Imaging Geometry Research Articles

Active thickness estimation and failure simulation of translational landslide using multi-orbit InSAR observations: A case study of the Xiongba landslide

The active thickness of the translational landslides plays a pivotal role in evaluating its hazards and simulating its instability. Existing techniques have difficulties in estimating the accurate active thickness due to the limitations of observation conditions and imaging geometry, leading to deviations in failure simulations. To overcome these challenges, this study proposes an enhanced method that utilizes multi-orbit Interferometric Synthetic Aperture Radar (InSAR) observations to estimate the active thickness of the translational landslides and subsequently conduct more accurate instability simulations. The method involves integrating multi-orbit InSAR imaging parameters with the spatial geometry of the landslide to establish a slope coordinate system. This system enables the projection of one-dimensional InSAR Line Of Sight (LOS) displacements onto the three-dimensional displacements of the landslide. Subsequently, the active thickness is estimated by combining InSAR three-dimensional displacements with the mass conservation method. Finally, the estimated thickness is incorporated into the geological model construction to simulate the dynamic movement of the landslide. The method was applied to the Xiongba translational landslide in Gongga County, Tibet Autonomous Region, China. The results show that the deformation is mainly concentrated at its forefront, with maximum three-dimensional deformation rates of 4.7 m/a, 2.3 m/a, and 1.24 m/a. The landslide encompasses an estimated area of around 5.33 square kilometers, and its active thickness varies from 0 to 106.59 m. The maximum displacement distance reaches 1469.76 m, with a peak velocity of 60.37 m/s. The proposed method provides scientific support for assessing, analyzing, and preventing landslide disasters.

An Improved NLCS Algorithm Based on Series Reversion and Elliptical Model Using Geosynchronous Spaceborne–Airborne UHF UWB Bistatic SAR for Oceanic Scene Imaging

Geosynchronous spaceborne–airborne (GEO-SA) ultra-high-frequency ultra-wideband bistatic synthetic aperture radar (UHF UWB BiSAR) provides high-precision images for marine and polar environments, which are pivotal in glacier monitoring and sea ice thickness measurement for polar ocean mapping and navigation. Contrasting with traditional high-frequency BiSAR, it faces unique challenges, such as the considerable spatial variability, significant range–azimuth coupling, and vast volumes of echo data, which impede high-resolution image reconstruction. This paper presents an improved bistatic nonlinear chirp scaling (NLCS) algorithm for imaging oceanic scenes with GEO-SA UHF UWB BiSAR. This methodology extends the two-dimensional (2-D) spectrum up to the sixth order via the method of series reversion (MSR) to meet accuracy demands and then employs an elliptical model to elucidate the alterations in the azimuth frequency modulation (FM) rate mismatch. Initially, the imaging geometry and signal model are introduced, and then a separation of bistatic slant ranges based on the configuration is proposed. In addition, during range processing, after eliminating linear range cell migration (RCM), the derivation process for the sixth-order 2-D spectrum is detailed and an improved filter is applied to correct the high-order RCM. Finally, during azimuth processing, the causes of the FM rate mismatch are analyzed, a cubic perturbation function derived from the elliptical model is used for FM rate equalization, and a unified sixth-order filter is applied to complete the azimuth compression. Experimental results with point targets and natural oceanic scenes validate the outstanding efficacy of the proposed NLCS algorithm, particularly in imaging quality enhancements for GEO-SA UHF UWB BiSAR.

Controlling chaotic vocal fold oscillations in the numerical production of vowel sounds

Lumped mass models have been studied in depth to unveil the complex nonlinear physics of phonation. Even in the case of simple symmetric models, slight changes in muscle restoring forces or excessive subglottal pressure can cause abnormal or even chaotic vocal fold oscillations. In a recent work, it was shown that it was possible to device a theoretical pacemaker for phonation that could render the chaotic motion regular again. This consisted of attaching an additional mass–spring–damper system to the vocal fold model, the damping of which could be adjusted according to an altering energy chaos control strategy. The chaos of phonation is low-dimensional and one may wonder whether it has a profound effect in voice production and, if so, whether the proposed phonation pacemaker could compensate for it. For this purpose, we compute the time evolution of the glottal volume velocity generated by normal, chaotic and controlled oscillations of the vocal folds and convolve it with the impulse response of magnetic resonance imaging (MRI) geometries of the human vocal tract, corresponding to the vowels /ɑ/, /i/ and /u/. The impulse response for each vowel is obtained from the solution of the wave equation by the finite element method, when a Gaussian pulse is prescribed as a boundary condition in the glottis of the vocal tract. It will be demonstrated that the chaotic vibration of the vocal folds severely distorts the vowel sounds and that the proposed control strategy is able to recover with high quality the vowels produced in normal phonation. Audiovisual files are provided to support the objective results of the phenomena in terms of spectral and time analysis of the train of glottal pulses generated by the vocal folds and the produced vowel sounds.

Bistatic spatial coherence for micronavigation of a volumetric synthetic aperture sonar

Combining multiple passes of a volumetric synthetic aperture sonar (SAS) may open new possibilities for sonar imaging, if the passes can be precisely aligned. Previous work suggests that coherence-based micronavigation is a potential approach to achieve this alignment. However, existing coherence-based techniques require assumptions that break down in many volumetric imaging geometries. This breakdown leads to a loss of coherence that has not been widely studied, and consequently, has hindered the application of micronavigation to volumetric SAS systems. This work will explore the impact of sensing range and bistatic separation on spatial coherence in downward-looking, volumetric sonar applications where the far-field assumption no longer holds. As signals transmitted from downward-looking sonars may penetrate into the sediment floor, this analysis will consider both interface and volumetric scattering. First, using both simulated and experimental sonar data, we will quantify the loss in coherence that occurs in these near-field geometries. Then, methods to regain lost coherence will be examined in an effort to enable spatial coherence-based navigation for a volumetric SAS. Finally, the work’s relevancy for ongoing efforts in acoustic navigation and repeat-pass imaging will be discussed.

3-D coseismic displacement mapping of the 2015 Mw7.8 Gorkha earthquake using multi-viewed InSAR

After the 2015 Mw7.8 Gorkha earthquake, geodetic measurements have been extensively used to constrain slip kinematics, fault geometry of the Main Himalayan Thrust (MHT) and earthquake cycle deformation. However, the spatially dense coseismic 3-D displacements remain largely unresolved, owing to the side-looking geometry of SAR images and sparse GPS observations. We improved 3-D displacements by incorporating a strain model in a Bayesian framework, utilizing all available coseismic interferograms and azimuth offsets from Sentinel-1 and ALOS-2 satellites. The coseismic strain map shows that major landslides in large slope areas are spatially consistent with extensional strain. The vertical component illustrates a spatial pattern different from interseismic and postseismic uplift, hinting at diverse contributions from various tectonic uplift processes in the frontal mountain belt. The spatial relationship between the interseismic strain and coseismic deformation suggests a partial release of the accumulated strain, implying a remaining notable seismic hazard around Gorkha.

Polarimetric SAR cross-calibration method based on stable distributed targets

ABSTRACT Polarimetric calibration is essential for the pre-processing of Polarimetric Synthetic Aperture Radar (PolSAR) data because it effectively mitigates polarimetric distortions in the measured PolSAR data. Traditional methods of polarimetric calibration employ man-made calibrators that offer high accuracy. However, the frequency of calibration is often limited due to the labor-intensive and time-consuming nature of deploying such calibrators. Some polarimetric calibration methods based on distributed targets in nature enable more frequent calibration. Nevertheless, these methods are constrained by the availability of specific distributed targets with known polarimetric properties for estimating parameters related to co-polarization channel imbalance (co-pol-imba) parameters. If distributed targets are not appropriately selected or suitable targets are absent within the image scene, the accuracy of calibration will be compromised. To address this challenge, this paper introduces the idea of cross-calibration, which uses calibrated PolSAR data to determine the real polarimetric property of distributed targets and cross-estimates co-pol-imba parameters for uncalibrated PolSAR data. Furthermore, considering the disparities in imaging geometry between calibrated and uncalibrated PolSAR data, the Cross-Co-Polarization Ratio (CCPR) coefficients are proposed to select stable distributed targets in both the calibrated PolSAR data and the uncalibrated PolSAR data. This approach not only takes into account the impact of co-pol-imba on feature extraction but can also be applied in a broader range of scenes. The real data experiments on the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) data show that the estimated results of the cross-calibration method for co-pol-imba are comparable to the polarimetric calibration method based on man-made calibrators, with an amplitude difference of 0.17 dB and a phase difference of 0.69°.

Muscle geometry and its relevance for sports performance? A perspective of current findings and future opportunities

Muscle geometry and its relevance for sports performance? A perspective of current findings and future opportunities

Sensitivity Testing of Stereophotoclinometry for the OSIRIS-REx Mission. II. Effective Observation Geometry for Digital Terrain Modeling

The OSIRIS-REx mission used stereophotoclinometry (SPC) to generate digital terrain models (DTMs) of its target asteroid, Bennu. Here we present a suite of preflight tests conducted to identify the observing geometry and number of images needed to create DTMs that would enable successful navigation around and to the surface of the asteroid. We demonstrate that high-quality DTMs can be generated by using only five images: four that are focused on topography, in which the spacecraft’s viewing geometry brackets the target (north, south, east, and west), and a fifth that measures the target’s albedo variation, taken from near local noon. We further show that the first 10 iterations of the SPC process can meaningfully improve DTM quality, including in the case of a suboptimal input image set, whereas after 10 iterations the DTM quality approaches an asymptotic maximum. We distill our findings into recommendations for observation planning that can be applied by other missions intending to use SPC to model the shape and terrain of their target.

GEOMETRY IN WARLI: MERGING FOLK ART WITH MATHEMATICS TEACHING

The study was themed on art integration (folk art “Warli” and geometry images) in mathematics teaching and its effect on learners' achievement. The objectives were (i) to develop art-integrated mathematical instructional modules to teach mathematical concepts and (ii)To measure the effect of an art-integrated mathematical instructional intervention on learner achievement. The quasi-experimental post-test research design with a single group post-test design was used. 45 participants of 7th-grade students from Govt Upper Primary School have been selected. The intervention was designed on the Triangle and its Properties through Warli folk art and geometry images. After obtaining post-test scores, data analysis was done. Therefore, learners' overall achievement was based on learning outcomes. The results revealed that the range of achievement was between 60-95%, and achievement of remembering, understanding, and applying learning objectives was 89%, 83%, and 84%, and analyzing learning outcomes achieved 64% while evaluating and creating learning outcomes were committed to 63 % and 69 %. The results showed that the art-integrated instructional intervention was found to be positive in higher-order cognitive abilities.

A clinical solution for non-toxic 3D-printed photon blocks in external beam radiation therapy.

A well-known limitation of multi-leaf collimators is that they cannot easily form island blocks. This can be important in mantle region therapy. Cerrobend photon blocks, currently used for supplementary shielding, are labor-intensive and error-prone. To address this, an innovative, non-toxic, automatically manufactured photon block using 3D-printing technology is proposed, offering a patient-specific and accurate alternative. The study investigates the development of patient-specific photon shielding blocks using 3D-printing for three different patient cases. A 3D-printed photon block shell filled with tungsten ball bearings (BBs) was designed to have similar dosimetric properties to Cerrobend standards. The generation of the blocks was automated using the Eclipse Scripting API and Python. Quality assurance was performed by comparing the expected and actual weight of the tungsten BBs used for shielding. Dosimetric and field geometry comparisons were conducted between 3D-printed and Cerrobend blocks, utilizing ionization chambers, imaging, and field geometry analysis. The quality assurance assessment revealed a -1.3% average difference in the mass of tungsten ball bearings for different patients. Relative dose output measurements for three patient-specific blocks in the blocked region agreed within 2% of each other. Against the Treatment Planning System (TPS), both 3D-printed and Cerrobend blocks agreed within 2%. For each patient, 6MV image profiles taken through the 3D-printed and Cerrobend blocks agreed within 1% outside high gradient regions. Jaccard distance analysis of the MV images against the TPS planned images, found Cerrobend blocks to have 15.7% dissimilarity to the TPS, while that of the 3D-printed blocks was 6.7%. This study validates a novel, efficient 3D-printing method for photon block creation in clinical settings. Despite potential limitations, the benefits include reduced manual labor, automated processes, and greater precision. It holds potential for widespread adoption in radiation therapy, furthering non-toxic radiation shielding.

Experimental determination of strain in thin aluminum plate with central hole subjected to far-field tensile loading using digital image correlation (DIC)

A flat Aluminum specimen with a geometric discontinuity, which allows testing of the applicability of 2D and 3D Digital Image Correlation Strain measurements, has been considered for this research since it is prone to high stress concentration via Addis Ababa Institute of Technology research interest. Experimental strain using digital image correlation and geometry measurements should be measured with estimated material properties and compare the results with theoretical model predictions. Aluminum plate with central hole were subjected for far field stress in the Machine shop of School of Mechanical and Industrial Engineering at Addis Ababa University in order to test the agreement between DIC’s strain analysis, strain gauge strain analysis and calculated empirical formulas of strain analysis and for the stress distribution of the plate elastically deformed by using VIC-3D and strain gauge. The aim is to measure vertical strain field, Vertical strain along horizontal line through hole center as function of applied loading and vertical strain using theoretical formula along same line as measurements in a plate with central hole subjected to far field and near field tensile loading using visual image coloration (VIC-3D) software, Destensometere device and solid mechanics equations to compare strain results.

Advancing 6-DoF Instrument Pose Estimation in Variable X-Ray Imaging Geometries.

Accurate 6-DoF pose estimation of surgical instruments during minimally invasive surgeries can substantially improve treatment strategies and eventual surgical outcome. Existing deep learning methods have achieved accurate results, but they require custom approaches for each object and laborious setup and training environments often stretching to extensive simulations, whilst lacking real-time computation. We propose a general-purpose approach of data acquisition for 6-DoF pose estimation tasks in X-ray systems, a novel and general purpose YOLOv5-6D pose architecture for accurate and fast object pose estimation and a complete method for surgical screw pose estimation under acquisition geometry consideration from a monocular cone-beam X-ray image. The proposed YOLOv5-6D pose model achieves competitive results on public benchmarks whilst being considerably faster at 42 FPS on GPU. In addition, the method generalizes across varying X-ray acquisition geometry and semantic image complexity to enable accurate pose estimation over different domains. Finally, the proposed approach is tested for bone-screw pose estimation for computer-aided guidance during spine surgeries. The model achieves a 92.41% by the 0.1·d ADD-S metric, demonstrating a promising approach for enhancing surgical precision and patient outcomes. The code for YOLOv5-6D is publicly available at https://github.com/cviviers/YOLOv5-6D-Pose.

Long baseline bistatic radar imaging of tumbling space objects for enhancing space domain awareness

AbstractLong baseline bistatic radar systems herald enhanced sensitivity and metric accuracy for space objects in geosynchronous orbits and beyond. Radio telescopes are ideal participants in such a system; in particular, they often feature large apertures with low‐noise temperatures and have stable, synchronised clocks. Pairing radio telescopes with high‐power radars creates new methodologies for Space Domain Awareness. This paper describes long baseline bistatic measurements using the Millstone Hill Radar in the USA, the Tracking and Imaging Radar in Germany, multiple receivers of the enhanced multi‐element remotely linked interferometer network array in the United Kingdom, and the Westerbork Synthesis Radio Telescope in the Netherlands. The authors, a Research Task Group formed by the NATO Science and Technology Organisation Sensors and Electronic Technology Panel (SET‐293), performed novel bistatic and monostatic radar imaging experiments with real on‐orbit tumbling rocket bodies. These experiments on tumbling objects at near‐geosynchronous orbits highlight successful demonstrations of advanced bistatic Doppler characterisation across diverse imaging geometries. Specialised Doppler processing on tumbling targets, such as the Doppler superpulse algorithm, enables high‐fidelity rotation period estimation and determination of minimum target size.

Carbon nanotube-based multiple source C-arm CT system: feasibility study with prototype system.

To extend the field of view while reducing dimensions of the C-arm, we propose a carbon nanotube (CNT)-based C-arm computed tomography (CT) system with multiple X-ray sources. A prototype system was developed using three CNT X-ray sources, enabling a feasibility study. Geometry calibration and image reconstruction were performed to improve the quality of image acquisition. However, the geometry of the prototype system led to projection truncation for each source and an overlap region of object area covered by each source in the two-dimensional Radon space, necessitating specific corrective measures. We addressed these problems by implementing truncation correction and applying weighting techniques to the overlap region during the image reconstruction phase. Furthermore, to enable image reconstruction with a scan angle less than 360°, we designed a weighting function to solve data redundancy caused by the short scan angle. The accuracy of the geometry calibration method was evaluated via computer simulations. We also quantified the improvements in reconstructed image quality using mean-squared error and structural similarity. Moreover, detector lag correction was applied to address the afterglow observed in the experimental data obtained from the prototype system. Our evaluation of image quality involved comparing reconstructed images obtained with and without incorporating the geometry calibration results and images with and without lag correction. The outcomes of our simulation study and experimental investigation demonstrated the efficacy of our proposed geometry calibration, image reconstruction method, and lag correction in reducing image artifacts.

Accretion Cycles, Structural Evolution, and Thrust Activity in Accretionary Wedges With Various Décollement Configurations: Insights From Sandbox Analog Modeling

AbstractThe architecture (geometry, fault network, and stacking pattern of accreted thrust sheets) of accretionary wedges influences subduction zone processes. However, it remains challenging to constrain the architectural evolution in natural accretionary wedges over geological timescales. In this study, we undertook sandbox analog modeling, with quantitative analysis of the wedge geometry and digital image correlation‐based kinematics, to delineate the wedge growth history with four décollement settings (single or double and continuous or discontinuous). The results show that the wedge is formed by repeated episodic frontal accretion with a constant cycle (i.e., the accretion cycle), and the degree of coupling between the base of the wedge and subducting plate interface appears to depend on the relative strengths of the wedge and detachment. An interbedded décollement layer in the incoming sediment facilitated wedge segmentation and rearrangement of the internal fault network, which weakened the wedge strength. A combination of a detachable high‐friction patch in the basal décollement and a continuous interbedded weak layer enabled underplating of underthrusted sediment beneath the inner wedge, which involved a low‐angle, long‐lived forethrust and multiple cycles of frontal accretion on short‐lived forethrusts at the deformation front. Our findings suggest that décollement configuration is a key factor in controlling the accretion cycle, strain distribution, fault network, and wedge strength on timescales of ∼105 yr in natural accretionary systems. This result should be considered when investigating modern subduction zones.

Augmented Grad-CAM++: Super-Resolution Saliency Maps for Visual Interpretation of Deep Neural Network

In recent years, deep neural networks have shown superior performance in various fields, but interpretability has always been the Achilles’ heel of deep neural networks. The existing visual interpretation methods for deep neural networks still suffer from inaccurate and insufficient target localization and low-resolution saliency maps. To address the above issues, this paper presents a saliency map generation method based on image geometry augmentation and super-resolution called augmented high-order gradient weighting class activation mapping (augmented grad-CAM++). Unlike previous approaches that rely on a single input image to generate saliency maps, this method first introduces the image geometry augmentation technique to create a set of augmented images for the input image and generate activation mappings separately. Secondly, the augmented activation mappings are combined to form the final saliency map. Finally, a super-resolution technique is introduced to add pixel points to reconstruct the saliency map pixels to improve the resolution of the saliency map. The proposed method is applied to analyze standard image data and industrial surface defect images. The results indicate that, in experiments conducted on standard image data, the proposed method achieved a 3.1% improvement in the accuracy of capturing target objects compared to traditional methods. Furthermore, the resolution of saliency maps was three times higher than that of traditional methods. In the application of industrial surface defect detection, the proposed method demonstrated an 11.6% enhancement in the accuracy of capturing target objects, concurrently reducing the false positive rate. The presented approach enables more accurate and comprehensive capture of target objects with higher resolution, thereby enhancing the visual interpretability of deep neural networks. This improvement contributes to the greater interpretability of deep learning models in industrial applications, offering substantial performance gains for the practical deployment of deep learning networks in the industrial domain.

Applicability of the InSAR technique for slope monitoring

Interferometry is a technique that can be applied to SAR (Synthetic Aperture Radar) images that allow obtaining Digital Elevation Models, displacement measurements and assistance for monitoring large areas and/or engineering constructions. The objective of this paper is to present aspects related to the technique of Interferometry SAR (InSAR) applied to the monitoring of slopes. To do so, a systematic bibliographical review was used, through research platforms in scientific collections, in order to highlight the functioning and method of operation of InSAR. Besides that, the practical experience of the authors contributed to a critical analysis of the remote sensing technique addressed. The results show theoretical aspects related to the operation of SARs on board satellites, highlighting their characteristics, orbital systems, types of imaging geometry, as well as the principles of interferometric processing of SAR images. Practical applications demonstrate the potential of InSAR with an emphasis on slope monitoring, highlighting its ability to acquire topographic information on a millimeter scale, monitoring the long-term temporal evolution of displacements, the possibility of composing a monitoring system allowing directing the implementation of other instruments for evaluating the in situ conditions and some limitations regarding the time interval (satellite revisit time) for the acquisition of the displacement data.

Monocular depth estimation using self-supervised learning with more effective geometric constraints

Self-supervised learning-based depth estimation from monocular videos is a challenging yet promising way for 3D environment perception. Existing methods that use photometric consistency as supervision are often fragile in the case of textureless environments or illumination variations. In this paper, we adopt geometric constraints to improve the reliability and accuracy of monocular depth estimation. We introduce an equation derived from the two-view imaging geometry, from which we also develop a novel geometric loss function that is shown to be more effective than the epipolar constraint in self-supervised learning. In addition, we design a depth reconstruction loss by explicitly aligning the depth scale of the consecutive estimated depth maps to keep the depth scale consistent. Finally, a new self-supervised learning framework is formulated by incorporating the proposed geometric constraints into depth, pose, and optical flow estimation models. Extensive experiments on KITTI, Make3D, and NYU Depth v2 datasets show that, by adding our geometric constraints, the depth estimation model compares favorably with state-of-the-art self-supervised learning methods, and each sub-task has a significant improvement.

Extraction of landslide morphology based on Topographic Profile along the Direction of Slope Movement using UAV images

The landslide morphology is quickly and accurately extracted from Unmanned Air Vehicle (UAV) images. It is of great significance for emergency rescue and quantitative evaluation of landslide disasters. However, due to the complexity of landslide morphology, choosing the reasonable extraction thresholds is a challenging issue. A threshold selection method of Topographic Profile along the Direction of Slope Movement (TP-DSM) was proposed. Firstly, a hierarchical extraction rule sets for landslide morphology was constructed by integrating multi-feature information such as spectral, texture, geometry, topography and space of UAV images. Second, TP-DSM was proposed to select the optimal elevation thresholds for classifying different landslide morphology. Finally, the thresholds were introduced into the rule sets to achieve effective extraction of landslide morphology. This study uses Digital Orthophoto Map (DOM) and Digital Elevation Model (DEM) generated by UAV images as data sources, and the landslide in Luquan County, Yunnan Province, China as the Study area, the results show that the overall accuracy (OA) of landslide morphology extraction was 89.58%, and the Kappa coefficient was 0.88, which is effective and more consistent with the reality. The proposed method can also be applied to other potential locations.

Hybrid GA-PSO method with local search and image clustering for automatic IFS image reconstruction of fractal colored images

AbstractOver the past few decades, the application of iterated function systems (IFS) in reconstructing fractal images has been a challenging research area. Numerous methods have been proposed to address this issue. However, they generally focus on binary or grayscale images, neglecting the color component of the process. Consequently, they are unsuitable for reconstructing colored images. In a previous paper presented at the ISCMI 2021 conference, the authors introduced a novel approach that utilizes the cuckoo search algorithm and k-means clustering for IFS fractal reconstruction of colored images. Building upon that work, this paper introduces an enhanced and extended method by combining genetic algorithms (GAs) and particle swarm optimization (PSO) with local search and image clustering. In this approach, GA and PSO are mutually coupled to automatically determine the color of the contractive functions and the IFS parameters, respectively. The output of each method serves as the input for the other in an iterative manner. Main contributions of this method are: (1) it computes automatically the optimal number and IFS code of the contractive functions; (2) the color of the contractive functions is determined automatically through an optimization process using GA; (3) a local refinement step is performed to further enhance the final solution. Overall, this new method yields highly accurate results in reconstructing the geometry and color of input fractal images, without requiring any additional information about the target beyond the bitmap image.