obtained by JWST, and the first-ever direct detection of an exoplanet beyond 5 μm. These observations demonstrate that JWST is exceeding its nominal predicted performance by up to a factor of 10, depending on separation and subtraction method, with measured 5σ contrast limits of ∼1 × 10−5 and ∼2 × 10−4 at 1″ for NIRCam at 4.4 μm and MIRI at 11.3 μm, respectively. These contrast limits provide sensitivity to sub-Jupiter companions with masses as low as 0.3M Jup beyond separations of ∼100 au. Together with existing ground-based near-infrared data, the JWST photometry are fit well by a BT-SETTL atmospheric model from 1 to 16 μm, and they span ∼97% of HIP 65426b's luminous range. Independent of the choice of model atmosphere, we measure an empirical bolometric luminosity that is tightly constrained between = −4.31 and −4.14, which in turn provides a robust mass constraint of 7.1 ± 1.2 M Jup. In totality, these observations confirm that JWST presents a powerful and exciting opportunity to characterize the population of exoplanets amenable to high-contrast imaging in greater detail.

NIRPed: A Novel Benchmark for Nighttime Pedestrian and Its Distance Joint Detection

In nighttime driving scenes, due to insufficient and uneven lighting, and the scarcity of high-quality datasets, the miss rate of nighttime pedestrian detection (PD) is much higher than that of daytime. Vision-based distance detection (DD) has the advantages of low cost and good interpretability, but the existing methods have low precision, poor robustness, and the DD is mostly performed independently of PD. A narrowband near-infrared (NIR) camera and an NIR lamp to relieve the impact of noisy visible light (VIS) and improve imaging quality have been selected; a LiDAR to obtain distance information has been embedded in the system; a nighttime driving scene pedestrian and its distance joint detection dataset NIRPed has been built. The NIRPed includes 146k pedestrian annotations, which is 3 times that of NightOwls, the largest VIS nighttime pedestrian dataset. Based on Faster-RCNN, a joint PD and DD method using monocular imaging has been proposed. The propo-sed method realizes the joint detection of pedestrian and its distance on the NIRPed dataset with the PD log-average miss rate and DD mean absolute error rate of 6.5% and 5.5%, respectively. For comparison, the joint detection method was implemented on other large-scale VIS pedestrian datasets as well. Moreover, compared with the existing vision-based DD methods, the proposed method is less affected by pedestrian distance and height, exhibits higher accuracy and robustness, and satisfied the ISO requirements for intelligent transportation systems (absolute error rate <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$&lt;$</tex-math> </inline-formula> 15%).

Fluorescence guided surgery using indocyanine green for pulmonary osteosarcoma metastasectomy in pediatric patients: A feasibility study

BackgroundIn osteosarcoma patients, resection of pulmonary metastases is considered necessary for long term survival. Radiologically detected lesions are sometimes difficult to identify intraoperatively, especially when no palpation is possible during thoracoscopy. In adults, fluorescence guided surgery (FGS) using indocyanine green (ICG) has been shown to be a safe method for intra-operative identification of pulmonary metastases of different primary tumors. Our aim is to determine the feasibility of using ICG for identification of pulmonary metastases in pediatric osteosarcoma patients. MethodsNine consecutive patients with pulmonary metastases received an intravenous dose of ICG 24 h preoperatively. We started with the adult dosage of 0.5 mg/kg and also used 1.0 mg/kg to confirm that maximum fluorescent signal was achieved. Intra-operatively and post-operatively, lesions were visualized with a near-infrared camera system. Fluorescence was quantified by calculating a tumor-to-background ratio (TBR). ResultsTwo (22%) patients underwent a thoracoscopy and seven (78%) underwent a thoracotomy. Five (56%) patients had a fluorescent metastasis during surgery. In four (44%) patients there were no fluorescent metastases. In two the metastases were necrotic. In the other two, intraoperative fluorescence was most likely hampered by the depth of the metastases. Ex vivo, all vital metastases were fluorescent and necrotic specimens were not. There was no difference between 1.0 mg/kg and 0.5 mg/kg concerning TBR. No adverse events occurred. ConclusionsICG for fluorescence guided metastasectomy of pulmonary osteosarcoma is a feasible procedure in the pediatric population. However, its additional value in intra-operative guidance still has to be investigated. Levels of evidenceLevel III evidence based on a Diagnostic test study: study without a universally applied “gold” standard.

A touchless user interface based on a near-infrared-sensitive transparent optical imager

Touchless user interfaces that are based on gestures typically rely on near-infrared cameras. However, such systems are often hampered by their limited field of view and high-accuracy calibration requirements. Here we report a touchless user interface that is based on a visually transparent near-infrared-sensitive organic photodetector array and can be used on top of a display. Optical transparency is achieved by using a printed copper grid as a bottom transparent conductive electrode and an array of patterned organic photodetector subpixels. Electro-optical modelling is used to optimize the design of the image sensor, leading to a photodetectivity of approximately 1012 Jones at 850 nm and a high visible-light transmittance of 70%. We show that the imager can be used as a penlight-controlled and gesture-controlled touchless user interface when combined with a commercial display.

The nature of an ultra-faint galaxy in the cosmic dark ages seen with JWST.

In the first billion years after the Big Bang, sources of ultraviolet (UV) photons are believed to have ionized intergalactic hydrogen, rendering the Universe transparent to UV radiation. Galaxies brighter than the characteristic luminosity L*(refs.1,2) do not provide enough ionizing photons to drive this cosmic reionization. Fainter galaxies are thought to dominate the photon budget; however, they are surrounded by neutral gas that prevents the escape of the Lyman-α photons, which has been the dominant way to identify them so far. JD1 was previously identified as a triply-imaged galaxy with a magnification factor of 13 provided by the foreground cluster Abell 2744 (ref. 3), and a photometric redshift of z ≈ 10. Here we report the spectroscopic confirmation of this very low luminosity (≈0.05 L*) galaxy at z = 9.79, observed 480 Myr after the Big Bang, by means of the identification of the Lyman break and redward continuum, as well as multiple ≳4σ emission lines, with the Near-InfraRed Spectrograph (NIRSpec) and Near-InfraRed Camera (NIRCam) instruments. The combination of the James Webb Space Telescope (JWST) and gravitational lensing shows that this ultra-faint galaxy (MUV = -17.35)-with a luminosity typical of the sources responsible for cosmic reionization-has a compact (≈150 pc) and complex morphology, low stellar mass (107.19 M⊙) and subsolar (≈0.6 Z⊙) gas-phase metallicity.

Qualify a NIR camera to detect thermal deviation during aluminum WAAM

This paper proposes to qualify the minimal quality deviation that can be detected by a near-infrared camera during aluminum wire arc additive manufacturing. First, a review of the literature is done to highlight the interest in monitoring the melt pool in industrial condition for thermal management during manufacturing. It points out the relevance of the use of a near-infrared camera for steels, but it has to be demonstrated for aluminum alloys. Indeed, the melt pool of the aluminum is significantly dimmer and less distinct than the melt pool of the steels. An experimental design is proposed to qualify the minimal quality deviation that can be detected on a thin wall. The chosen default to correlate with the thermal deviation is the width of the wall. A method is proposed to extract a thermal metric from the camera image and to analyze its sensitivity to a width deviation of the wall. The paper shows the correlation between the width of the wall and the thermal metric for different heat conditions. Moreover, the thermal metric is sensitive to width deviation either on the wall scale or on the bead scale. It indicates the relevance of a near-infrared camera to detect heat accumulation-induced width deviation during wire arc additive manufacturing of aluminum alloy.

Recent progress in lanthanide-based metal halide perovskites: Synthesis, properties, and applications

Metal halide perovskites (MHPs) have recently attracted significant interest, owing to their excellent optoelectronic properties and diverse applications, including photovoltaics, solid-state lighting emitting diodes (LEDs), and other optoelectronic applications. However, owing to the toxic nature of lead-based MHPs, lanthanide-based MHPs have recently emerged as an alternative, leading to new opportunities for emerging applications, such as in near-infrared (NIR) imaging, NIR cameras, white LEDs, photovoltaics, and information encryption. Moreover, lanthanide doping significantly enhances the stability and optical properties of MHPs. In this review, we have attempted to overview state-of-the-art synthesis strategies and investigate the structural, and optical properties of MHPs. Furthermore, several applications of MHPs, white LEDs, solar cells, and temperature sensors are discussed along with outlooks and future directions.

Validation of three-dimensional facial imaging captured with smartphone-based photogrammetry application in comparison to stereophotogrammetry system

Statement of problemThe development of facial scanners has improved capabilities to create three-dimensional (3D) virtual patients for accurate facial and smile analysis. However, most of these scanners are expensive, stationary and involve a significant clinical footprint. The use of the Apple iPhone and its integrated “TrueDepth” near-infrared (NIR) scanner combined with an image processing application (app) offers the potential to capture and analyze the unique 3D nature of the face; the accuracy and reliability of which are yet to be established for use in clinical dentistry. PurposeThis study was designed to validate both the trueness and precision of the iPhone 11 Pro smartphone TrueDepth NIR scanner in conjunction with the Bellus3D Face app in capturing 3D facial images in a sample of adult participants in comparison to the conventional 3dMDface stereophotogrammetry system. Material and methodsTwenty-nine adult participants were prospectively recruited. Eighteen soft tissue landmarks were marked on each participant's face before imaging. 3D facial images were captured using a 3dMDface system and the Apple iPhone TrueDepth NIR scanner combined with the Bellus3D Face app respectively. The best fit of each experimental model to the 3dMD scan was analyzed using Geomagic Control X software. The root mean square (RMS) was used to measure the “trueness” as the absolute deviation of each TrueDepth scan from the reference 3dMD image. Individual facial landmark deviations were also assessed to evaluate the reliability in different craniofacial regions. The “precision” of the smartphone was tested by taking 10 consecutive scans of the same subject and comparing those to the reference scan. Intra-observer and inter-observer reliabilities were assessed using the intra-class correlation coefficient (ICC). ResultsRelative to the 3dMDface system, the mean RMS difference of the iPhone/Bellus3D app was 0.86 ± 0.31 mm. 97% of all the landmarks were within 2 mm of error compared with the reference data. The ICC for intra-observer reproducibility or precision of the iPhone/Bellus3D app was 0.96, which was classified as excellent. The ICC for inter-observer reliability was 0.84, which was classified as good. ConclusionsThese results suggest that 3D facial images acquired with this system, the iPhone TrueDepth NIR camera in conjunction with the Bellus3D Face app, are clinically accurate and reliable. Judicious use is advised in clinical situations that require high degrees of detail due to a lack of image resolution and a longer acquisition time. Generally, this system possesses the potential to serve as a practical alternative to conventional stereophotogrammetry systems for use in a clinical setting due to its accessibility and relative ease of use and further research is planned to appraise its updated clinical use.

A comparative analysis of near-infrared image colorization methods for low-power NVIDIA Jetson embedded systems.

The near-infrared (NIR) image obtained by an NIR camera is a grayscale image that is inconsistent with the human visual spectrum. It can be difficult to perceive the details of a scene from an NIR scene; thus, a method is required to convert them to visible images, providing color and texture information. In addition, a camera produces so much video data that it increases the pressure on the cloud server. Image processing can be done on an edge device, but the computing resources of edge devices are limited, and their power consumption constraints need to be considered. Graphics Processing Unit (GPU)-based NVIDIA Jetson embedded systems offer a considerable advantage over Central Processing Unit (CPU)-based embedded devices in inference speed. For this study, we designed an evaluation system that uses image quality, resource occupancy, and energy consumption metrics to verify the performance of different NIR image colorization methods on low-power NVIDIA Jetson embedded systems for practical applications. The performance of 11 image colorization methods on NIR image datasets was tested on three different configurations of NVIDIA Jetson boards. The experimental results indicate that the Pix2Pix method performs best, with a rate of 27 frames per second on the Jetson Xavier NX. This performance is sufficient to meet the requirements of real-time NIR image colorization.