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Three-dimensional surface templates are being used to identify and locate landmarks on Mars and Phobos. They can be aligned both with images and the MOLA map to help tie these two data types together. The Martian templates form a control network of well-defined and easily identified landmarks.
A technique was created to measure the pupil alignment of instruments in situ by measuring calibrated pupil alignment references (PARs) in instruments. The PAR can also be measured using an alignment telescope or an imaging system. PAR allows the verification of the science instrument (SI) pupil alignment at the integrated science instrument module (ISIM) level of assembly at ambient and cryogenic operating temperature. This will allow verification of the ISIM+SI alignment, and provide feedback to realign the SI if necessary.
Pin-point landing is required to enable missions to land close, typically within 10 meters, to scientifically important targets in generally hazardous terrain. In Pin Point Landing both high accuracy and high speed estimation of position and orientation is needed to provide input to the control system to safely choose and navigate to a safe landing site. A proposed algorithm called VISion aided Inertial NAVigation (VISINAV) has shown that the accuracy requirements can be met. [2][3] VISINAV was shown in software only, and was expected to use FPGA enhancements in the future to improve the computational speed needed for pin point landing during Entry Descent and Landing (EDL). Homography, feature detection and spatial correlation are computationally intensive parts of VISINAV. Homography aligns the map image with the descent image so that small correlation windows can be used, and feature detection provides regions that spatial correlation can track from frame to frame in order to estimate vehicle motion. On MER the image Homography, Feature Detection and Correlation would take approximately 650ms tracking 75 features between frames. We implemented Homography, Feature detection and Correlation on a Virtex 4 LX160 FPGA to run in under 25ms while tracking 500 features to improve algorithm reliability and throughput.
MatchGUI software, based on MATLAB, automatically matches two images and displays the match result by superimposing one image on the other. A slider bar allows focus to shift between the two images. There are tools for zoom, auto-crop to overlap region, and basic image markup. Given a pair of ortho-rectified images (focused primarily on Mars orbital imagery for now), this software automatically co-registers the imagery so that corresponding image pixels are aligned. MatchGUI requires minimal user input, and performs a registration over scale and inplane rotation fully automatically
This invention documents the efforts on the research and development of a miniaturized GPS/MEMS IMU integrated navigation system. A miniaturized GPS/MEMS IMU integrated navigation system is presented; Laser Dynamic Range Imager (LDRI) based alignment algorithm for space applications is discussed. Two navigation cameras are also included to measure the range and range rate which can be integrated into the GPS/MEMS IMU system to enhance the navigation solution.
A set of co-aligned high resolution images from the Atmospheric Imaging Assembly (AIA) on board the Solar Dynamics Observatory (SDO) is used to investigate propagating disturbances (PDs) in warm fan loops at the periphery of a non-flaring active region NOAA AR 11082. To measure PD speeds at multiple coronal temperatures, a new data analysis methodology is proposed enabling quantitative description of sub visual coronal motions with low signal-to-noise ratios of the order of 0.1. The technique operates with a set of one-dimensional surfing signals extracted from position-timeplots of several AIA channels through a modified version of Radon transform. The signals are used to evaluate a two-dimensional power spectral density distribution in the frequency - velocity space which exhibits a resonance in the presence of quasi-periodic PDs. By applying this analysis to the same fan loop structures observed in several AIA channels, we found that the traveling velocity of PDs increases with the temperature of the coronal plasma following the square root dependence predicted for the slow mode magneto-acoustic wave which seems to be the dominating wave mode in the studied loop structures. This result extends recent observations by Kiddie et al. (2012) to a more general class of fan loop systems not associated with sunspots and demonstrating consistent slow mode activity in up to four AIA channels.
Time-resolved, high-speed self-aligned focusing schlieren images were acquired in the NASA Glenn Research Center Transonic Turbine Blade Cascade facility to help understand the aerodynamic behavior of high-pressure, thick trailing edge turbine blades. The trailing edge thickness of 9% of axial chord tested represents simulated ceramic matrix composite fabrication constraints, which was verified previously to possess a high-loss flow regime at high inlet turbulence conditions over a narrow range of Reynolds numbers and at a fixed design exit Mach number of 0.74. Our high-speed images, which were acquired at 10 distinct Reynolds numbers, show a significant increase in energy from flow oscillations due to transonic vortex shedding at Reynolds numbers corresponding to the high loss conditions. For those conditions, strong acoustic waves turn into shock waves. Spectral Proper Orthogonal Decomposition of the high-speed images shows acoustic waves from trailing edge vortex shedding at all conditions, with increased spectral energy at the high-loss conditions and slightly increasing frequency (about 6%) as a function of Reynolds number. Analysis of potential feedback timing is performed using velocity fields from a previous LES simulation, considering different feedback mechanisms. Most noteworthy is the acoustic/shock-boundary layer interaction mechanism on the suction surface at the blade geometric throat, which likely plays an important role in realistic curved blade passages.
Shadowgraph system projects magnified image on screen so that alignment of small electrodes mounted on electrical discharge machines can be corrected and verified. Technique may be adapted to other machine tool equipment where physical contact cannot be made during inspection and access to tool limits conventional runout checking procedures.
Purpose: In proton therapy, patient alignment is of critical importance due to the sensitivity of the proton range to tissue heterogeneities. Traditionally proton radiography is used for verification of the water-equivalent path length (WEPL), which dictates the depth protons reach. In this work we propose its use for alignment. Additionally, many new proton centers have cone-beam computed tomography in place of beamline X-ray imaging and so proton radiography offers a unique patient alignment verification similar to portal imaging in photon therapy. Method: Proton radiographs of a CIRS head phantom were acquired using the Beam Imaging System (BIS) (IBA, Louvain-la-Neuve) in a horizontal beamline. A scattered beam was produced using a small, dedicated, range modulator (RM) wheel fabricated out of aluminum. The RM wheel was rotated slowly (20 sec/rev) using a stepper motor to compensate for the frame rate of the BIS (120 ms). Dose rate functions (DRFs) over two RM wheel rotations were acquired. Calibration was made with known thicknesses of homogeneous solid water. For each pixel the time width, skewness and kurtosis of the DRFs were computed. The time width was used to compute the object WEPL. In the heterogeneous phantom, the excess skewness and excess kurtosis (i.e. difference from homogeneous cases) were computed and assessed for suitability for patient set up. Results: The technique allowed for the simultaneous production of images that can be used for WEPL verification, showing few internal details, and excess skewness and kurtosis images that can be used for soft tissue alignment. These latter images highlight areas where range mixing has occurred, correlating with phantom heterogeneities. Conclusion: The excess skewness and kurtosis images contain details that are not visible in the WET images. These images, unique to the time-resolved proton radiographic method, could be used for patient set up according to soft tissues.
FeCo thin films are fabricated by alternate monoatomic layer deposition method on a Cu{sub 3}Au buffer layer, which in-plane lattice constant is very close to the predicted value to obtain a large magnetic anisotropy constant. The variation of the in-plane lattice constant during the deposition process is investigated by reflection high-energy electron diffraction. The magnetic domain images are also observed by a photoelectron emission microscope in order to microscopically understand the magnetic structure. As a result, element-specific magnetic domain images show that Fe and Co magnetic moments align parallel. A series of images obtained with various azimuth reveal that the FeCo thin films show fourfold in-plane magnetic anisotropy along 〈110〉 direction, and that the magnetic domain structure is composed only of 90∘ wall.
X-rays offer high penetration with the potential for tomography of centimetre-sized specimens, but synchrotron beamlines often provide illumination that is only millimetres wide. Here an approach is demonstrated termed Tomosaic for tomographic imaging of large samples that extend beyond the illumination field of view of an X-ray imaging system. This includes software modules for image stitching and calibration, while making use of existing modules available in other packages for alignment and reconstruction. The approach is compatible with conventional beamline hardware, while providing a dose-efficient method of data acquisition. By using parallelization on a distributed computing system, it provides a solution for handling teravoxel-sized or larger datasets that cannot be processed on a single workstation in a reasonable time. Using experimental data, the package is shown to provide good quality three-dimensional reconstruction for centimetre-sized samples with sub-micrometre pixel size.
Purpose: To compute daily dose delivered during radiotherapy, deformable registration needs to be relatively fast, automated, and accurate. The aim of this study was to evaluate the performance of commercial deformable registration software for deforming between two modalities: planning computed tomography (pCT) images acquired for treatment planning and cone beam (CB) CT images acquired prior to each fraction of prostate cancer radiotherapy. Methods: A workflow was designed using MIM Software™ that aligned and deformed pCT into daily CBCT images in two steps: (1) rigid shifts applied after daily CBCT imaging to align patient anatomy to the pCT and (2) normalized intensity-based deformable registration to account for interfractional anatomical variations. The physician-approved CTV and organ and risk (OAR) contours were deformed from the pCT to daily CBCT over the course of treatment. The same structures were delineated on each daily CBCT by a radiation oncologist. Dice similarity coefficient (DSC) mean and standard deviations were calculated to quantify the deformable registration quality for prostate, bladder, rectum and femoral heads. Results: To date, contour comparisons have been analyzed for 31 daily fractions of 2 of 10 of the cohort. Interim analysis shows that right and left femoral head contours demonstrate the highest agreement (DSC: 0.96±0.02) with physician contours. Additionally, deformed bladder (DSC: 0.81±0.09) and prostate (DSC: 0.80±0.07) have good agreement with physician-defined daily contours. Rectum contours have the highest variations (DSC: 0.66±0.10) between the deformed and physician-defined contours on daily CBCT imaging. Conclusion: For structures with relatively high contrast boundaries on CBCT, the MIM automated deformable registration provided accurate representations of the daily contours during treatment delivery. These findings will permit subsequent investigations to automate daily dose computation from CBCT. However, improved methods need to be investigated to improve deformable results for rectum contours.
To investigate the feasibility of interior imaging reconstruction in soft X-ray tomography for higher-resolution cellular imaging, including whole-cell imaging, we develop an alignment and reconstruction algorithm that combines a small number of sparse whole-cell images with a high-resolution local interior scan. Based on numerical simulations, we demonstrate that combined reconstructions mitigate the depth-of-field limitation in high-resolution scans, enable radiation dose optimization, and yield quantitative X-ray absorption values with sparse sampling. We further validate our numerical approach using experimental data from two different cell types and show that the combined reconstruction reliably provides high spatial resolution within an interior region of interest of a whole cell. The resulting sparse reconstruction framework offers robust, faithful visualization of cellular organelles in soft X-ray tomography. This mesoscale imaging strategy allows one to ‘scout’ and zoom into selected subcellular volumes of interest, enabling increased spatial resolution without sacrificing larger-volume imaging and providing information on the relative positions of all organelles within a cell.
A method for collecting and processing remotely sensed imagery in order to achieve precise spatial co-registration (e.g., matched alignment) between multi-temporal image sets is presented. Such precise alignment or spatial co-registration of imagery can be used for change detection, image fusion, and temporal analysis/modeling. Further, images collected in this manner may be further processed in such a way that image frames or line arrays from corresponding photo stations are matched, co-aligned and if desired merged into a single image and/or subjected to the same processing sequence. A second methodology for automated detection of moving objects within a scene using a time series of remotely sensed imagery is also presented. Specialized image collection and preprocessing procedures are utilized to obtain precise spatial co-registration (image registration) between multitemporal image frame sets. In addition, specialized change detection techniques are employed in order to automate the detection of moving objects.
In this paper, we focus on exploring the directional assembly of anisotropic Au nanorods along de novo designed 1D protein nanofiber templates. Using machine learning and automated image processing, we analyze scanning electron microscopy (SEM) images to study how the attachment density and alignment fidelity are influenced by variables such as the aspect ratio of the Au nanorods, and the salt concentration of the solution. We find that the Au nanorods prefer to align parallel to the protein nanofibers. This preference decreases with increasing salt concentration, but is only weakly sensitive to the nanorod aspect ratio. While the overall specific Au nanorod attachment density to the protein fibers increases with increasing solution ionic strength, this increase is dominated primarily by non-specific binding to the substrate background, and we find that greater specific attachment (nanorods attached to the nanofiber template as compared to the substrates) occurs at the lower studied salt concentrations, with the maximum ratio of specific to non-specific binding occurring when the protein fiber solutions are prepared in 75 mM NaCl concentration.
Measurements of thermal 0+ ion parameters from the Thermal Ion Dynamics Experiment (TIDE) on POLAR obtained near 5000 km altitude are compared with auroral images from the Ultra Violet Imager (UVI), for southern perigee passes. Ion parameters, including parallel velocity, density, and flux are combined with multiple dayside and nightside auroral images to investigate relationships between O+ field aligned flows and the structure and brightness seen in the auroral forms. Results indicate field aligned upflowing O+ ions over regions of bright auroral activity and downward flows over dark regions. These and other relationships will be presented for several POLAR passes when both ion measurements and auroral images are observed under favorable conditions for comparison.
The author has identified the following significant results. In comparing the interpretation of the imagery with that of photomosaics, the following results were derived. The drainage networks of the RBV images show information in greater detail than the photomosaics, and maps, yet maintain scale differences. However, for the basins the mosaics and maps provide better information. The geomorphology is best interpreted in the images of the ERTS-1, not only for the regional countryside, but also for the morphological formations. It was concluded that the satellite images offer the better possibility for identifying the alignment of joints and faults. In the images the relation is 4 to 1. The considered N-S alignments were identified in both systems with a ratio of 2 to 1. The E-W alignments for the areas considered in the ERTS-1 images show a basic Paleozoic formation not previously detected.
Neutron imagers are important diagnostics for the inertial confinement fusion implosions at the National Ignition Facility. They provide two- and three-dimensional reconstructions of the neutron source shape that are key indicators of the overall performance. To interpret the shape results properly, it is critical to estimate the uncertainty in those reconstructions. There are two main sources of uncertainties: limited neutron statistics, leading to random errors in the reconstructed images, and incomplete knowledge of the instrument response function (the pinhole-dependent point spread function). While the statistical errors dominate the uncertainty for lower yield deuterium-tritium (DT) shots, errors due to the instrument response function dominate the uncertainty for DT yields on the order of 10 16 neutrons or higher. In this work, a bootstrapping method estimates the uncertainty in a reconstructed image due to the incomplete knowledge of the instrument response function. The main reconstruction is created from the fixed collection of pinhole images that are best aligned with the neutron source. Additional reconstructions are then built using subsets of that collection of images. Variations in the shapes of these additional reconstructions originate solely from uncertainties in the instrument response function, allowing us to use them to provide an additional systematic uncertainty estimate.