Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “image simulation”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Initial Investigation of the Small Feature Detection Capability of the ORNL Fast Neutron Tomographic Imaging System

A variety of fast neutron imaging simulations and measurements were performed to investigate the spatial resolution and small feature detection capability of a version of the Oak Ridge National Laboratory fast neutron tomographic imaging system. Two image quality indicators were examined: (1) a variety of long steel pins embedded axially in the interior of a polyethylene cylinder, and (2) a variety of short steels pins embedded radially in the surface of a polyethylene cylinder. Measurements demonstrated detectability of about 3 mm. Further data analysis may show improved detection performance and allow a more precise determination of the spatial resolution. Our current simulation code takes only partial consideration of the DT generator neutron production spot size, with neutron production effectively originating at a single point. Simulations showed that features less than 2 mm should be detectable with an improved generator. Our current ING-27 DT generator has a neutron production spot size of about 3.5 mm, which appears to be the limiting factor at present. Generators with spot sizes as small as 1 mm are commercially available. Higher-power, small–spot size associated particle generators are at the prototype stage and are expected to be commercially available soon.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

The effect of scanning jitter on geometric phase analysis in STEM images

Geometric phase analysis (GPA) is a useful method to map strain distribution in atomically resolved scanning/transmission electron microscopy (S/TEM) images. Nevertheless, the inevitable periodic jitter of electron probe in STEM along the scanning direction due to the interference of electric power supply, including grounding, can give rise to major artifacts, as evidenced by the appearance of satellite spots surrounding all main peaks in the power spectrum of the images. Here we reveal the origin of the image artifacts related to the probe jitter by mapping the image distortion component εxx using the GPA algorithm. The effect is verified by introducing a periodic displacement field to a STEM image simulated from a perfect crystal structure, and the calculated εxx maps show very good agreement with the experimental observations. Based on the quantitative analysis of the images distortion, we propose and test a feasible strategy to eliminate the effect of probe jitter from STEM images. Successful examples illustrate that the approach can help improve the accuracy in quantification of STEM images.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1998

Multi-Scale Fractal Analysis of Image Texture and Pattern

Fractals embody important ideas of self-similarity, in which the spatial behavior or appearance of a system is largely independent of scale. Self-similarity is defined as a property of curves or surfaces where each part is indistinguishable from the whole, or where the form of the curve or surface is invariant with respect to scale. An ideal fractal (or monofractal) curve or surface has a constant dimension over all scales, although it may not be an integer value. This is in contrast to Euclidean or topological dimensions, where discrete one, two, and three dimensions describe curves, planes, and volumes. Theoretically, if the digital numbers of a remotely sensed image resemble an ideal fractal surface, then due to the self-similarity property, the fractal dimension of the image will not vary with scale and resolution. However, most geographical phenomena are not strictly self-similar at all scales, but they can often be modeled by a stochastic fractal in which the scaling and self-similarity properties of the fractal have inexact patterns that can be described by statistics. Stochastic fractal sets relax the monofractal self-similarity assumption and measure many scales and resolutions in order to represent the varying form of a phenomenon as a function of local variables across space. In image interpretation, pattern is defined as the overall spatial form of related features, and the repetition of certain forms is a characteristic pattern found in many cultural objects and some natural features. Texture is the visual impression of coarseness or smoothness caused by the variability or uniformity of image tone or color. A potential use of fractals concerns the analysis of image texture. In these situations it is commonly observed that the degree of roughness or inexactness in an image or surface is a function of scale and not of experimental technique. The fractal dimension of remote sensing data could yield quantitative insight on the spatial complexity and information content contained within these data. A software package known as the Image Characterization and Modeling System (ICAMS) was used to explore how fractal dimension is related to surface texture and pattern. The ICAMS software was verified using simulated images of ideal fractal surfaces with specified dimensions. The fractal dimension for areas of homogeneous land cover in the vicinity of Huntsville, Alabama was measured to investigate the relationship between texture and resolution for different land covers.

Emerson, Charles W.↗
DOE OSTI2019

High resolution for confocal fluorescence microscopy via extending zero-region of super-oscillation

Superoscillation is the phenomenon that is observed when a wave oscillates locally faster than its highest Fourier component. Although previous reports have been shown that the superoscillation is highly attractive for imaging, however, the small zero-region area of the superoscillation increases the remarkable effect of the outsidelobes. In this work, we introduce a method using a binary phase mask with radial polarization to extend the zero-region of the superoscillation for high numerical aperture objectives. We successfully design a binary phase mask combining with a radial polarization to obtain a big zero-region of the superoscillation. Evaluation methods rely on point spread function and simulation images are presented. The results demonstrate that our proposed method is very effective for suppressing the outsidelobes. In addition, we show that our technique becomes more effective by adding an amplitude mask.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Gradient descent algorithm applied to wavefront retrieval from through-focus images by an extreme ultraviolet microscope with partially coherent source

The wavefront retrieval by gradient descent algorithm that is typically applied to coherent or incoherent imaging is extended to retrieve a wavefront from a series of through-focus images by partially coherent illumination. For accurate retrieval, we modeled partial coherence as well as object transmittance into the gradient descent algorithm. However, this modeling increases the computation time due to the complexity of partially coherent imaging simulation that is repeatedly used in the optimization loop. To accelerate the computation, we incorporate not only the Fourier transform but also an eigenfunction decomposition of the image. As a demonstration, the extended algorithm is applied to retrieve a field-dependent wavefront of a microscope operated at extreme ultraviolet wavelength (13.4 nm). The retrieved wavefront qualitatively matches the expected characteristics of the lens design.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Deblending galaxies with variational autoencoders: A joint multiband, multi-instrument approach

ABSTRACT Blending of galaxies has a major contribution in the systematic error budget of weak-lensing studies, affecting photometric and shape measurements, particularly for ground-based, deep, photometric galaxy surveys, such as the Rubin Observatory Legacy Survey of Space and Time (LSST). Existing deblenders mostly rely on analytic modelling of galaxy profiles and suffer from the lack of flexible yet accurate models. We propose to use generative models based on deep neural networks, namely variational autoencoders (VAE), to learn probabilistic models directly from data. We train a VAE on images of centred, isolated galaxies, which we reuse, as a prior, in a second VAE-like neural network in charge of deblending galaxies. We train our networks on simulated images including six LSST bandpass filters and the visible and near-infrared bands of the Euclid satellite, as our method naturally generalizes to multiple bands and can incorporate data from multiple instruments. We obtain median reconstruction errors on ellipticities and r-band magnitude between ±0.01 and ±0.05, respectively, in most cases, and ellipticity multiplicative bias of 1.6 per cent for blended objects in the optimal configuration. We also study the impact of decentring and prove the method to be robust. This method only requires the approximate centre of each target galaxy, but no assumptions about the number of surrounding objects, pointing to an iterative detection/deblending procedure we leave for future work. Finally, we discuss future challenges about training on real data and obtain encouraging results when applying transfer learning.

Arcelin, Bastien↗
DOE OSTI2024

The Impact of Bias Row Noise to Photometric Accuracy: Case Study Based on a Scientific CMOS Detector

Abstract We tested a new model of CMOS detector manufactured by the Gpixel Inc, for potential space astronomical application. In laboratory, we obtain some bias images under the typical application environment. In these bias images, clear random row noise pattern is observed. The row noise also contains some characteristic spatial frequencies. We quantitatively estimated the impact of this feature to photometric measurements, by making simulated images. We compared different bias noise types under strict parameter control. The result shows the row noise will significantly deteriorate the photometric accuracy. It effectively increases the readout noise by a factor of 2–10. However, if it is properly removed, the image quality and photometric accuracy will be significantly improved.

Astronomy & Astrophysics↗
NASA NTRS1998

Dust Morphology of Comet Hale-Bopp (C/1995 01). II. Introduction of a Working Model

A Monte Carlo image simulation code for dust features in comets is applied to comet Hale-Bopp in order to model the object's persistent porcupine-like appearance on high-resolution images taken between May 11 and November 2, 1996. In this scenario, the dust-emission profile is dominated by several brief flare-ups, or puffs in the production of dust from one of the sources.

comet↗
DOE OSTI2013

SIMULTANEOUS MULTI-BAND DETECTION OF LOW SURFACE BRIGHTNESS GALAXIES WITH MARKOVIAN MODELING

We present to the astronomical community an algorithm for the detection of low surface brightness (LSB) galaxies in images, called MARSIAA (MARkovian Software for Image Analysis in Astronomy), which is based on multi-scale Markovian modeling. MARSIAA can be applied simultaneously to different bands. It segments an image into a user-defined number of classes, according to their surface brightness and surroundings-typically, one or two classes contain the LSB structures. We have developed an algorithm, called DetectLSB, which allows the efficient identification of LSB galaxies from among the candidate sources selected by MARSIAA. The application of the method to two and three bands simultaneously was tested on simulated images. Based on our tests, we are confident that we can detect LSB galaxies down to a central surface brightness level of only 1.5 times the standard deviation from the mean pixel value in the image background. To assess the robustness of our method, the method was applied to a set of 18 B- and I-band images (covering 1.3 deg{sup 2} in total) of the Virgo Cluster to which Sabatini et al. previously applied a matched-filter dwarf LSB galaxy search algorithm. We have detected all 20 objects from the Sabatini et al. catalog which we could classify by eye as bona fide LSB galaxies. Our method has also detected four additional Virgo Cluster LSB galaxy candidates undetected by Sabatini et al. To further assess the completeness of the results of our method, both MARSIAA, SExtractor, and DetectLSB were applied to search for (1) mock Virgo LSB galaxies inserted into a set of deep Next Generation Virgo Survey (NGVS) gri-band subimages and (2) Virgo LSB galaxies identified by eye in a full set of NGVS square degree gri images. MARSIAA/DetectLSB recovered {approx}20% more mock LSB galaxies and {approx}40% more LSB galaxies identified by eye than SExtractor/DetectLSB. With a 90% fraction of false positives from an entirely unsupervised pipeline, a completeness of 90% is reached for sources with r{sub e} > 3'' at a mean surface brightness level of {mu}{sub g} = 27.7 mag arcsec{sup -2} and a central surface brightness of {mu}{sup 0}{sub g} = 26.7 mag arcsec{sup -2}. About 10% of the false positives are artifacts, the rest being background galaxies. We have found our proposed Markovian LSB galaxy detection method to be complementary to the application of matched filters and an optimized use of SExtractor, and to have the following advantages: it is scale free, can be applied simultaneously to several bands, and is well adapted for crowded regions on the sky.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

WE-E-BRF-01: The ESTRO-AAPM Joint Symposium On Imaging for Proton Treatment Planning and Guidance

In this first inaugural joint ESTRO-AAPM session we will attempt to provide some answers to the problems encountered in the clinical application of particle therapy. Indeed the main advantage is that the physical properties of ion beams offer high ballistic accuracy for tightly conformal irradiation of the tumour volume, with excellent sparing of surrounding healthy tissue and critical organs, This also its Achilles' heel calling for an increasing role of imaging to ensure safe application of the intended dose to the targeted area during the entire course of fractionated therapy. We have three distinguished speakers addressing possible solutions. Katia Parodi (Ludwig Maximilians University, Munich, Germany) To date, Positron Emission Tomography (PET) is the only technique which has been already clinically investigated for in-vivo visualization of the beam range during or shortly after ion beam delivery. The method exploits the transient amount of β{sup 2}-activity induced in nuclear interactions between the primary beam and the irradiated tissue, depending on the ion beam species, the tissue elemental composition and physiological properties (in terms of biological clearance), as well as the time course of irradiation and imaging. This contribution will review initial results, ongoing methodological developments and remaining challenges related to the clinical usage of viable but often suboptimal instrumentation and workflows of PET-based treatment verification. Moreover, it will present and discuss promising new detector developments towards next-generation dedicated PET scanners relying on full-ring or dual-head designs for in-beam quasi real-time imaging. Denis Dauvergne (Institut de Physique Nucleaire de Lyon, Lyon, France) Prompt gamma radiation monitoring of hadron therapy presents the advantage of real time capability to measure the ion range. Both simulations and experiments show that millimetric verification of the range can be achieved at the pencil beam scale for active proton beam delivery in homogenous targets. The development of gamma cameras, that has been studied by several groups worldwide over the last years, now reaches - for some of them - the stage of being applicable in clinical conditions, with real size prototypes and count rate capability matching the therapeutic beam intensities. We will review the different concepts of gamma cameras, the advantages and limitations of this method, and the main challenges that should still be overcome before the widespread of prompt gamma quality assurance for proton and hadrontherapy. Jon Kruse (Mayo Clinic, Rochester, MN, USA) Treatment simulation images for proton therapy are used to determine proton stopping power and range in the patient. This talk will discuss the careful control of CT numbers and conversion of CT number to stopping power required in proton therapy. Imaging for treatment guidance of proton therapy also presents unique challenges which will be addressed. Among them are the enhanced relationship between internal anatomy changes and dosimetry, the need for imaging to support adaptive planning protocols, and high operational efficiency. Learning Objectives: To learn about the possibilities of using activation products to determine the range of particle beams in a patient treatment setting To be informed on an alternative methodology using prompt gamma detectors To understand the impact of the accuracy of the knowledge of the patient information with respect to the delivered treatment.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

Collimator design for a dedicated molecular breast imaging-guided biopsy system: Proof-of-concept

Purpose: Molecular breast imaging (MBI) is a dedicated nuclear medicine breast imaging modality that employs dual-head cadmium zinc telluride (CZT) gamma cameras to functionally detect breast cancer. MBI has been shown to detect breast cancers otherwise occult on mammography and ultrasound. Currently, a MBI-guided biopsy system does not exist to biopsy such lesions. Our objective was to consider the utility of a novel conical slant-hole (CSH) collimator for rapid (<1 min) and accurate monitoring of lesion position to serve as part of a MBI-guided biopsy system. Methods: An initial CSH collimator design was derived from the dimensions of a parallel-hole collimator optimized for MBI performed with dual-head CZT gamma cameras. The parameters of the CSH collimator included the collimator height, cone slant angle, thickness of septa and cones of the collimator, and the annular areas exposed at the base of the cones. These parameters were varied within the geometric constraints of the MBI system to create several potential CSH collimator designs. The CSH collimator designs were evaluated using Monte Carlo simulations. The model included a breast compressed to a thickness of 6 cm with a 1-cm diameter lesion located 3 cm from the collimator face. The number of particles simulated was chosen to represent the count density of a low-dose, screening MBI study acquired with the parallel-hole collimator for 10 min after a {approx}150 MBq (4 mCi) injection of Tc-99m sestamibi. The same number of particles was used for the CSH collimator simulations. In the resulting simulated images, the count sensitivity, spatial resolution, and accuracy of the lesion depth determined from the lesion profile width were evaluated. Results: The CSH collimator design with default parameters derived from the optimal parallel-hole collimator provided 1-min images with error in the lesion depth estimation of 1.1 {+-} 0.7 mm and over 21 times the lesion count sensitivity relative to 1-min images acquired with the current parallel-hole collimator. Sensitivity was increased via more vertical cone slant angles, larger annular areas, thinner cone walls, shorter cone heights, and thinner radiating septa. Full width at half maximum trended in the opposite direction as sensitivity for all parameters. There was less error in the depth estimates for less vertical slant angles, smaller annular areas, thinner cone walls, cone heights near 1 cm, and generally thinner radiating septa. Conclusions: A Monte Carlo model was used to demonstrate the feasibility of a CSH collimator design for rapid biopsy application in molecular breast imaging. Specifically, lesion depth of a 1-cm diameter lesion positioned in the center of a typical breast can be estimated with error of less than 2 mm using circumferential count profiles of images acquired in 1 min.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2012

Chemical contrast in STM imaging of transition metal aluminides

The present manuscript reviews recent scanning tunnelling microscopy (STM) studies of transition metal (TM) aluminide surfaces. It provides a general perspective on the contrast between Al atoms and TM atoms in STM imaging. A general trend is the much stronger bias dependence of TM atoms, or TM-rich regions of the surface. This dependence can be attenuated by the local chemical arrangements and environments. Al atoms can show a stronger bias dependence when their chemical environment, such as their immediate subsurface, is populated with TM. All this is well explained in light of combined results of STM and both theoretical and experimental electronic and crystallographic structure determinations. Since STM probes the Fermi surface, the electronic structure in the vicinity of the Fermi level (EF) is essential for understanding contrast and bias dependence. Hence, partial density of states provides information about the TM d band position and width, s–p–d hybridization or interactions, or charge transfer between constituent elements. In addition, recent developments in STM image simulations are very interesting for elucidating chemical contrast at Al–TM alloy surfaces, and allow direct atomic identification, when the surface does not show too much disorder. Overall, we show that chemically-specific imaging is often possible at these surfaces.

36 MATERIALS SCIENCE↗
NASA NTRS2020

Optical Navigation for Autonomous Approach of Small Unknown Bodies

State of the practice in navigation around small celestial bodies heavily relies on ground sup- port and human skill, in particular, for perception-based operations such as optical navigation and mapping. This leads to longer duration and more complex mission operations and sub- sequently higher cost. Furthermore, it imposes limitations for certain missions such as fast fly-bys or multi-agent operations. In this work, we present an autonomous navigation strat- egy suitable for approaching small unexplored bodies. During the approach, we estimate the body’s physical properties as well as the spacecraft’s relative trajectory and associated un- certainties. The autonomous navigation strategy, which is solely based on optical measure- ments, begins as soon as the body becomes resolved in the navigation camera and terminates at the start of proximity operations, when the spacecraft makes its first trajectory correction to stay in the vicinity of the body. Our strategy uses multiple image-processing algorithms: light-curve analysis for estimating the target body’s rotation rate, Shape-from-Silhouette for reconstructing the 3D shape and estimating its rotation pole, and feature tracking tailored to Small-Body images for estimating relative navigation parameters. We used the Mission Analysis, Operations, and Navigation Toolkit Environment (MONTE) developed by the Jet Propulsion Laboratory to evaluate the feasibility of this multi-phase navigation strategy using simulated images of an approach trajectory. We used the Rosetta mission data to generate photorealistic images to characterise the performance of this approach. This work is based on the assumptions that the spacecraft attitude is known, the body is a principal-axis rotator, a-priori estimates of ephemerides and scale are available, and the body is observed from a zero sun phase only during initial approach. Preliminary results show orbit determination performance that is on par with the human navigation from the Rosetta mission; albeit with a 1% bias in spacecraft-target radial distance estimate. The bias error is likely due to the robustness and accuracy of the visual tracking under dynamic lighting conditions and per- spective changes, which decrease accuracy.

Villa, Jacopo↗
NASA NTRS1992

A vision architecture for the extravehicular activity retriever

The Extravehicular Activity Retriever (EVAR) is a robotic device currently being developed by the Automation and Robotics Division at the NASA Johnson Space Center to support activities in the neighborhood of the Space Shuttle or Space Station Freedom. As the name implies, the Retriever's primary function will be to provide the capability to retrieve tools, equipment or other objects which have become detached from the spacecraft, but it will also be able to rescue a crew member who may have become inadvertently de-tethered. Later goals will include cooperative operations between a crew member and the Retriever such as fetching a tool that is required for servicing or maintenance operations. This report documents a preliminary design for a Vision System Planner (VSP) for the EVAR that is capable of achieving visual objectives provided to it by a high level task planner. Typical commands which the task planner might issue to the VSP relate to object recognition, object location determination, and obstacle detection. Upon receiving a command from the task planner, the VSP then plans a sequence of actions to achieve the specified objective using a model-based reasoning approach. This sequence may involve choosing an appropriate sensor, selecting an algorithm to process the data, reorienting the sensor, adjusting the effective resolution of the image using lens zooming capability, and/or requesting the task planner to reposition the EVAR to obtain a different view of the object. An initial version of the Vision System Planner which realizes the above capabilities using simulated images has been implemented and tested. The remaining sections describe the architecture and capabilities of the VSP and its relationship to the high level task planner. In addition, typical plans that are generated to achieve visual goals for various scenarios will be discussed. Specific topics to be addressed will include object search strategies, repositioning of the EVAR to improve the quality of information obtained from the sensors, complementary usage of the sensors and redundant capabilities.

Magee, Michael↗
NASA NTRS1993

A vision system planner for increasing the autonomy of the Extravehicular Activity Helper/Retriever

The Extravehicular Activity Retriever (EVAR) is a robotic device currently being developed by the Automation and Robotics Division at the NASA Johnson Space Center to support activities in the neighborhood of the Space Shuttle or Space Station Freedom. As the name implies, the Retriever's primary function will be to provide the capability to retrieve tools and equipment or other objects which have become detached from the spacecraft, but it will also be able to rescue a crew member who may have become inadvertently de-tethered. Later goals will include cooperative operations between a crew member and the Retriever such as fetching a tool that is required for servicing or maintenance operations. This paper documents a preliminary design for a Vision System Planner (VSP) for the EVAR that is capable of achieving visual objectives provided to it by a high level task planner. Typical commands which the task planner might issue to the VSP relate to object recognition, object location determination, and obstacle detection. Upon receiving a command from the task planner, the VSP then plans a sequence of actions to achieve the specified objective using a model-based reasoning approach. This sequence may involve choosing an appropriate sensor, selecting an algorithm to process the data, reorienting the sensor, adjusting the effective resolution of the image using lens zooming capability, and/or requesting the task planner to reposition the EVAR to obtain a different view of the object. An initial version of the Vision System Planner which realizes the above capabilities using simulated images has been implemented and tested. The remaining sections describe the architecture and capabilities of the VSP and its relationship to the high level task planner. In addition, typical plans that are generated to achieve visual goals for various scenarios are discussed. Specific topics to be addressed will include object search strategies, repositioning of the EVAR to improve the quality of information obtained from the sensors, and complementary usage of the sensors and redundant capabilities.

Magee, Michael↗
NASA NTRS1987

Image based SAR product simulation for analysis

SAR product simulation serves to predict SAR image gray values for various flight paths. Input typically consists of a digital elevation model and backscatter curves. A new method is described of product simulation that employs also a real SAR input image for image simulation. This can be denoted as 'image-based simulation'. Different methods to perform this SAR prediction are presented and advantages and disadvantages discussed. Ascending and descending orbit images from NASA's SIR-B experiment were used for verification of the concept: input images from ascending orbits were converted into images from a descending orbit; the results are compared to the available real imagery to verify that the prediction technique produces meaningful image data.

Domik, G.↗
DOE OSTI2021

Sensitivity of back‐projection algorithm (BPA) synthetic aperture radar (SAR) image formation to initial position, velocity, and attitude navigation errors

Abstract The Back‐Projection Algorithm (BPA) is a time‐domain‐matched filtering technique to form synthetic aperture radar (SAR) images. To produce high‐quality BPA images, precise navigation data for the radar platform must be known. Errors in position, velocity, or attitude result in improperly formed images that are corrupted by shifting and blurring. The contribution of this paper is the development of analytical expressions that characterise the relationship between navigation errors and image formation errors from an inertial navigation point of view, where trajectory estimation errors in position, velocity, and attitude propagate through time and cause compounding errors in the vehicle state vector. These analytical expressions are verified via simulated image formation and real‐data image formation.

Lindstrom, Colton↗