Point-like Features Research Articles

Comparative Study of GPR Acquisition Methods for Shallow Buried Object Detection

This paper investigates the use of ground-penetrating radar (GPR) technology for detecting shallow buried objects, utilizing an air-coupled stepped frequency continuous wave (SFCW) radar system that operates within a 2 GHz bandwidth starting at 500 MHz. Different GPR data acquisition methods for air-coupled systems are compared, specifically down-looking, side-looking, and circular acquisition strategies, employing the back projection algorithm to provide focusing of the acquired GPR data. Experimental results showed that the GPR can penetrate up to 0.6 m below the surface in a down-looking mode. The developed radar and the back projection focusing algorithm were used to acquire data in the side-looking and circular mode, providing focused images with a resolution of 0.1 m and detecting subsurface objects up to 0.3 m below the surface. The proposed approach transforms B-scans of the GPR-based data into 2D images. The provided approach has significant potential for advancing shallow object detection capabilities by transforming hyperbola-based features into point-like features.

El Gordo needs El Anzuelo: Probing the structure of cluster members with multi-band extended arcs in JWST data

Gravitational lensing by galaxy clusters involves hundreds of galaxies over a large redshift range and increases the likelihood of rare phenomena (supernovae, microlensing, dark substructures, etc.). Characterizing the mass and light distributions of foreground and background objects often requires a combination of high-resolution data and advanced modeling techniques. We present the detailed analysis of a prominent quintuply imaged dusty star-forming galaxy ($ mainly lensed by three members of the massive galaxy cluster ACT-CL\,J0102$-$4915, also known as d =0.87$). We leverage JWST/NIRCam images, which contain lensing features that were unseen in previous HST images, using a Bayesian, multi-wavelength, differentiable and GPU-accelerated modeling framework that combines (lens modeling) and (field model and inference) software packages. For one of the deflectors, we complement lensing constraints with stellar kinematics measured from VLT/MUSE data. In our lens model, we explicitly include the mass distribution of the cluster, locally corrected by a constant shear field. We find that the two main deflectors (L1 and L2) have logarithmic mass density slopes steeper than isothermal, with $ L1 and $ L2 We argue that such steep density profiles can arise due to tidally truncated mass distributions, which we probe thanks to the cluster lensing boost and the strong asymmetry of the lensing configuration. Moreover, our three-dimensional source model captures most of the surface brightness of the lensed galaxy, revealing a clump with a maximum diameter of $400$ parsecs at the source redshift, visible at wavelengths $ rest mu m. Finally, we caution on using point-like features within extended arcs to constrain galaxy-scale lens models before securing them with extended arc modeling.

VolCID: A MATLAB-based GUI for the detection of volcanic vent clusters

In this work, a MATLAB Graphic User Interphase (GUI) is presented to support the identification of a clustered structure of eruptive centers for which only their spatial coordinates are known. The GUI, called VolCID (Volcano Cluster IDentification), combines an unsupervised classification scheme with user approval at various stages of the analysis. It is not necessary to make any assumption about the total number of clusters expected or about other characteristics of the clusters (as, for example, minimum cluster size) at the beginning of any analysis. Due to its flexibility, VolCID allows exploration of the effect of different distances of reference and to assess the possibility of chaining effects in a systematic and reproducible form. The combination of objective calculations and subjective choices therefore helps the operator to bring forward underlying assumptions (e.g., the expected number of clusters, general shape of each cluster, number of volcanoes per area of specific clusters) that often remain unstated in these types of studies. VolCID also incorporates the possibility of completing the analysis superimposed to an image of geologic significance, as well as to complete analysis of volcanic features on other planets. By facilitating the exploration of distribution schemes, VolCID might be a helpful tool that can be used to further our understanding of volcanic phenomena (or any other geologic feature that can be represented by point-like features) on Earth and other planets as well.

Extrahepatic portal vein aneurysm in which the acute thrombogenic process triggered by trauma confirmed by abdominal ultrasonography: a case report.

Extrahepatic portal vein aneurysm (PVA) is a rare condition in which the extrahepatic portal vein is partially dilated into a sac-like or spindle-like shape. Usually, patients are followed, but surgery is considered in cases of rupture, thrombus, or enlargement. We report a case of thrombus formation in an extrahepatic portal vein aneurysm following trauma that resulted in regression of the aneurysm and extrahepatic portal vein occlusion. Immediately after the trauma, ultrasonography showed moderately hyperechoic structures and comet signs along the vessel wall of the aneurysm and turbulent blood flow in the aneurysm, like in a whirlpool. There were floating point-like echogenic features, which were presumed to be microthrombi. In other words, the trauma might have triggered Virchow's triad: changes in the vessel wall, changes in blood properties, and blood stagnation. This is a valuable case in which ultrasonography imaging revealed interesting changes during the thrombus formation process inside an extrahepatic portal vein aneurysm. The aneurysm's size was reduced by thrombus-induced organization, but the main trunk of the portal vein became deficient in blood flow, resulting in extrahepatic portal vein occlusion. This case is suggestive of the mechanism of extrahepatic portal vein occlusion.

Infrared Moving Small Target Detection Based on Consistency of Sparse Trajectory

Infrared search and track (IRST) systems require reliable detection of small targets in complex backgrounds. Outlier based methods are prone to high false positive rates due to the resemblance of point-like background features to small targets. The difference image-based method is an effective approach for suppressing point-like background interference; however, it has limitations in detecting slow-moving targets. In this letter, a novel sparse trajectory is proposed for moving target detection in IR videos. With a trajectory growing strategy, two kinds of trajectories from difference images, namely short sparse trajectories and long sparse trajectories, are correlated to avoid the slow-moving targets being dismissed. The strategy matches the trajectories based on the sparse trajectory intensity composed of similarity measures and optical flow consistency. Finally, real targets are extracted from candidate trajectories using trajectory filtering. Experimental results show that, in the scene with point-like background features, our method achieves the best detection rate and lowest false alarm compared to state-of-the-art methods.

An ATA Search for a Repetition of the Wow Signal

Abstract The Allen Telescope Array was used to search for signals with characteristics similar to the “Wow” signal, the best candidate for an extraterrestrial radio signal found during Ohio State University’s (OSU’s) seven-year 21 cm 10-kHz channel sky survey for signals possibly due to extraterrestrial intelligence. While previous follow-up searches have reported null results, our observations covered a 5 deg2 field of view that extends well beyond the locus of all consistent directions of arrival (DOAs) of the original signal, and covered a 10 MHz bandwidth four times wider than the widest prior follow-up observations, using 12.8 kHz channels approximating OSU’s 10 kHz resolution. Approximately 100 hours of data were accumulated, considerably more time than any previous follow-up campaigns. We used interferometric imaging with an angular resolution of approximately 007 and automated feature-finding to search for point-like features mimicking a Wow repetition, obtaining single-channel sensitivity of ∼1.2 Jy for one minute averages. This allows identification of the DOA of a very brief repetition, with strong discrimination from radio interference, and eliminates the usual constraint that the signal must persist for long periods of time (around one hour) before the true DOA can be verified (because interfering signals from the horizon sometimes masquerade as coming from the look direction). No point-like features significantly exceeding the noise were found inside the full width at half maximum of the OSU fields of view, although one 26σ point-like feature was detected during one 10 second integration about 1/3° away.

On the relationship between volcanic pointlike features and the crust-mantle boundary at the Pinacate Volcanic Field, Sonora, México

A description of numerical methods is presented, which applied to data from a digital elevation model, helps to enhance the presence of pointlike features in a volcanic field. It was assumed in the development of the method, that the scalar field representing the topography in a digital elevation model is the vertical gradient of a harmonic function u. The second derivatives of u, in orthogonal directions, x, y, z, are computed in the wavenumber domain, via the two-dimensional Fourier transform, to obtain the gradient tensor of u. At every point in the digital elevation model, the gradient tensor components form a 3 by 3 symmetric matrix. I use the singular value decomposition of these matrices to calculate its eigenvalues to obtain their principal invariants. The square of the second invariant is found as an excellent choice to select pointlike features, likely related to volcanic vents. The method is fully described and illustrated using a digital elevation model with a horizontal resolution of 25 m from the Pinacate volcanic field in northwestern Sonora, where we have selected 353 pointlike features. Fundamental statistical analysis of the azimuth and location of the central point between every two points was carried in the range (0–5] km to obtain a rose diagram, where the azimuth of maximum and minimum frequencies are separated apart 90°, suggesting that most of the magma, that built the Pinacate Volcanic Field, was emplaced along the N25 ± 5°W direction. This direction is nearly parallel to the trend of the Crust-Mantle interface, inferred by nonlinear inversion of isostatic residual gravity data, which lies at a depth of about 18.5 km beneath the Santa Clara Volcano. The magnetization between 18 and 21 km-depth, inferred by linear inversion of aeromagnetic data, may correspond with mafic rocks of gabbroic composition, which led to monogenetic volcanism of basaltic composition. It is suggested that monogenetic volcanic activity in the PVF was accommodated mainly in a direction normal to a major lateral change in density.

New High-quality Strong Lens Candidates with Deep Learning in the Kilo-Degree Survey

Abstract We report new high-quality galaxy-scale strong lens candidates found in the Kilo-Degree Survey data release 4 using machine learning. We have developed a new convolutional neural network (CNN) classifier to search for gravitational arcs, following the prescription by Petrillo et al. and using only r-band images. We have applied the CNN to two “predictive samples”: a luminous red galaxy (LRG) and a “bright galaxy” (BG) sample (r < 21). We have found 286 new high-probability candidates, 133 from the LRG sample and 153 from the BG sample. We have ranked these candidates based on a value that combines the CNN likelihood of being a lens and the human score resulting from visual inspection (P-value), and here we present the highest 82 ranked candidates with P-values ≥0.5. All of these high-quality candidates have obvious arc or pointlike features around the central red defector. Moreover, we define the best 26 objects, all with P-values ≥0.7, as a “golden sample” of candidates. This sample is expected to contain very few false positives; thus, it is suitable for follow-up observations. The new lens candidates come partially from the more extended footprint adopted here with respect to the previous analyses and partially from a larger predictive sample (also including the BG sample). These results show that machine-learning tools are very promising for finding strong lenses in large surveys and more candidates can be found by enlarging the predictive samples beyond the standard assumption of LRGs. In the future, we plan to apply our CNN to the data from next-generation surveys such as the Large Synoptic Survey Telescope, Euclid, and the Chinese Space Station Optical Survey.

Influence of method selection on clustering analyses of point-like features: Examples from three zones of distributed volcanism

Most regions that have experienced spatially distributed volcanism also present a clustered structure of eruptive vents. Attempts to identify patterns from the spatial distribution of vents have resorted to various methods. The influence that specific methods might have on the identified patterns, however, has remained largely unexplored. In this work I assess the ability of common “out-of-the-box” algorithms to yield consistent results. The geological significance of those groupings is also tested. The results of those tests indicate that method selection exerts a strong influence, and therefore introduces undesired biases on the identification of groups on zones of distributed volcanism. The results reported below indicate that it is almost impossible to capture the fine structure of volcanic clusters by focusing on a single value that “best” describes spatial distribution. Nevertheless, an alternative approach that could reduce the negative influence of such method-dependence is outlined. This method searches for core-groups as the membership identified on each group by more than one algorithm. Despite the limited ability of this method to reproduce pre-existing geologic or tectonic partitions, it provides grounds for a more robust interpretation of results than the use of only one out-of-the box method in isolation.

Optical counterparts of an ultraluminous X-Ray Source X-1 in NGC 2500

ABSTRACT We present the results of a search for optical counterparts of ultraluminous X-ray source (ULX) X-1 in the nearby galaxy NGC 2500 by using archival images taken with the Hubble Space Telescope Wide Field Camera (WFC3)/UVIS. We identified four optical sources as possible counterparts within the 2σ error radius of 0$^{\prime \prime }_{.}$3 in the images. However, only two of them were investigated as candidates for counterparts due to their point-like features and their identification in various filters. These two faint candidates have absolute magnitudes of MV ≈ −3.4 and −3.7. The spectral energy distributions of two candidates were modelled by a power-law spectrum with a photon index (α) ∼1.5, but the spectrum of one candidate shows a deviation. This may suggest that at least two components are responsible for the optical emission. The red part of the spectrum could arise from the companion star and the blue part could be interpreted as an evidence of reprocessing of the X-rays from the disc.

Volumetric calibration enhancements for single-camera light-field PIV

This work presents a volumetric calibration method for single-camera light-field particle image velocimetry (light-field PIV or LF-PIV). The proposed technique makes use of the unique point-like feature of particle light-field images to accurately determine affected pixels for a spatial voxel over a relative large measurement volume. A calibration model is derived based on Gaussian optics, which relates a spatial point light source with its confusion circle produced on microlens array (MLA), and optical distortions are accounted for by introducing five calibration parameters. By taking lens defects and misalignment between MLA and image sensor into account, the calibration method can calculate weighting coefficient for particle image reconstruction more accurately than the theoretical ray-tracing method, especially for regions further away from focal plane where light ray deflections are significant due to optical distortions. The volumetric calibration method was validated by simulation tests using synthetic light-field images, and has been successfully applied to a classic vortex-ring LF-PIV measurement, where the measurable range in depth direction was successfully extended and the quality of reconstructed volumetric velocity field was greatly improved.

Sparse ISAR imaging using a greedy Kalman filtering approach

The Compressive sensing (CS) theory provides a novel type of image reconstruction methods for radar imaging. A good image can be obtained using much less data as compared to the conventional imaging methods, however under the sparse assumptions of the scene/target in certain domains. In this paper, we present a Kalman filter based sparse reconstruction approach for ISAR imaging. As the Kalman filter has robust and excellent estimation performance in statistical settings for linear problems, it leads to good image reconstruction results for real ISAR data. In addition to the spatial sparsity of the scene, we exploit the sparsity in wavelet domain to improve the reconstruction of region-like features in the target image other than point-like features. The images obtained by assuming the sparsity in different domains are synthesized to further improve the image reconstruction. The ISAR real data processing demonstrates the performance of the Kalman filter based sparse ISAR imaging method and the effectiveness of the image synthesis methods.

Estimation of glacier surface motion by robust phase correlation and point like features of SAR intensity images

For monitoring of glacier surface motion in pole and alpine areas, radar remote sensing is becoming a popular technology accounting for its specific advantages of being independent of weather conditions and sunlight. In this paper we propose a method for glacier surface motion monitoring using phase correlation (PC) based on point-like features (PLF). We carry out experiments using repeat-pass TerraSAR X-band (TSX) and Sentinel-1 C-band (S1C) intensity images of the Taku glacier in Juneau icefield located in southeast Alaska. The intensity imagery is first filtered by an improved adaptive refined Lee filter while the effect of topographic reliefs is removed via SRTM-X DEM. Then, a robust phase correlation algorithm based on singular value decomposition (SVD) and an improved random sample consensus (RANSAC) algorithm is applied to sequential PLF pairs generated by correlation using a 2D sinc function template. The approaches for glacier monitoring are validated by both simulated SAR data and real SAR data from two satellites. The results obtained from these three test datasets confirm the superiority of the proposed approach compared to standard correlation-like methods. By the use of the proposed adaptive refined Lee filter, we achieve a good balance between the suppression of noise and the preservation of local image textures. The presented phase correlation algorithm shows the accuracy of better than 0.25 pixels, when conducting matching tests using simulated SAR intensity images with strong noise. Quantitative 3D motions and velocities of the investigated Taku glacier during a repeat-pass period are obtained, which allows a comprehensive and reliable analysis for the investigation of large-scale glacier surface dynamics.

Volcanic edifice alignment detection software in MATLAB: Test data and preliminary results for shield fields on Venus

The scarcity of impact craters on Venus make it difficult to infer the relative ages of geologic units. Stratigraphic methods can be used to help infer the relative ordering of surface features, but the relatively coarse resolution of available radar data means ambiguity about the timing of certain features is common. Here we develop a set of statistical tools in MATLAB to help infer the relative timing between clusters of small shield volcanoes and sets of fractures in the surrounding terrain. Specifically, we employed two variants of the two-point azimuth method to detect anisotropy in the distribution of point-like features. The results of these methods are shown to successfully identify anisotropy at two spatial scales: at the whole-field level and at scales smaller than a set fraction of the mean value. Initial results on the test cases presented here are promising, at least for volcanic fields emplaced under uniform conditions. These methods could also be used for detecting anisotropy in other point-like geologic features, such as hydrothermal vents, springs, and earthquake epicenters.

Suboptimal threshold estimation for detection of point-like objects in radar images

There are many methods for detection of point-like features in gray-leveled bitmap images. The problem of defining a threshold for acceptance or rejection of the results is usually neglected or left to experts. In this paper, a novel method of estimating suboptimal detection threshold values is proposed. It is based on overlapping the results of two or three different methods parametrized with respective thresholds. The quality functions (of two or three variables), whose global extrema (maximum) approximately correspond to the suboptimal levels of thresholds for the used methods, are defined. This method was applied to a series of the bitmaps generated by a radar sensor and by simulated bitmaps.

AN ENIGMATIC POINT-LIKE FEATURE WITHIN THE HD 169142 TRANSITIONAL DISK,

We report the detection of a faint pointlike feature possibly related to ongoing planet-formation in the disk of the transition disk star HD 169142. The pointlike feature has a $\Delta$mag(L)$\sim$6.4, at a separation of $\sim$0.11" and PA$\sim$0$^{\circ}$. Given its lack of an H or K$_{S}$ counterpart despite its relative brightness, this candidate cannot be explained by purely photospheric emission and must be a disk feature heated by an as yet unknown source. Its extremely red colors make it highly unlikely to be a background object, but future multi-wavelength followup is necessary for confirmation and characterization of this feature.

Migration of Ca II H bright points in the internetwork

The migration of magnetic bright point-like features (MBP) in the lower solar atmosphere reflects the dispersal of magnetic flux as well as the horizontal flows of the atmospheric layer they are embedded in. We analyse trajectories of the proper motion of intrinsically magnetic, isolated internetwork Ca II H MBPs (mean lifetime 461 +- 9 s) to obtain their diffusivity behaviour. We use seeing-free high spatial and temporal resolution image sequences of quiet-Sun, disc-centre observations obtained in the Ca II H 3968 {\AA} passband of the Sunrise Filter Imager (SuFI) onboard the Sunrise balloon-borne solar observatory. Small MBPs in the internetwork are automatically tracked. The trajectory of each MBP is then calculated and described by a diffusion index ({\gamma}) and a diffusion coefficient (D). We further explore the distribution of the diffusion indices with the help of a Monte Carlo simulation. We find {\gamma} = 1.69 +- 0.08 and D = 257 +- 32 km^2/s averaged over all MBPs. Trajectories of most MBPs are classified as super-diffusive, i.e., {\gamma} > 1, with the determined {\gamma} being to our knowledge the largest obtained so far. A direct correlation between D and time-scale ({\tau}) determined from trajectories of all MBPs is also obtained. We discuss a simple scenario to explain the diffusivity of the observed, relatively short-lived MBPs while they migrate within a small area in a supergranule (i.e., an internetwork area). We show that the scatter in the {\gamma} values obtained for individual MBPs is due to their limited lifetimes. The super-diffusive MBPs can be well-described as random walkers (due to granular evolution and intergranular turbu- lence) superposed on a large systematic (background) velocity, caused by granular, mesogranular and supergranular flows.

CURVELET-WAVELET REGULARIZED SPLIT BREGMAN ITERATION FOR COMPRESSED SENSING

Compressed sensing is a new concept in signal processing. Assuming that a signal can be represented or approximated by only a few suitably chosen terms in a frame expansion, compressed sensing allows one to recover this signal from much fewer samples than the Shannon–Nyquist theory requires. Many images can be sparsely approximated in expansions of suitable frames as wavelets, curvelets, wave atoms and others. Generally, wavelets represent point-like features while curvelets represent line-like features well. For a suitable recovery of images, we propose models that contain weighted sparsity constraints in two different frames. Given the incomplete measurements f = Φu + ϵ with the measurement matrix Φ ∈ ℝK × N, K ≪ N, we consider a jointly sparsity-constrained optimization problem of the form [Formula: see text]. Here Ψcand Ψware the transform matrices corresponding to the two frames, and the diagonal matrices Λc, Λwcontain the weights for the frame coefficients. We present efficient iteration methods to solve the optimization problem, based on Alternating Split Bregman algorithms. The convergence of the proposed iteration schemes will be proved by showing that they can be understood as special cases of the Douglas–Rachford Split algorithm. Numerical experiments for compressed sensing-based Fourier-domain random imaging show good performances of the proposed curvelet-wavelet regularized split Bregman (CWSpB) methods, where we particularly use a combination of wavelet and curvelet coefficients as sparsity constraints.

Numerical recognition of alignments in monogenetic volcanic areas: Examples from the Michoacán-Guanajuato Volcanic Field in Mexico and Calatrava in Spain

Identification of geological lineaments using numerical methods is a useful tool to reveal structures that may not be evident to the naked eye. In this sense, monogenetic volcanic fields represent an especially suitable case for the application of such techniques, since eruptive vents can be considered as point-like features. Application of a two-point azimuth method to the Michoacán-Guanajuato Volcanic Field (Mexico) and the Calatrava Volcanic Province (Spain) demonstrates that the main lineaments controlling the distributions of volcanic vents (~ 322° in Calatrava and ~ 30° in Michoacán) approach the respective main compressional axes that dominate in the area (i.e. the Cocos–North America plates convergence and the main Betics compressional direction, respectively). Considering the stress fields that are present in each volcanic area and their respective geodynamic history, it seems that although volcanism may be a consequence of contemporaneous extensional regimes, the distribution of the volcanic vents in these kinds of monogenetic fields is actually controlled by reactivation of older fractures which then become more favourable for producing space for magma ascent at near-surface levels.

STEREOSCOPIC DETERMINATION OF HEIGHTS OF EXTREME ULTRAVIOLET BRIGHT POINTS USING DATA TAKEN BY SECCHI/EUVI ABOARDSTEREO

We measure the heights of EUV bright points (BPs) above the solar surface by applying a stereoscopic method to the data taken by the Solar TErrestrial RElations Observatory/SECCHI/Extreme UltraViolet Imager (EUVI). We have developed a three-dimensional reconstruction method for point-like features such as BPs using the simple principle that the position of a point in the three-dimensional space is specified as the intersection of two lines of sight. From a set of data consisting of EUVI 171 A, 195 A, 284 A, and 304 A images taken on 11 days arbitrarily selected during a period of 14 months, we have identified and analyzed 210 individual BPs that were visible on all four passband images and smaller than 30 Mm. The BPs seen in the 304 A images have an average height of 4.4 Mm, and are often associated with the legs of coronal loops. In the 171 A, 195 A, and 284 A images the BPs appear loop-shaped, and have average heights of 5.1, 6.7, and 6.1 Mm, respectively. Moreover, there is a tendency that overlying loops are filled with hotter plasmas. The average heights of BPs in 171 A, 195 A, and 284 A passbands are roughly twice the corresponding average lengths. Our results support the notion that an EUV BP represents a system of small loops with temperature stratification like flaring loops, being consistent with the magnetic reconnection origin.