Scan Distortion Research Articles

Physics-Based Scan Distortion Correction in Hardware

Physics-Based Scan Distortion Correction in Hardware

Interlacing in Atomic Resolution Scanning Transmission Electron Microscopy.

Fast frame rates are desirable in scanning transmission electron microscopy for a number of reasons: controlling electron beam dose, capturing in situ events, or reducing the appearance of scan distortions. While several strategies exist for increasing frame rates, many impact image quality or require investment in advanced scan hardware. Here, we present an interlaced imaging approach to achieve minimal loss of image quality with faster frame rates that can be implemented on many existing scan controllers. We further demonstrate that our interlacing approach provides the best possible strain precision for a given electron dose compared with other contemporary approaches.

Accuracy assessment (trueness and precision) of a confocal based intraoral scanner under twelve different ambient lighting conditions

ObjectivesThe ambient lighting condition has been identified as an important factor that influences the accuracy of intraoral scanners (IOSs). The purpose of this study was to evaluate the influence of 12 different ambient lighting conditions on the accuracy of a confocal based IOS (PrimeScan). Materials and methodsA typodont was digitized using a laboratory scanner (L2i) to obtain a reference standard tessellation language (STLr) file. A restorative dentist recorded the scans using an IOS (PrimeScan) under 12 different ambient lighting conditions where the luminosity was measured using a light meter (LX1330B Light Meter). Twelve groups were created, namely 0-, 500-, 1000-, 2000-, 3000-, 4000-, 5000-, 6000-, 7000-, 8000-, 9000-, and 10 000 lux groups. Ten STL files were recorded per group. The STLr file was used as a reference with which to compare the distortion of the 120 STL files obtained using a software program (Meshlab). The normality Shapiro–Wilk test indicated that the distributions were not normal. Therefore, the nonparametric Kruskal–Wallis and pairwise multicomparison tests were used to analyze the data (α = 0.05). ResultsThe group with the 1000 lux lighting condition obtained the smallest median ±interquartile range (IQR) with scanning distortion values of 69.5 ± 97.4 µm, followed by the 8000 lux group with a median ±IQR of 166.5 ± 318.1 µm. The 0 lx group presented the highest distortion values with a mean ±IQR of 355.5 ± 488.0 µm (p < 0.05). ConclusionsAmbient lighting conditions influenced the accuracy of the IOS tested. The highest accuracy values were obtained with 1000 lux. The lowest scanning accuracy was obtained with 0 lux.

Quantifying the Structure and Chemistry of Semiconductor Devices with the Latest Advancements in Scanning Transmission Electron Microscopy

Electron microscopy has been revolutionized by the advent of the aberration corrector and advances in detector both for imaging and spectroscopy. Aberration correction dramatically improved spatial resolution into the sub-ångstrom regime, while new detectors have unlocked information about materials that was previously only imaginable.While these recent advances have proven essential to the atomic scale characterization of materials, many measurements have remained largely semi-quantitative. In particular, accuracy and precision for scanning transmission electron microscopy (STEM) was significantly hampered by the presence of sample drift and scan distortion. Until recently, this limitation has obscured the capabilities to characterize minute changes to the atomic structure that can ultimately define material properties.In this talk, we will introduce revolving scanning transmission electron microscopy (RevSTEM) for the characterization of semiconductors. The method uses a series of fast-acquisition STEM images, but with the scan coordinates rotated between successive frames. This scan rotation introduces a concomitant change in image distortion that is then used to analyze the sample drift rate and direction. Multiple case studies will be presented to demonstrate the power of this technique to characterize electronic materials. For example, we will show how picometer level precision and accuracy enabled the capability to directly quantify ferroelectric HfO2 thin films. We will also show how RevSTEM images can be used to accurately determine crystallographic parameters in real-space, and to determine the structural origins of polarization.When combined with modern spectroscopy tools, the technique can directly inform growth mechanisms in AlN based materials for fabrication of quantum well structures. Specifically, We will show the interface quality between various AlGaN/AlN quantum wells using a combination of high-angle annular dark-field (HAADF) imaging and energy dispersive X-ray spectroscopy (EDS). We will show that we can directly measure the lattice parameters for each layer and how they vary across each AlN/AlGaN interface. Using EDS, we correlate the lattice parameters and lattice parameter values to the chemical composition in each layer. We show that throughout multiple quantum well structures, there is an asymmetrical interface with a diffusion of Ga on one side of the AlGaN layer. Further, we will discuss fluctuation in the composition present throughout each layer and the role on the local strain distribution.

Accurate and Robust Calibration of the Uniform Affine Transformation Between Scan-Camera Coordinates for Atom-Resolved In-Focus 4D-STEM Datasets.

Accurate geometrical calibration between the scan coordinates and the camera coordinates is critical in four-dimensional scanning transmission electron microscopy (4D-STEM) for both quantitative imaging and ptychographic reconstructions. For atomic-resolved, in-focus 4D-STEM datasets, we propose a hybrid method incorporating two sub-routines, namely a J-matrix method and a Fourier method, which can calibrate the uniform affine transformation between the scan-camera coordinates using raw data, without a priori knowledge of the crystal structure of the specimen. The hybrid method is found robust against scan distortions and residual probe aberrations. It is also effective even when defects are present in the specimen, or the specimen becomes relatively thick. We will demonstrate that a successful geometrical calibration with the hybrid method will lead to a more reliable recovery of both the specimen and the electron probe in a ptychographic reconstruction. We will also show that, although the elimination of local scan position errors still requires an iterative approach, the rate of convergence can be improved, and the residual errors can be further reduced if the hybrid method can be firstly applied for initial calibration. The code is made available as a simple-to-use tool to correct affine transformations of the scan-camera coordinates in 4D-STEM experiments.

The effect of post-acquisition data misalignments on the performance of STEM tomography

Scanning transmission electron microscopy (STEM) tomography is widely used to reveal three-dimensional (3D) structure of the specimens from nanometers to atomic resolution. Advances in transmission electron microscope enable high resolution and low dose data acquisition for 3D reconstruction to resolve 3D coordinates of single atoms. Meanwhile, the developments of reconstruction algorithms increase the reconstruction quality. However, the as-acquired raw datasets often require alignments before they can be used as inputs to feed a reconstruction algorithm. The effect of post-acquisition data misalignments on the final reconstruction quality of STEM tomography is less discussed. Here, using phantom datasets with a focus on atomic features, we simulate a range of misalignments on each alignment step and correlate the level of misalignments to the final reconstruction quality. The study pinpoints that accurate alignments of tilt angles and stack positions and minimizing scan distortion are important to the reconstruction quality, while the sequence of alignment steps do not affect the reconstruction quality. The study not only emphasizes the most important alignment steps that should be pay attention to for a high-quality 3D reconstruction, but also summarizes post-acquisition data alignment procedures as a primer for new practitioners to use STEM tomography.

A scanning distortion correction method based on X – Y galvanometer Lidar system* *Project supported by the National Natural Science Foundation of China (Grant Nos. 61775048 and 62027823) and the Natural Science Foundation of Shenzhen (Grant No. JCYJ2020109150808037).

Aiming at the problem of scanning distortion in X–Y galvanometer light detecting and ranging (Lidar) scanning system, we propose a method of image scanning distortion correction with controllable driving voltage compensation. Firstly, the geometrical optics vectors model is established to explain the principle of pincushion distortion in the galvanometer scanning system, and the simulation result of scanning trajectory is consistent with experiments. The linear relationship between the driving voltage and the scanning angle of the galvanometer is verified. Secondly, the relationship between the deflection angle of the galvanometer and the scanning trajectory and the driving voltage is deduced respectively, and an image scanning correction algorithm with controllable driving voltage compensation is obtained. The simulation experiment results of the proposed method show that the root-mean-square error (RMSE) and the corresponding curve between the scan value and the actual value at different distances, have a good correction effect for the pincushion distortion. Finally, the X–Y galvanometer scanning Lidar system is established to obtain undistorted two-dimensional scanned image and it can be applied to the three-dimensional Lidar scanning system in the actual experiments, which further demonstrates the feasibility and practicability of our method.

Automated Processing of Declassified KH-9 Hexagon Satellite Images for Global Elevation Change Analysis Since the 1970s

Observing changes in Earth surface topography is crucial for many Earth science disciplines. Documenting these changes over several decades at regional to global scale remains a challenge due to the limited availability of suitable satellite data before the year 2000. Declassified analog satellite images from the American reconnaissance program Hexagon (KH-9), which surveyed nearly all land surfaces from 1972 to 1986 at metric resolution, provide a unique opportunity to fill the gap in observations. However, large-scale processing of analog imagery remains challenging. We developed an automated workflow to generate Digital Elevation Models (DEMs) and orthophotos from scanned KH-9 mapping camera stereo images. The workflow includes a preprocessing step to correct for film and scanning distortions and crop the scanned images, and a stereo reconstruction step using the open-source NASA Ames Stereo Pipeline. The processing of several hundreds of image pairs enabled us to estimate reliable camera parameters for each KH-9 mission, thereby correcting elevation biases of several tens of meters. The resulting DEMs were validated against various reference elevation data, including snow-covered glaciers with limited image texture. Pixel-scale elevation uncertainty was estimated as 5 m at the 68% confidence level, and less than 15 m at the 95% level. We evaluated the uncertainty of spatially averaged elevation change and volume change, both from an empirical and analytical approach, and we raise particular attention to large-scale correlated biases that may impact volume change estimates from such DEMs. Finally, we present a case study of long-term glacier elevation change in the European Alps. Our results show the suitability of these historical images to quantitatively study global surface change over the past 40-50 years.

HAADF-STEM block-scanning strategy for local measurement of strain at the nanoscale

Lattice strain measurement of nanoscale semiconductor devices is crucial for the semiconductor industry as strain substantially improves the electrical performance of transistors. High resolution scanning transmission electron microscopy (HR-STEM) imaging is an excellent tool that provides spatial resolution at the atomic scale and strain information by applying Geometric Phase Analysis or image fitting procedures. However, HR-STEM images regularly suffer from scanning distortions and sample drift during image acquisition. In this paper, we propose a new scanning strategy that drastically reduces artefacts due to drift and scanning distortion, along with extending the field of view. It consists of the acquisition of a series of independent small subimages containing an atomic resolution image of the local lattice. All subimages are then analysed individually for strain by fitting a nonlinear model to the lattice images. The method allows flexible tuning of spatial resolution and the field of view within the limits of the dynamic range of the scan engine while maintaining atomic resolution sampling within the subimages. The obtained experimental strain maps are quantitatively benchmarked against the Bessel diffraction technique. We demonstrate that the proposed scanning strategy approaches the performance of the diffraction technique while having the advantage that it does not require specialized diffraction cameras.

Recent features in EBSD, including new trapezoidal correction for multi-mapping

EBSD (electron backscatter diffraction) of geological samples can be a challenge due to the complex crystal structures of minerals and commonly 5 or more different minerals in the samples. This poses a big challenge as the EBSP (electron backscatter diffraction patterns) of the minerals like feldspar and quartz commonly are much noisier than metallurgical materials that have simpler structures. Therefore, the indexing of geological samples can commonly be quite difficult and to correct for this in the online procedure means that the data acquisition needs to be redone on the SEM. This is a costly procedure, also because the indexing can take longer than the pattern acquisition itself. We, therefore, suggest that offline techniques are better suited for geological materials because the patterns can be re-indexed using different settings and further can be processed using different software both for indexing and pattern improvement. EBSD commonly have geometric scan distortion which increases with decreasing magnification. This problem is solved by acquiring using a geometric online scan correction during data collection in the NORDIF software using calibration grid. This overcomes stitching problems and additionally removes hidden problems such as geometrically distorted grain boundary segments and grain shape distortions.

Lattice Strain Measurement of Core@Shell Electrocatalysts with 4D Scanning Transmission Electron Microscopy Nanobeam Electron Diffraction

Strain engineering enables the direct modification of the atomic bonding and is currently an active area of research aimed at improving the electrocatalytic activity. However, directly measuring the lattice strain of individual catalyst nanoparticles is challenging, especially at the scale of a single unit cell. Here, we quantitatively map the strain present in rhodium@platinum (core@shell) nanocube electrocatalysts using conventional aberration-corrected scanning transmission electron microscopy (STEM) and the recently developed technique of 4D-STEM nanobeam electron diffraction. We demonstrate that 4D-STEM combined with data pre-conditioning allows for quantitative lattice strain mapping with sub-picometer precision without the influence of scan distortions. When combined with multivariate curve resolution, 4D-STEM allows us to distinguish the nanocube core from the shell and to quantify the unit cell size as a function of distance from the core-shell interface. Our results demonstrate that 4D-STEM has significant precision and accuracy advantages in strain metrology of catalyst materials compared to aberration-corrected STEM imaging and is beneficial for extracting information about the evolution of strain in catalyst nanoparticles.

Calibration method of curvature distortion in step height measurement by atomic force microscopy

Atomic force microscopy (AFM) is widely used to characterize the surface topography in nanomaterials and biology research since the high resolution in 3 dimensions. Height measurement is important in the investigation of graphene thickness. Due to some AFMs use tube scanner, the curved scanning distortion will cause height measurement error. Step height standards calibrated by metrological AFM are used to calibrate the Z axis of conventional AFMs. However, for step structure with large width, the method specified in ISO 5436 is not suitable. The distortion of the curvature scanning is discussed for different samples, and for large step width the influence is significant. So the substrate correction method is proposed to eliminate the scanning curvature and the comparison with several other fitting correction methods is also discussed.

RBPF-MSIS: Toward Rao-Blackwellized Particle Filter SLAM for Autonomous Underwater Vehicle With Slow Mechanical Scanning Imaging Sonar

Simultaneous localization and mapping (SLAM) has the potential to play a fundamental and significant role in achieving full autonomy for autonomous underwater vehicles (AUV). This article proposes a Rao-Blackwellized particle filter (RBPF) SLAM algorithm for an AUV equipped with a mechanically scanning imaging sonar (MSIS) that has a very slow scanning frequency. To tackle the issues of scan distortion and sonar data sparseness caused by the slow-sampling MSIS, the core of the algorithm is a carefully designed sliding window-based scan forming module. Then the formed scans are fed into the modified RBPF to build a consistent grid-based map thus localizing the AUV accurately. Extensive simulation and experiments are carried out to verify the proposed algorithm. The results show that the proposed algorithm outperforms existing ones in terms of the level of map consistency with the environment as well as the accuracy of pose estimation.

A MATHEMATICAL SENSOR MODEL FOR INDOOR USE OF A MULTI-BEAM ROTATING 3D LIDAR

Abstract. Our contribution presents a new perspective in the mathematical description of a rotating multi-beam LiDAR sensor, in a sense that we make use of projective geometry along with the “homogeneous general equation of the second degree” to parametrize scan lines. We describe the scan geometry of a typical multi-beam rotating 3D LiDAR by representing scan lines as pojective conics that represent a projective figure (a cone) in an embedding plane. This approach enables the parameterization of each scan line using a generic conic section equation. Most modeling approachs model spinning LiDAR sensors in terms of individual points sampled by a laser beam. On the contrary, we propose a model that provides a high-level geometric interpretation both for the environment and the laser scans. Possible application scenarios include exterior and interior calibration of multiple rotating multi-beam sensors, scan distortion correction and localization in planar maps.

Airborne SAR Imaging Algorithm for Ocean Waves Based on Optimum Focus Setting

Ocean waves are the richest texture on the sea surface, from which valuable information can be inversed. In general, the Synthetic Aperture Radar (SAR) images of surface waves will inevitably be distorted due to the intricate motion of surface waves. However, commonly used imaging algorithms do not take the motion of surface waves into consideration. Therefore, surface waves on the obtained SAR images are rather blurred. To solve this problem, an airborne SAR imaging algorithm for ocean waves based on optimum focus setting is proposed in this paper. Firstly, in order to obtain the real azimuth phase speed of dominant wave, the geometric and scanning distortion in the blurred SAR image is calibrated. Subsequently, according to the SAR integration time and wavelength of the dominant wave, a proper focus setting variation section is selected. Afterwards, all the focus settings in this variation section are used to refocus the image, which are then compared to decide the optimum focus setting for dominant wave. Finally, by redesigning the azimuth matched filter using this optimum focus setting, a well-focused SAR image for the dominant wave can be obtained. The proposed algorithm is applied to both simulation and field data, and SAR images of surface waves are obtained. Furthermore, the obtained images are compared with those obtained with a zero-focus setting. The comparison shows that the focus of surface waves is significantly improved, which verifies the effectiveness of the proposed algorithm. Finally, how to choose the appropriate focus setting variation section under different parameters and the applicability of the algorithm are analyzed.

Joint non-rigid image registration and reconstruction for quantitative atomic resolution scanning transmission electron microscopy

Aberration corrected scanning transmission electron microscopes (STEM) enable to determine local strain fields, composition and bonding states at atomic resolution. The precision to locate atomic columns is often obstructed by scan artifacts limiting the quantitative interpretation of STEM datasets. Here, a novel bias-corrected non-rigid registration approach is presented that compensates for fast and slow scan artifacts in STEM image series. The bias-correction is responsible for the correction of the slow scan artifacts and based on a explicit coupling of the deformations of the individual images in a series via a minimization of the average deformation. This allows to reduce fast scan noise in an image series and slow scan distortions simultaneously. The novel approach is tested on synthetic and experimental images and its implication on atomic resolution strain and elemental mapping is discussed.

A 3D Rotating Laser-Based Navigation Solution for Micro Aerial Vehicles in Dynamic Environments

In this paper, we present a 3D rotating laser-based navigation framework for micro aerial vehicles (MAVs) to fly autonomously in dynamic environments. It consists of a 6-degree of freedom (DoF) localization module and a 3D dynamic mapping module. A self-designed rotating laser scanner generates dense point clouds in which 3D features are extracted and aligned. The localization module is able to solve scan distortion issue while estimating the 6-DoF pose of MAVs. At the same time, the dynamic mapping module can further eliminate dynamic trails so that a clear dense 3D map is reconstructed. The dynamic targets are detected based on the spatial constraints and therefore without the need of dense point cloud clustering. Through filtering the detected dynamic obstacles, the localization approach can be robust to the dynamic environment variations. To verify the robustness and effectiveness of our proposed framework, we have tested our system in both real indoor environment with dynamic obstacles and outdoor foliage condition using a customized MAV platform.

Constant linear velocity spiral scanning for near video rate 4D OCT ophthalmic and surgical imaging with isotropic transverse sampling

Ultrahigh speed optical coherence tomography (OCT) systems with >100 kHz A-scan rates can generate volumes rapidly with minimal motion artifacts and are well suited for 4D imaging (volumes through time) applications such as intra-operative imaging. In such systems, high OCT data acquisition efficiency (defined as the fraction of usable A-scans generated during the total acquisition time) is desired to maximize the volumetric frame rate and sampling pitch. However, current methods for beam scanning using non-resonant and resonant mirror scanners can result in severe scan distortion and transverse oversampling as well as require acquisition dead times, which limit the acquisition efficiency and performance of ultrahigh speed 4D OCT. We introduce constant linear velocity spiral scanning (CLV-SC) as a novel beam scanning method to maximize the data acquisition efficiency of ultrahigh speed 4D OCT systems. We demonstrate that CLV-SC does not require acquisition dead times and achieves more uniform transverse sampling compared to raster scanning. To assess its clinical utility, we implement CLV-SC with a 400 kHz OCT system and image the anterior eye and retina of healthy adults at up to 10 volumes per second with isotropic transverse sampling, allowing B-scans with equal sampling pitch to be extracted from arbitrary locations within a single volume. The feasibility of CLV-SC for intra-operative imaging is also demonstrated using a 800 kHz OCT system to image simulated retinal surgery at 15 volumes per second with isotropic transverse sampling, resulting in high quality volume renders that enable clear visualization of surgical instruments and manipulation of tissue.

Correction of phase-delay distortion for α-β circular scanning.

α-β circular scanning with a large scanning field of view and high reliability can be widely applied in laser scanning imaging systems and laser processing. However, mechanical inertia of the galvanometers introduces phase delay and ultimately leads to scanning distortions in α-β circular scanning in both constant angular velocity scanning (CAVS) and constant line velocity scanning (CLVS). To compensate for the phase-delay distortions, two correction models are respectively proposed for CAVS and CLVS, which utilize phase-frequency relationships based on the galvanometer's transfer function. Experimental results show that the presented models can effectively correct rotation distortion in CAVS and tortuosity distortion in CLVS. The correction of phase-delay distortion can improve the image quality and refine positioning accuracy in laser scanning systems.

Detection and Recognition of Traffic Planar Objects Using Colorized Laser Scan and Perspective Distortion Rectification

Reliable detection and recognition of planar objects including traffic sign, street sign, and road surface in dynamic cluttered natural scenes are a big challenge for self-driving cars. In this paper, we propose a comprehensive method for planar object detection and recognition. First, the data association of LIDAR and camera is set up to acquire colorized laser scans, which simultaneously contain both color and geometrical information. Second, we combine three color spaces of RGB, HSV, and CIE L*a*b* with laser reflectivity as an aggregation-based feature vector. Third, the 3-D geometrical characteristics of planar objects that contain planarity, size, and aspect ratio are exploited to further reduce false alarm. Fourth, in order to increase robustness to any viewpoint variation, we present a new virtual camera-based rectification method to synthesize fronto-parallel views of refined object descriptors in 3-D space. Finally, experimental results achieved under a variety of challenging conditions show that integration of color space aggregation and laser reflectivity is superior to individuals. Specifically, the proposed perspective distortion rectification method remarkably eliminates false recognition error by 45.5%. Overall, the detection rate of our comprehensive method has up to 95.87% and the recognition rate even reaches 95.07% for traffic signs ranging within 100 m, with about 33.25 ms average running time per frame.