Resolution Optical Tomography Research Articles

AOHSR: attention mechanism-based optical image-guided hyperspectral image super-resolution

ABSTRACT With the rapid development of hyperspectral imaging technology, hyperspectral image (HSI) has been applied in various fields. However, due to the constraint of hyperspectral imaging devices, the spatial resolution of HSI remains too low to accurately meet the needs of target detection and recognition, which shackles the further application of HSI. In this paper, an optical image-guided HSISR algorithm based on the attention mechanism (AOHSR) was proposed in order to effectively improve the resolution of HSI. With the help of the attention mechanism, the proposed algorithm can effectively retain the spectral information of HSI and the spatial information of the optical image. Even without high spatial resolution optical imaging in the test stage, favourable reconstruction results can still be achieved. Firstly, the framework of the proposed optical image-guided HSI SR algorithm based on the attention mechanism was introduced. The algorithm consists of three modules: spectral reservation module (SRM), optical image guidance module (OIGM) and spatial-spectral recovery module (SSRM). The SRM uses an improved channel attention mechanism to extract spectral features from low-resolution (LR) HSIs to preserve spectral information. Through an improved spatial attention mechanism, the OIGM extracts spatial information from high-resolution (HR) optical images, supplementing the information extracted from LR HSI. The SSRM is used to fuse the spectral information on HSI and the spatial information on optical images to reconstruct HR HSI. Then, a joint training algorithm for reconstruction loss and optical image content loss was also proposed, which can effectively guide to learn the reconstruction of detailed information of the spatial texture while ensuring the preservation of spectral information. The results of experiments on three open datasets reveal that the HSIs reconstructed by the proposed network performed better than the existing algorithms regardless of whether optical images in the test stage exist.

High-resolution mapping of forest structure from integrated SAR and optical images using an enhanced U-net method

Forest structure is an essential part of biodiversity and ecological analysis and provides crucial insights to address challenges in these areas. Modern sensor technologies unlock new possibilities for more advanced vegetation monitoring. This study examines the potential of single high resolution X-band synthetic aperture radar (SAR) and optical images for pixel-wise mapping of four forest structure attributes (height, average height, fractional cover, and density) at a striking 0.5 m resolution. The study site is situated in Western Norway, hosting trees from flatlands to elevated mountainous areas and in-between. The proposed model architecture, called PSE-UNet, is a modified UNet incorporating key components from state-of-the-art deep learning from the field of forest structure monitoring. A comparative analysis involving state-of-the-art models shows promising results with MAE% between 21.5 and 24.7, depending on the variable.

Improved design method for suppressing optical focal spots and experimental verification

Pupil filtering is an effective method to modulate the 3D point spread function distribution of an optical system. Based on vector Debye-Wolf diffraction integral and a new fusion optimization algorithm, an improved method is described for efficiently designing the most widely-used concentric multi-belt pupil filters. The main advantage of this method is that it actively selects the minimum belt width and the total belt number for facilitating low-cost batch processing. Pupil filters for visible and near-infrared bands have been separately designed for improving the spatial resolution of optical imaging and ultrafast laser processing. The method has been experimentally demonstrated for suppressing the optical focal spot. The proposed method can be readily modified for designing more sophisticated multi-level pupil filters for practical applications in high-resolution imaging and fine laser micromachining.

Radical resection of trigeminal schwannoma at the cerebellopontine angle with support of the digital robotic exoscope Synaptive Modus V system: A case report and literature review

We report on a 67-year-old woman who experienced drowsy mental status, facial numbness, and hearing loss on the right side; the symptom gradually worsened over the last 4 years. Brain magnetic resonance imaging revealed a 4.8 × 1.8 × 2.6 cm lesion located in the right cerebellopontine angle. She underwent surgery with the retrosigmoid suboccipital approach and support from the digital robotic exoscope Synaptive Modus V system. To the best of our knowledge, this is the first reported case that used the robotic exoscope system in Vietnam, and also in Asia. We performed radical resection of the tumor, the surgery position and the pathology result concluded the diagnosis was trigeminal schwannoma. After 30 months of follow-up, she fully recovered and the magnetic resonance imaging showed radical resection of the tumor. The aim of this study is to share our experience with the robotic exoscope system, which can improve optical field and image resolution, hence creating an opportunity for surgery that otherwise is impossible. The application of this robotic exoscope system is a breakthrough in neurosurgery in developing countries, such as Vietnam.

Modelling the Light Scattering Behavior of Transmission-Mode GaAs Photocathode Under the AlGaAs Window Layer Rough Surface

To improve the understanding of the optical image resolution of transmission-mode GaAs photocathode, by establishing the surface scattering analysis model of AlGaAs window layer, we have researched the effect of the surface height distribution variance σ on scattering surface transfer function (STF) and point spread function (PSF) of transmission-mode GaAs photocathode. The simulation results show that the decrease of surface height distribution variance σ is beneficial to improve the optical image resolution. This improvement is mainly attributed to the decrease in input light energy attenuation and spatial diffusion caused by smaller surface height distribution variance σ, and thus the signal to noise ratio of scattering degraded optical image is increased.

Shocks and Photoionization of the Inner 650 au Jet of the Interacting Binary Star R Aquarii from Multiwavelength Hubble Space Telescope Observations

Astrophysical jets are present in a range of environments, including young stellar objects, X-ray binaries, and active galactic nuclei, but their formation is still not fully understood. As one of the nearest symbiotic binary stars, R Aquarii (D ∼ 220 pc) offers a unique opportunity to study the inner region within ∼600 au of the jet source, which is particularly crucial to our understanding of nonrelativistic jet formation and origin. We present high-angular resolution UV and optical imaging from the Hubble Space Telescope in six emission-line regions of the inner jet. Using these observations to obtain a range of representative line ratios for our system and kinematic data derived from a comparison with previous studies, we model the shocked gas in order to determine the relative roles of shock heating and photoionization in the R Aquarii system. We find that our shock models suggest that a nonzero magnetic field is needed to describe the measured line ratios. We also find that the Mg ii λλ2795,2802 intensities are overpredicted by our models for most of the jet regions, perhaps because of depletion onto grains or to opacity in these resonance lines.

Complexity of cortical wave patterns of the wake mouse cortex

Rich spatiotemporal dynamics of cortical activity, including complex and diverse wave patterns, have been identified during unconscious and conscious brain states. Yet, how these activity patterns emerge across different levels of wakefulness remain unclear. Here we study the evolution of wave patterns utilizing data from high spatiotemporal resolution optical voltage imaging of mice transitioning from barbiturate-induced anesthesia to wakefulness (N = 5) and awake mice (N = 4). We find that, as the brain transitions into wakefulness, there is a reduction in hemisphere-scale voltage waves, and an increase in local wave events and complexity. A neural mass model recapitulates the essential cellular-level features and shows how the dynamical competition between global and local spatiotemporal patterns and long-range connections can explain the experimental observations. These mechanisms possibly endow the awake cortex with enhanced integrative processing capabilities.

UAV data collection parameters impact on accuracy of Scots pine stand mensuration

A wide range of UAV systems used for forest research requires unified approaches to data collection. The research aims to determine the optimal parameters for UAV data collection to obtain accurate information about stands, considering the cost of resources for its collection. The process of collecting remote sensing data consisted of nine combinations divided into three levels of overlap and three levels of spatial resolution (survey altitude) and changing the degree of filtering of a dense point cloud during image processing. Individual tree detectingin the stand was performed using the R programming language and the ForestTools package. The results of the assessment of the dependence of the radius of tree crowns on their height were used to set the parameters of the variable filter function for finding local maxima for Scots pine stands. Errors in the identification of treetops were estimated using the F-score. The identified heights were compared with the field data of the ground survey. The proportion of classified digital elevation model DEM in the dense point cloud was reduced from the total area of the test site using images of 4.1 cm/pix spatial resolution (150 m survey altitude). The study presents the results of assessing the impact of spatial resolution of optical images collected from UAVs and their overlap on the results of measurements of stands parameters. It is determined that a photogrammetric survey with input images with a longitudinal overlap of less than 90% is not appropriate for the study of forest areas due to the impossibility of aligning all images. The results of the assessment of tree accounting in the stand showed that it is most appropriate to use images with a spatial resolution of up to 3.3 cm/pix (120 m survey altitude), otherwise, the proportion of missed treetops increases. Reducing the spatial resolution of remote sensing data leads to an increase in errors in determining the height of individual trees, and the average heights of the experimental plots had the same trend. Given the combination of the assessed factors, it is not recommended to use images with a spatial resolution of more than 3.3 cm/pix for forestry research due to increased errors in the individual tree detection and tree height determination. The results obtained can be used to select data collection parameters for research on Scots pine stands to assess their growing stock and phytomass

Data Fusion for Satellite-Derived Earth Surface: The 2021 Topographic Map of Etna Volcano

We present a new automatic procedure for updating digital topographic data from multi-source satellite imagery, which consists in the production of Digital Surface Models (DSMs) from high resolution optical satellite images, followed by a context-aware fusion that exploits the complementary characteristics of the multi-source DSMs. The fused DSM minimizes blunders and artifacts due to occlusions (e.g., the presence of clouds, snow or ash plumes) in the source images, resulting in improved accuracy and quality versus those that are not merged. The procedure has been tested to produce the 2021 digital topography of Mt Etna, whose summit area is constantly changing and shows the new peak of 3347 m on the north rim of the South East Crater. We also employ the 2021 DSM to measure the volcanic deposits emplaced in the last five years, finding about 120 million cubic meters, with a yearly average volume of about 24 million cubic meters in agreement with the large eruptive rates registered at Mt Etna since the nineteen seventies. The flexibility and modularity of the presented procedure make it easily exportable to other environmental contexts, allowing for a fast and frequent reconstruction of topographic surfaces even in extreme environments.

Ultra-diffuse Galaxies as Extreme Star-forming Environments. I. Mapping Star Formation in H i-rich UDGs

Ultra-diffuse galaxies (UDGs) are both extreme products of galaxy evolution and extreme environments in which to test our understanding of star formation. In this work, we contrast the spatially resolved star formation activity of a sample of 22 H i-selected UDGs and 35 low-mass galaxies from the NASA Sloan Atlas (NSA) catalog within 120 Mpc. We employ a new joint spectral energy distribution fitting method to compute star formation rate and stellar mass surface density maps that leverage the high spatial resolution optical imaging data of the Hyper Suprime-Cam Subaru Strategic Program and the UV coverage of the Galaxy Evolution Explorer, along with H i radial profiles estimated from a subset of galaxies that have spatially resolved H i maps. We find that UDGs have low star formation efficiencies as a function of their atomic gas down to scales of 500 pc. We additionally find that the stellar mass-weighted sizes of our UDG sample are unremarkable when considered as a function of their H i mass—their stellar sizes are comparable to NSA dwarfs at fixed H i mass. This is a natural result in the picture where UDGs are forming stars normally, but at low efficiencies. We compare our results to predictions from contemporary models of galaxy formation, and find in particular that our observations are difficult to reproduce in models where UDGs undergo stellar expansion due to vigorous star formation feedback should bursty star formation be required down to z = 0.

Correction of multi-scale sunglint reflections from the water surface in airborne high-spatial resolution optical images.

Airborne optical images (AOI) are often with complex sunglint reflections, which brings a certain influence to watercolor retrieval. This includes the sunglint reflection with water surface statistical distribution characteristics caused by imaging viewing angles differences, with high spatial resolution surface discrete characteristics sharing similar viewing angles, and the surface Fresnel reflection sunglint differences caused by the skylight difference during the flight of unmanned aerial vehicles. Aiming at the multiscale optical characteristics of sunglint reflection in high spatial resolution AOI, based on multi-path optical radiation transmission, the sunglint reflection interference from three different imaging processes is clarified. We developed a correction method to eliminate these different sunglint reflections on water surfaces and improve the reflectivity accuracy. The comparison with the in situ measured remote sensing reflectance of water indicated that the root mean square error (RMSE) was reduced from 0.0009 sr-1 to 0.0004 sr-1, and the mean relative error (MRE) decreased from 21.8% to 15.7%. This method has also been applied to correct the Airborne Visible Infrared Imaging Spectrometer (AVIRIS) images, showing good applicability. The method is fast, effective, and without auxiliary parameters, which provides a correction reference for different surface sunglint corrections of various AOI.

A-IGZO thin-film transistors with transparent ultrathin Al/Ag bilayer source and drain for active neural interfaces

Electro-optical neural interface technologies based on transparent electronics have been developed to take advantage of both high spatial resolution of optical cellular imaging by microscopes and high temporal resolution of electrical neural recordings. Recently, active-matrix systems based on amorphous indium gallium zinc oxide (a-IGZO) thin-film transistors (TFTs) have been suggested for high-density electrical neural recordings owing to the high mobility and optical transparency of the IGZO. However, conventional metallic source and drain electrodes forming ohmic contacts with the a-IGZO are the limiting factors of the overall system transparency because the electrodes have substantial portions in the TFT structures. In this work, we propose an ultrathin metal bilayer as the transparent source and drain electrodes of the a-IGZO TFTs for fully transparent TFT-based electro-optical neural interfaces. The ultrathin metal bilayer electrodes consist of 2.5–4.5 nm-thick aluminum as a seed layer and 8 nm-thick silver. The ultrathin Al/Ag bilayer suppressed localized surface plasmonic resonance, showing 40–70% of transmittance in the range of 350–700 nm and thus allowing us to observe cultured neurons through the transparent electrodes. We also confirmed that the ultrathin Al/Ag electrodes form decent ohmic contacts to the IGZO, showing width-normalized contact resistance of 2.9 kΩ-cm which is similar to the previously reported other transparent S/D electrodes. The a-IGZO TFTs with the ultrathin Al/Ag showed the highest linear mobility of 3.9 cm2/Vs of in long channels and 0.2–0.64 cm2/Vs in short channels. The gate-bias normalized cut-off frequency was 8–26 kHz/V at Lch = 20 μm, which would be sufficient for recording a wide range of neural signals.

Discrimination of Oceanic Whitecaps Derived by Sea Surface Wind Using Sentinel‐2 MSI Images

AbstractOceanic whitecaps, as a manifestation of the wind‐wave breaking process and the medium of air‐sea exchange, play an important role in sea surface research. The observational data of oceanic whitecap coverage are generally in situ photographs or videos. The use of spaceborne optical sensors to capture oceanic whitecaps could provide more spatial distribution and dynamic marine environment information. In this study, more than 100 Sentinel‐2 Multi‐Spectral Instrument (MSI) images and corresponding synchronous buoy wind speed data were collected to investigate oceanic whitecaps. A curvature image processing method was employed to successfully identify oceanic whitecaps in MSI images and the whitecap coverage was estimated based on the whitecap recognition results. We established a power‐law model of MSI‐estimated whitecap coverage (W) and whitecap number density with buoy‐measured wind speed at a height of 10 m above the sea surface (U10). In addition, the differences between the MSI‐derived model and in situ measurement‐derived models which are mainly caused by the scale effect of optical remote sensing, are discussed. The whitecap‐wind model demonstrates that MSI images can improve the quantification of sea surface wind speed with high spatial resolution. MSI images were used to estimate regional high‐spatial resolution (4 km) wind speeds, and the merged results (0.25°) were verified with the hourly wind products of the fifth generation European ECMWF (Centre for Medium‐Range Weather Forecasts) atmospheric reanalysis (ERA5). Moreover, the influence of sunglint on whitecap recognition and whitecap coverage was also analyzed. The reflectance of whitecap‐affected pixels in MSI images increased obviously with wind speed compared with background seawater in weak sunglint reflection area. These results indicated that the parameters of oceanic whitecaps derived from high‐spatial resolution optical images can be used to estimate wind speed and provide a new approach for monitoring marine dynamic environments in the future.

Off‐Fault Deformation in Regions of Complex Fault Geometries: The 2013, Mw7.7, Baluchistan Rupture (Pakistan)

AbstractObservations of recent earthquake surface ruptures show that ground deformations include a localized component occurring on faults, and an off‐fault component affecting the surrounding medium. This second component is also referred to as off‐fault deformation (OFD). The localized component generally occurs on complex networks of faults that connect at depth onto a unique fault plane, whereas OFD consists of distributed fracturing and diffuse deformation of the bulk volume, and occurs over scales of hundreds of meters to kilometers around the faults. High‐resolution optical image correlation presents a unique potential to characterize the complexity of the surface displacements, including on‐fault displacements and OFDs. In this study, we used sub‐pixel correlation of 0.5‐m resolution optical images to measure the surface displacement field with a <20 cm accuracy for a 30‐km long section of the 2013 Mw7.7 Baluchistan, Pakistan, rupture. Our results document significant variability in the fault displacements, associated with large proportions of OFD in regions of fault geometrical complexity. Conversely, in regions where the fault geometry is simple, surface deformation is entirely accommodated by the primary faults with 0% OFD. When combining the localized deformation on faults with the OFD, we show that the total surface displacement budget is constant along the strike of the rupture, despite strong variations observed in the rupture geometry. Based on this analysis, we propose an idealized scenario of earthquake surface deformation as a function of the rupture geometrical variations.

Object detection in high resolution optical image based on deep learning technique

Deep learning-based object detection in high resolution optical imagery is an active research frontier. Dataset for object detection is fundamentally important to drive deep learning models. Compared to datasets in computer vision, there is a lack of datasets for object detection in the remote sensing field. This work produced a high-quality dataset for object detection based on the high-resolution remote sensing images of the TripleSAT. The spatial resolution of the TripleSAT images is 0.8 ​m and the dataset for object detection includes 3 categories: wind turbine, airplane and oil storage tank. 3583 TripleSAT images are used, in which 7320 instances are manually annotated, to compose a TripleSAT dataset. To test the performance of the TripleSAT dataset, a state-of-the-art deep learning model, the RetinaNet was used with the PyTorch framework. Our results show that the mean average precision of the RetinaNet for wind turbines, airplanes and oil storage tanks are 93.47%, 92.8% and 96.55%, respectively. The results demonstrate the capability of the TripleSAT satellite images in producing datasets for deep learning models. Dataset made from single remote sensing sensor can achieve high accuracy and fast detection. The proposed dataset, including wind turbine, oil storage tank and airplane is meaningful supplement for data on hazard-affected bodies.

PATLAB: A graphical computational software package for photoacoustic computed tomography research

Photoacoustic tomography (PAT) provides high resolution optical images of tissue at depths of up to several centimetres. This modality has been of interest to researchers for at least 30 years and is still the subject of intensive research. However, PAT researchers lack access to a comprehensive open-source graphical simulation and reconstruction software package. In this article, we introduce PATLAB, an open-source MATLAB-based graphical software package that can perform both PAT simulation and image reconstruction. PATLAB is simple to use yet is capable of complex PAT data processing tasks and offers advanced users a framework to build and test new methods.

Quantifying ocean surface green tides using high-spatial resolution thermal images.

The use of thermal remote sensing for marine green tide monitoring has not been clearly demonstrated due to the lack of high-resolution spaceborne thermal observation data. This problem has been effectively solved using high-spatial resolution thermal and optical images collected from the sensors onboard the Ziyuan-1 02E (ZY01-02E) satellite of China. The characteristics and principles of spaceborne thermal remote sensing of green tides were investigated in this study. Spaceborne thermal cameras can capture marine green tides depending on the brightness temperature difference (BTD) between green tides and background seawater, which shows a positive or negative BTD contrast between them in the daytime or nighttime. There is a significant difference between thermal and optical remote sensing in the ability to detect green tides; compared with optical remote sensing, pixels containing less algae are not easily distinguishable in thermal images. However, there is a good linear statistical relationship between the BTD and the optical parameter (scaled algae index of virtual baseline height of floating macroalgae, SAI(VB)) of green tides, which indicates that the BTD can be used to quantify the green tide coverage area in a pixel or biomass per area. Then, the uncertainty in thermal quantitative remote sensing of green tides was clarified according to the pixel-to-pixel relationship between optical and thermal images. In a mixed pixel, green tide coverage and algal thickness have different thermal signal responses, which results in this uncertainty. In future research, more thermally remotely sensed images with high spatial resolution are needed to increase the observation frequency in the daytime and nighttime for the dynamic monitoring of green tides.

Anti-scattering light focusing with full-polarization digital optical phase conjugation based on digital micromirror devices.

The high resolution of optical imaging and optogenetic stimulation in the deep tissue requires focusing light against strong scattering with high contrast. Digital optical phase conjugation (DOPC) has emerged recently as a promising solution for this requirement, because of its short latency. A digital micromirror device (DMD) in the implementation of DOPC enables a large number of modulation modes and a high speed of modulation both of which are important when dealing with a highly dynamic scattering medium. Here, we propose full-polarization DOPC (fpDOPC) in which two DMDs simultaneously modulate the two orthogonally polarized components of the optical field, respectively, to mitigate the effect of depolarization caused by strong scattering. We designed a simple system to overcome the difficulty of alignment encountered when modulating two polarized components independently. Our simulation and experiment showed that fpDOPC could generate a high-contrast focal spot, even though the polarization of light had been highly randomized by scattering. In comparison with the conventional method of modulating the polarization along a particular direction, fpDOPC can improve the peak to background ratio of the focal spot by a factor of two. This new technique has good potential in applications such as high-contrast light focusing in vivo.

Single Date Wind Turbine Detection on Sentinel-2 Optical Images

ESA's Sentinel-2 satellites have been in orbit for six years, acquiring massive amounts of data all over the world. They are a formidable tool for mass detection as they are freely available and cover the entire world. Given their future role in the energetic transition and their spread over countries or continents, wind turbines are natural candidates for such studies. We detail the implementation of a single-date automatic wind turbine detector for low resolution optical satellite images based on an a contrario approach, exploiting the geometry of wind turbines' shadows and hubs.

MULTI-DATE WIND TURBINE DETECTION ON OPTICAL SATELLITE IMAGES

Abstract. Satellite imaging is shifting from the photo-interpreter era to one of automatic monitoring. Indeed, the vast amount of data provided by the recent constellations of satellites, performing recurrent observation of every point on the globe, can only be handled by automatic methods; controlling false detections is thus crucial. The low costs of those satellites often imply lower resolution; the fusion of multi-date images can compensate to some extent the low resolution. Given their future role in the energetic transition and their spread over countries or continents, monitoring wind turbines is a natural candidate for such studies. This work details an algorithm for automatic, multi-date wind turbine detection on low resolution optical satellite images. The method is based on the a contrario statistical approach to provide a control of false detections and exploits the geometry of wind turbines’ shadows and hubs.