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At least 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
NASA NTRS2024

Commercial Synthetic Aperture Radar Data for Surface Deformation and Change

The commercial synthetic aperture radar (SAR) market is experiencing year-over-year growth and is currently capable of imaging anywhere in the world within an hour at X-band. Surface Deformation and Change (SDC) is a mission study at NASA to investigate innovative architectures beyond the NASA-ISRO SAR (NISAR) mission in the next decade. In this article we present preliminary findings on the technical capabilities of the currently available commercial SAR data, and investigate their applicability to SDC goals, such as imaging quality and retrieval of surface motion.

SAR↗
DOE OSTI2021

Stable Parallel Training of Wasserstein Conditional Generative Adversarial Neural Networks : *Full/Regular Research Paper submission for the symposium CSCI-ISAI: Artificial Intelligence

We use a stable parallel approach to train Wasserstein Conditional Generative Adversarial Neural Networks (W-CGANs). The parallel training reduces the risk of mode collapse and enhances scalability by using multiple generators that are concurrently trained, each one of them focusing on a single data label. The use of the Wasserstein metric reduces the risk of cycling by stabilizing the training of each generator. We apply the approach on the CIFAR10 and the CIFAR100 datasets, two standard benchmark datasets with images of the same resolution, but different number of classes. Performance is assessed using the inception score, the Fréchet inception distance, and image quality. An improvement in inception score and Fréchet inception distance is shown in comparison to previous results obtained by performing the parallel approach on deep convolutional conditional generative adversarial neural networks (DC-CGANs). Weak scaling is attained on both datasets using up to 100 NVIDIA V100 GPUs on the OLCF supercomputer Summit.

Lupo Pasini, Massimiliano↗
DOE OSTI2023

A Method To Characterize Metalenses For Light Collection Applications

Metalenses and metasurfaces are promising emerging technologies that could improve light collection in light collection detectors, concentrating light on small area photodetectors such as silicon photomultipliers. Here we present a detailed method to characterize metalenses to assess their efficiency at concentrating monochromatic light coming from a wide range of incidence angles, not taking into account their imaging quality.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

An Experimental Feasibility Study on Applying Neutron Tomography to Encapsulated Spent Nuclear Fuel - 20050

Visual inspection makes easier to ensure the integrity and safety of spent nuclear fuel (SNF) than any classical techniques. Various classical techniques have been applied but there are no reliable methods to qualitatively and quantitatively verify spent fuel in dry storage. Thus, the present authors have developed the prototype safeguards apparatus for dry storage employing the array of He-4 gas scintillation detectors (S670E, Arktis Radiation Detectors Ltd., Switzerland), newly designed to simultaneously measure thermal and fast neutrons without any moderators. The S670E detector has a cylindrical shape with a diameter of 52 mm and active length of 600 mm (total length: 875 mm). The detector is filled by He-4 gas with an approximate pressure of 180 bar for fast neutron detection, and its inner wall is coated by Li-6 for thermal neutron detection. The scintillation lights generated via Li-6 nuclear reaction and elastic scattering are collected by 24 SiPMs linearly paired at the center of the detector. The detector delivers a TTL (Transistor-Transistor Logic) output for pulse readout and UART (Universal Asynchronous Receiver Transmitter) for device control. In order to assess feasibility of the apparatus, an experimental system has been designed, built, and optimized via computational studies. Cf-252 neutron sources and linearly arrayed detectors, working as a single detector, were occupied for this study due to the difficulties in working with SNF. The laboratory scale cask (diameter: 0.67 m, height: 1.5 m), minimized by a factor of 10 compared to the actual thickness of a commercial TN-32 cask, was also manufactured. The detector array was designed to rotate the lab-scale cask and obtain 36 image profiles at every 10 degrees. All profiles were aligned in single frame image called a sinogram, and the cross-sectional image was then fabricated by the inverse radon transform algorithm. These experiments have been repeated with different configurations and numbers of sources. Some gamma-ray sources were also measured with neutron sources in order to distinguish between neutron and gamma-ray pulses. Basically, a He-4 detector is designed to run on Linux OS so it is difficult to directly apply to Windows-based equipment widely used in S. Korea. Therefore, a new data acquisition board working on Windows OS was designed and built. The board mainly consists of FPGA (Field Programmable Gate Array) and SoC (System on Chip) for TTL pulse readout, sorting measured data, and transferring data to a user interface. In conclusion, the tomographic system at lab-scale has shown considerable potential to detect a partial or gross defect of encapsulated assemblies in dry storage. Next steps of this study will be to 1) repeatedly carry out experiments to demonstrate scientific reliability and validity, and 2) numerically integrate signals with weight factors to enhance the image quality since the suggested system based on passive interrogation method requires longer measurement time. Finally, the system will apply to a commercial dry storage phased out soon in S. Korea. (authors)

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2024

Production of High Specific Activity 155 Tb, 161 Tb and 203 Pb for Research and Clinical Applications: Effective Target Design, Target Material Recycling and Radioisotope Separation (Final Technical Report)

The overall objectives of this project were (1) to develop methods for the production and separation of a diagnostic and therapeutic or “theranostic” pair of radioisotopes, terbium-155 ( 155 Tb) and terbium-161 ( 161 Tb) and (2) to train graduate students and postdoctoral fellows in technologies and methods used in radionuclide production. Radionuclides can be incorporated into drugs called radiopharmaceuticals that target a specific disease (e.g., cancer). The need for theranostic radionuclides is escalating with the clinical translation of radiopharmaceuticals due to their implementation in personalized medicine, which has demonstrated enhanced patient treatments. High purity and high specific activity radionuclides are critical for theranostic agent development, for example to maintain diagnostic image quality, to minimize radiation dose to the patient, and to increase uptake in the targeted tissue (e.g., tumor), especially in the case of receptor- and antigen-targeted agents. The 155 Tb (diagnostic) and 161 Tb (therapeutic) radioisotopes that were generated through this project are a theranostic pair with demonstrated potential for the development and translation into individualized, targeted, and dosimetry-driven radiotherapies. However, the development of such radiotherapies has been hindered by the lack of a routine and reliable supply of these isotopes in the United States. Methods for the production, separation, and supply of 155 Tb and 161 Tb were investigated and developed in this project. Further, the strong emphasis throughout the project on the training of graduate students and postdoctoral fellows has helped to ensure and enhance the nuclear science workforce through the training of the next generation of highly qualified scientists in nuclear and radiochemistry. This grant also continued a collaboration between scientists at the University of Washington (UW), the University of Missouri (MU) and Brookhaven National Laboratory (BNL). All three institutions were involved in the project, but to different degrees on the various tasks through which the overall objectives were met.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2024

Methods for ultraviolet excitation microscopy of biological surfaces

Microscopy with Ultraviolet Surface Excitation (MUSE) for use in the classroom to enhance life sciences education and curricula, or for other applications, including without limtiation the operating room, other medical environments, research environments, and low resource environments. MUSE's suitability is based on multiple key factors including its simplicity of use, the incorporation of inexpensive hardware including LED illumination, and very basic tissue preparation. The ultraviolet excitation acts as passive optical sectioning confining the generated fluorescence signal to only a few micrometers below the tissue surface thus eliminating the out of focus signals. This facilitates image capture of tissue microstructure and organization from specimens at the intact or sliced surface arising from varying fluorophore concentration within the different cellular compartments. Although just the tissue auto fluorescence maybe used, image quality is enhanced with brief application of nontoxic fluorescent dyes to selectively highlight cellular compartments. Sample preparation is safe, efficient and familiar to students with basic chemistry or biology lab experience. Mixed-dye powders may be used to simplify translation of this method for educational, medical, research, low resource, and other settings.

Demos, Stavros G.↗
NASA NTRS1984

Evaluation of Landsat-4 Thematic Mapper and multispectral scanner data quality

Landsat-4 image data quality was evaluated for test sites in Iowa and Illinois. Radiometric and geometric quality was tested and an applications evaluation was carried out using a cooling-pond thermal-mapping example. Geometric quality was found to be generally very good. Small errors were found in registration of the middle IR bands of the TM and the thermal IR band was found to be misregistered by one 120-meter pixel. Radiometric quality of the TM is excellent with only minor striping effects.

Bartolucci, L. A.↗
DOE OSTI2020

Real-time biomass feedstock particle quality detection using image analysis and machine vision

Abstract A common and costly challenge in the nascent biorefinery industry is the consistent handling and conveyance of biomass feedstock materials, which can vary widely in their chemical, physical, and mechanical properties. Solutions to cope with varying feedstock qualities will be required, including advanced process controls to adjust equipment and reject feedstocks that do not meet a quality standard. In this work, we present and evaluate methods to autonomously assess corn stover feedstock quality in real time and provide data to process controls with low-cost camera hardware. We explore the use of neural networks to classify feedstocks based on actual processing behavior and pixel matrix feature parameterization to further assess particle attributes that may explain the variable processing behavior. We used the pretrained ResNet neural network coupled with a gated recurrent unit (GRU) time-series classifier trained on our image data, resulting in binary classification of feedstock anomalies with favorable performance. The textural aspects of the image data were statistically analyzed to determine if the textural features were predictive of operational disruptions. The significant textural features were angular second moment, prominence, mean height of surface profile, mean resultant vector, shade, skewness, variation of the polar facet orientation, and direction of azimuthal facets. Expansion of these models is recommended across a wider variety of labeled feedstock images of different qualities and species to develop a more robust tool that may be deployed using low-cost cameras within biorefineries.

09 BIOMASS FUELS↗
NASA NTRS2008

Second Harmonic Imaging improves Echocardiograph Quality on board the International Space Station

Ultrasound (US) capabilities have been part of the Human Research Facility (HRF) on board the International Space Station (ISS) since 2001. The US equipment on board the ISS includes a first-generation Tissue Harmonic Imaging (THI) option. Harmonic imaging (HI) is the second harmonic response of the tissue to the ultrasound beam and produces robust tissue detail and signal. Since this is a first-generation THI, there are inherent limitations in tissue penetration. As a breakthrough technology, HI extensively advanced the field of ultrasound. In cardiac applications, it drastically improves endocardial border detection and has become a common imaging modality. U.S. images were captured and stored as JPEG stills from the ISS video downlink. US images with and without harmonic imaging option were randomized and provided to volunteers without medical education or US skills for identification of endocardial border. The results were processed and analyzed using applicable statistical calculations. The measurements in US images using HI improved measurement consistency and reproducibility among observers when compared to fundamental imaging. HI has been embraced by the imaging community at large as it improves the quality and data validity of US studies, especially in difficult-to-image cases. Even with the limitations of the first generation THI, HI improved the quality and measurability of many of the downlinked images from the ISS and should be an option utilized with cardiac imaging on board the ISS in all future space missions.

Garcia, Kathleen↗
DOE OSTI2025

Location generalizability of image-based air quality models

This paper is to be submitted at the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) Computer Vision for Earth Observation workshop. The full paper abstract is below: The ability to rapidly quantify atmospheric pollutants is important both for global emissions monitoring and for mitigating the adverse effects that follow a hazardous chemical release. In the aftermath of a chemical release, imagery is often the only available resource to assess local conditions. Recent work has demonstrated initial success in predicting particulate matter pollution from imagery; however, these results are tied to a specific site and do not generalize to new geographic locations. In this work, we seek to understand how easily deep learning models generalize to new locations in the context of image-based air quality assessments, targeting two distinct tasks: (1) broad measures of particulate matter pollution, and (2) the mass of a given chemical released in hazardous plumes. For the latter, we focus on sulfur dioxide, a toxic aerosol and a major component of particulate matter pollution caused by industrial fossil fuel consumption. To develop a model that operates in the widest possible range of environments, we test different training strategies, including the use of new geolocation foundation models. The best performing models achieve >80% accuracy when evaluating unseen imagery at previously seen sites, but we find significant drops in performance when evaluating imagery from unseen sites, at best 65%. Additionally, we present the public release of the National Parks Air Quality Index Dataset, a new medium-sized dataset that pairs imagery with sensor-based air quality measurements at 15 different national parks.

Byler, Eleanor B. [BATTELLE (PACIFIC NW LAB)]↗
DOE OSTI2024

Uncertainty quantification and propagation in lithium-ion battery electrodes using bayesian convolutional neural networks

The complex nature of manufacturing processes stipulates electrodes to possess high variability with increased heterogeneity during production. X-ray computed tomography imaging has proved to be critical in visualizing the complicated stochastic particle distribution of as-manufactured electrodes in lithium-ion batteries. However, accurate prediction of their electrochemical performance necessitates precise evaluation of kinetic and transport properties from real electrodes. Image segmentation that characterizes voxels to particle/pore phase is often meticulous and fraught with subjectivity owing to a myriad of unconstrained choices and filter algorithms. Here we utilize a Bayesian convolutional neural network to tackle segmentation subjectivity and quantify its pertinent uncertainties. Otsu inter-variance and Blind/Referenceless Imaging Spatial Quality Evaluator are used to assess the relative image quality of grayscale tomograms, thus evaluating the uncertainty in the derived microstructural attributes. We analyze how image uncertainty is correlated with the uncertainties and magnitude of kinetic and transport properties of an electrode, further identifying pathways of uncertainty propagation within microstructural attributes. The coupled effect of spatial heterogeneity and microstructural anisotropy on the uncertainty quantification of transport parameters is also understood. This work demonstrates a novel methodology to extract microstructural descriptors from real electrode images through quantification of associated uncertainties and discerning the relative strength of their propagation, thus facilitating feedback to manufacturing processes from accurate image based electrochemical simulations.

25 ENERGY STORAGE↗
NASA NTRS1975

Physical correction filter for improving the optical quality of an image

A family of physical correction filters is described. Each filter is designed to correct image content of a photographed scene of limited resolution and includes a first filter element with a pinhole through which light passes to a differential amplifier. A second filter element through which light passes through one or more openings, whose geometric configuration is a function of the cause of the resolution loss included. The light, passing through the second filter element, is also supplied to the differential amplifier whose output is used to activate an optical display or recorder to reproduce a photograph or display of the scene in the original photograph or display of the scene in the original photograph with resolution which is significantly greater than that characterizing the original photograph.

Lee, S. Y.↗
NASA NTRS2013

On-Orbit Lunar Modulation Transfer Function Measurements for the Moderate Resolution Imaging Spectroradiometer

Spatial quality of an imaging sensor can be estimated by evaluating its modulation transfer function (MTF) from many different sources such as a sharp edge, a pulse target, or bar patterns with different spatial frequencies. These well-defined targets are frequently used for prelaunch laboratory tests, providing very reliable and accurate MTF measurements. A laboratory-quality edge input source was included in the spatial-mode operation of the Spectroradiometric Calibration Assembly (SRCA), which is one of the onboard calibrators of the Moderate Resolution Imaging Spectroradiometer (MODIS). Since not all imaging satellites have such an instrument, SRCA MTF estimations can be used as a reference for an on-orbit lunar MTF algorithm and results. In this paper, the prelaunch spatial quality characterization process from the Integrated Alignment Collimator and SRCA is briefly discussed. Based on prelaunch MTF calibration using the SRCA, a lunar MTF algorithm is developed and applied to the lifetime on-orbit Terra and Aqua MODIS lunar collections. In each lunar collection, multiple scan-directionMoon-to-background transition profiles are aligned by the subpixel edge locations from a parametric Fermi function fit. Corresponding accumulated edge profiles are filtered and interpolated to obtain the edge spread function (ESF). The MTF is calculated by applying a Fourier transformation on the line spread function through a simple differentiation of the ESF. The lifetime lunar MTF results are analyzed and filtered by a relationship with the Sun-Earth-MODIS angle. Finally, the filtered lunarMTF values are compared to the SRCA MTF results. This comparison provides the level of accuracy for on-orbit MTF estimations validated through prelaunch SRCA measurements. The lunar MTF values had larger uncertainty than the SRCA MTF results; however, the ratio mean of lunarMTF fit and SRCA MTF values is within 2% in the 250- and 500-m bands. Based on the MTF measurement uncertainty range, the suggested lunar MTF algorithm can be applied to any on-orbit imaging sensor with lunar calibration capability.

Choi, Taeyong↗
NASA NTRS1994

Improved image decompression for reduced transform coding artifacts

The perceived quality of images reconstructed from low bit rate compression is severely degraded by the appearance of transform coding artifacts. This paper proposes a method for producing higher quality reconstructed images based on a stochastic model for the image data. Quantization (scalar or vector) partitions the transform coefficient space and maps all points in a partition cell to a representative reconstruction point, usually taken as the centroid of the cell. The proposed image estimation technique selects the reconstruction point within the quantization partition cell which results in a reconstructed image which best fits a non-Gaussian Markov random field (MRF) image model. This approach results in a convex constrained optimization problem which can be solved iteratively. At each iteration, the gradient projection method is used to update the estimate based on the image model. In the transform domain, the resulting coefficient reconstruction points are projected to the particular quantization partition cells defined by the compressed image. Experimental results will be shown for images compressed using scalar quantization of block DCT and using vector quantization of subband wavelet transform. The proposed image decompression provides a reconstructed image with reduced visibility of transform coding artifacts and superior perceived quality.

Orourke, Thomas P.↗
NASA NTRS1985

The earth's surface studied from space; Proceedings of Workshop II of the COSPAR 25th Plenary Meeting, Graz, Austria, June 25-July 7, 1984

Consideration is given to: Landsat image data quality studies; a preliminary evaluation of Landsat-4 Thematic Mapper (TM) data for mineral exploration; and the early evaluation of TM data for mapping forest, agricultural and soil resources. Among other topics discussed are: shortwave infrared detection of vegetation; SPOT image quality and post-launch assessment; an evaluation of SPOT HRV simulation data for Corps of Engineers applications; and the application potential of SPOT imagery for topographic mapping. Consideration is also given to: verification studies of MOS-1 sensors; multiple sensor geocoded data; and the utility of proposed sensors for coastal engineering studies.

Ungar, S. G.↗
NASA NTRS2016

Exploiting Measurement Uncertainty Estimation in Evaluation of GOES-R ABI Image Navigation Accuracy Using Image Registration Techniques

In evaluating GOES-R Advanced Baseline Imager (ABI) image navigation quality, upsampled sub-images of ABI images are translated against downsampled Landsat 8 images of localized, high contrast earth scenes to determine the translations in the East-West and North-South directions that provide maximum correlation. The native Landsat resolution is much finer than that of ABI, and Landsat navigation accuracy is much better than ABI required navigation accuracy and expected performance. Therefore, Landsat images are considered to provide ground truth for comparison with ABI images, and the translations of ABI sub-images that produce maximum correlation with Landsat localized images are interpreted as ABI navigation errors. The measured local navigation errors from registration of numerous sub-images with the Landsat images are averaged to provide a statistically reliable measurement of the overall navigation error of the ABI image. The dispersion of the local navigation errors is also of great interest, since ABI navigation requirements are specified as bounds on the 99.73rd percentile of the magnitudes of per pixel navigation errors. However, the measurement uncertainty inherent in the use of image registration techniques tends to broaden the dispersion in measured local navigation errors, masking the true navigation performance of the ABI system. We have devised a novel and simple method for estimating the magnitude of the measurement uncertainty in registration error for any pair of images of the same earth scene. We use these measurement uncertainty estimates to filter out the higher quality measurements of local navigation error for inclusion in statistics. In so doing, we substantially reduce the dispersion in measured local navigation errors, thereby better approximating the true navigation performance of the ABI system.

navigation performance↗
NASA NTRS1972

Land use management in Minnesota

The author has identified the following significant results. Preliminary analysis of bulk imagery suggests that the forty-acre data cell used in the Minnesota Land Management Information Systems (MLMIS) can be utilized in interpretation of ERTS-1 data. High quality bulk images of the Twin Cities metropolitan area suggest that detail in urban land use patterns is much greater than originally anticipated. This implies a greater work effort in this area than was planned. Furthermore, the forest classes of land use can also be usefully divided into subcategories. Preliminary analysis of one rather low quality image also indicates that subclasses of wetlands can be identified. Prospects are bright for improving the potential detail that ERTS-1 can contribute to MLMIS.

Sizer, J. E.↗
DOE OSTI2020

Effect of defocusing on the quality of quantum ghost images

The effect of defocusing due to the finite thickness of the crystal, in which parametric scattering occurs, on the spatial resolution of ghost images is considered. The necessary relationships are presented, and methods of levelling this distorting factor and improving the quality of ghost images are proposed. (paper)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗