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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.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

Image interpretation and prediction in microwave diversity imaging

The microwave image of a metallic object is interpreted from a point of view based on the understanding of the interconnection between the scattering mechanisms, the data acquisition system, and the image reconstruction algorithm. From this understanding it is possible to interpret and predict microwave images reconstructed from data collected over specified and angular windows. The connection between a special scattering mechanism, edge diffraction, and its reconstructed image is established. The microwave image of an edge is two bright points whose locations correspond to the end points of the edge if the normal aspect angle is not included in the angular windows; otherwise a line joining the two end points and representing the edge will appear in the image. Experimental images of a trihedral reflector constructed from data collected over different angular windows support this approach to image interpretation and prediction.

Li, Hsueh-Jyh↗
DOE OSTI2019

On the possibility of a significant improvement in the quality of a quantum ghost image by registering an additional image in the object channel

A modification of the classical scheme of the quantum ghost image formation is considered, in which an image of the object under study is formed and recorded in the object channel. This image is used together with the ghost image to construct an estimate of the transparency distribution of the object. It is shown that this technique reduces the image quality worsening associated with the non-unit quantum efficiency of the sensors, even when the quantum image obtained in the object channel is additionally distorted by noise due to photons that did not interact with the object. (image processing)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Mapping Benthic Habitat Conditions and Seafloor Deposits using Sediment Profile Imaging and a Semiautomated Image Processing System

Objectives/Scope: Sediment profile imaging (SPI) technology characterizes in situ physical, geochemical, and biological seafloor features. SPI was required by Mexico’s Agency for Safety, Energy, and Environment in 2017 for environmental baseline surveys (EBS) of oil lease blocks in the southern Gulf of Mexico. Because of its ability to provide information on benthic community health and the distribution of very thin (down to the centimeter scale) layers of deposited materials, SPI technology is highly effective for mapping drill cuttings or drilling muds released around wellheads during exploration or production and documenting their ecological impacts. SPI technology has not been widely used in the oil and gas industry for EBS or other monitoring activities. A primary objective of this work is to improve the transparency and consistency of the SPI data generation and data management process. Methods, Procedures, Process: The SPI camera works like an inverted periscope and obtains an undisturbed 21x15-cm cross-sectional image of the upper sediment column. The camera is internally powered and can be deployed rapidly from a standard winch in depths to 4,000 m. Many stations can be sampled in a single day by “pogo-sticking” across a survey area. Sediment grain size, penetration depth, surface boundary roughness, natural and anthropogenic depositional layers, depth of the oxidized surface sediment layer, maximum biogenic mixing depth, and infaunal successional stage can be directly measured at sea or immediately following the cruise. Final SPI data sets can be provided within a few weeks of the survey. Results, Observations, Conclusions: Details on the features measured in SPI images and the underlying interpretive paradigms are presented. To standardize the SPI data generation process, Integral Consulting Inc. has developed 1) a semiautomated image analysis platform, and 2) a SPI data-specific database architecture that allows both numerical and non-numerical metrics to be incorporated into a standard database structure. An integrated, software-based SPI analysis platform has been developed that imports image files and metadata and provides a graphical user interface. The software automatically stores the data, which can then be reviewed for quality assurance, plotted, statistically analyzed, and mapped or exported to other platforms (e.g., Esri ArcGIS©) for further evaluation. Image processing algorithms have been developed using a combination of open-source and commercially available software packages (e.g., MATLAB® and OpenCV) to automatically quantify key parameters. Novel/Additive Information: SPI technology’s underutilization in the oil and gas industry may be in part due to a lack of standardization in the measurement of basic features in SPI images. A primary objective of this work is to develop a streamlined, standardized, and transparent process for generating and managing SPI data.

02 PETROLEUM↗
NASA NTRS2016

Image Navigation and Registration Performance Assessment Tool Set for the GOES-R Advanced Baseline Imager and Geostationary Lightning Mapper

The GOES-R Flight Project has developed an Image Navigation and Registration (INR) Performance Assessment Tool Set (IPATS) for measuring Advanced Baseline Imager (ABI) and Geostationary Lightning Mapper (GLM) INR performance metrics in the post-launch period for performance evaluation and long term monitoring. For ABI, these metrics are the 3-sigma errors in navigation (NAV), channel-to-channel registration (CCR), frame-to-frame registration (FFR), swath-to-swath registration (SSR), and within frame registration (WIFR) for the Level 1B image products. For GLM, the single metric of interest is the 3-sigma error in the navigation of background images (GLM NAV) used by the system to navigate lightning strikes. 3-sigma errors are estimates of the 99.73rd percentile of the errors accumulated over a 24-hour data collection period. IPATS utilizes a modular algorithmic design to allow user selection of data processing sequences optimized for generation of each INR metric. This novel modular approach minimizes duplication of common processing elements, thereby maximizing code efficiency and speed. Fast processing is essential given the large number of sub-image registrations required to generate INR metrics for the many images produced over a 24-hour evaluation period. Another aspect of the IPATS design that vastly reduces execution time is the off-line propagation of Landsat based truth images to the fixed grid coordinates system for each of the three GOES-R satellite locations, operational East and West and initial checkout locations. This paper describes the algorithmic design and implementation of IPATS and provides preliminary test results.

Image Navigation↗
NASA NTRS2016

Image Navigation and Registration (INR) Performance Assessment Tool Set (IPATS) for the GOES-R Advanced Baseline Imager and Geostationary Lightning Mapper

The GOES-R Flight Project has developed an Image Navigation and Registration (INR) Performance Assessment Tool Set (IPATS) for measuring Advanced Baseline Imager (ABI) and Geostationary Lightning Mapper (GLM) INR performance metrics in the post-launch period for performance evaluation and long term monitoring. For ABI, these metrics are the 3-sigma errors in navigation (NAV), channel-to-channel registration (CCR), frame-to-frame registration (FFR), swath-to-swath registration (SSR), and within frame registration (WIFR) for the Level 1B image products. For GLM, the single metric of interest is the 3-sigma error in the navigation of background images (GLM NAV) used by the system to navigate lightning strikes. 3-sigma errors are estimates of the 99.73rd percentile of the errors accumulated over a 24 hour data collection period. IPATS utilizes a modular algorithmic design to allow user selection of data processing sequences optimized for generation of each INR metric. This novel modular approach minimizes duplication of common processing elements, thereby maximizing code efficiency and speed. Fast processing is essential given the large number of sub-image registrations required to generate INR metrics for the many images produced over a 24 hour evaluation period. Another aspect of the IPATS design that vastly reduces execution time is the off-line propagation of Landsat based truth images to the fixed grid coordinates system for each of the three GOES-R satellite locations, operational East and West and initial checkout locations. This paper describes the algorithmic design and implementation of IPATS and provides preliminary test results.

Image Registration↗
DOE OSTI2019

Fusion Imaging to Guide Thoracic Endovascular Aortic Repair (TEVAR): A Randomized Comparison of Two Methods, 2D/3D Versus 3D/3D Image Fusion

Purpose: To compare the accuracy of two-dimensional (2D) versus three-dimensional (3D) image fusion for thoracic endovascular aortic repair (TEVAR) image guidance. Materials and Methods: Between December 2016 and March 2018, all eligible patients who underwent TEVAR were prospectively included in a single-center study. Image fusion methods (2D/3D or 3D/3D) were randomly assigned to guide each TEVAR and compared in terms of accuracy, dose area product (DAP), volume of contrast medium injected, fluoroscopy time and procedure time. Results: Thirty-two patients were prospectively included; 18 underwent 2D/3D and 14 underwent 3D/3D TEVAR. The 3D/3D method allowed more accurate positioning of the aortic mask on top of the fluoroscopic images (proximal landing zone error vector: 1.7 ± 3.3 mm) than was achieved by the 2D/3D method (6.1 ± 6.1 mm; p = 0.03). The 3D/3D image fusion method was associated with significantly lower DAP than the 2D/3D method (50.5 ± 30.1 Gy cm{sup 2} for 3D/3D vs. 99.5 ± 79.1 Gy cm{sup 2} for 2D/3D; p = 0.03). The volume of contrast medium injected was significantly lower for the 3D/3D method than for the 2D/3D method (50.6 ± 22.9 ml vs. 98.4 ± 47.9 ml; p = 0.002). Conclusion: Higher image fusion accuracy and lower contrast volume and irradiation dose were observed for 3D/3D image fusion than for 2D/3D during TEVAR. Level of Evidence: II, Randomized trial.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2024

Gamma-ray imaging of Np-237 metal using an organic glass imager

Neutron and gamma-ray imaging systems are deployed within the field of nuclear safeguards for the detection and localization of special nuclear materials and other materials of interest. 237 Np is one of these materials of interest due its presence in spent nuclear fuel and potential for use in nuclear weapons when purified. Here, for the first time, a 6 kg neptunium sphere (98.8 wt% 237 Np) was measured using a dual-particle imager, from the University of Michigan, consisting of organic glass and inorganic scintillators. The novel composition of organic glass scintillator was recently developed at Sandia National Labs and has been used in particle imaging systems due to its time resolution and particle discrimination capabilities. Gamma-ray energy spectra from single and coincident events were extracted and the sequencing of Compton scatter and photoelectric absorption gamma-ray events was used to generate images using simple backprojection. The emissions of interest in this work are the 312 keV and 416 keV gamma rays from 233 Pa, a daughter isotope from the neptunium decay series. The results of this work show that there is close agreement between the true source location in angular space and the converged location from the gamma ray images created using the system. The gamma spectroscopy from single and coincident events also identified the characteristic emission from the daughter isotope and could be used to assist with the identification of 237 Np. Furthermore, successful localization of the source with 5 s of data demonstrates the practical application of the imaging system for imaging and detection of material in weapons-useable quantities.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Imaging from Macro to Nanoscale: Multimodal Advances in Chemical and Biomedical Imaging

Imaging increasingly serves as a multiscale framework for linking molecular mechanisms to cellular behavior, tissue architecture, and organ phenotypes in biology and unraveling fundamental processes in chemistry, physics and materials science. This Perspective highlights recent advances in chemical and biomedical imaging across macro-, micro-, and nanoscales, using representative examples published in Chemical and Biomedical Imaging (CBMI). At the macroscale, we discuss chemically selective MRI, including endogenous and exogenous CEST strategies, together with photoacoustic imaging as a hybrid modality with functional and chemical contrast. At the microscale, we consider fluorescence, label-free optical and vibrational imaging, and selected X-ray approaches that expand sensitivity, specificity, and temporal resolution in biological and materials systems. At the nanoscale, we highlight super-resolution fluorescence microscopy, single-molecule methods, tip-enhanced Raman spectroscopy, and correlative imaging strategies that resolve local heterogeneity and molecular organization. Across scales, a common theme emerges that advances in probes, contrast mechanisms, instrumentation, and sample handling are enabling chemically informed imaging that connects molecular specificity with biological context.

multiscale imaging↗
DOE OSTI2017

A Heuristic Approach to Remove the Background Intensity on White-light Solar Images. I. STEREO /HI-1 Heliospheric Images

White-light coronal and heliospheric imagers observe scattering of photospheric light from both dust particles (the F-Corona) and free electrons in the corona (the K-corona). The separation of the two coronae is thus vitally important to reveal the faint K-coronal structures (e.g., streamers, co-rotating interaction regions, coronal mass ejections, etc.). However, the separation of the two coronae is very difficult, so we are content in defining a background corona that contains the F- and as little K- as possible. For both the LASCO-C2 and LASCO-C3 coronagraphs aboard the Solar and Heliospheric Observatory ( SOHO ) and the white-light imagers of the SECCHI suite aboard the Solar Terrestrial Relationships Observatory ( STEREO ), a time-dependent model of the background corona is generated from about a month of similar images. The creation of such models is possible because the missions carrying these instruments are orbiting the Sun at about 1 au. However, the orbit profiles for the upcoming Solar Orbiter and Solar Probe Plus missions are very different. These missions will have elliptic orbits with a rapidly changing radial distance, hence invalidating the techniques in use for the SOHO /LASCO and STEREO /SECCHI instruments. We have been investigating techniques to generate background models out of just single images that could be used for the Solar Orbiter Heliospheric Imager and the Wide-field Imager for the Solar Probe Plus packages on board the respective spacecraft. In this paper, we introduce a state-of-the-art, heuristic technique to create the background intensity models of STEREO /HI-1 data based solely on individual images, report on new results derived from its application, and discuss its relevance to instrumental and operational issues.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Full-Depth Coadds of the WISE and First-Year NEOWISE-Reactivation Images

The Near Earth Object Wide-field Infrared Survey Explorer (NEOWISE) Reactivation mission released data from its first full year of observations in 2015. This data set includes ~2.5 million exposures in each of W1 and W2, effectively doubling the amount of WISE imaging available at 3.4 μm and 4.6 μm relative to the AllWISE release. In this paper, we have created the first ever full-sky set of coadds combining all publicly available W1 and W2 exposures from both the AllWISE and NEOWISE-Reactivation (NEOWISER) mission phases. We employ an adaptation of the unWISE image coaddition framework, which preserves the native WISE angular resolution and is optimized for forced photometry. By incorporating two additional scans of the entire sky, we not only improve the W1/W2 depths, but also largely eliminate time-dependent artifacts such as off-axis scattered moonlight. We anticipate that our new coadds will have a broad range of applications, including target selection for upcoming spectroscopic cosmology surveys, identification of distant/massive galaxy clusters, and discovery of high-redshift quasars. In particular, our full-depth AllWISE+NEOWISER coadds will be an important input for the Dark Energy Spectroscopic Instrument selection of luminous red galaxy and quasar targets. Our full-depth W1/W2 coadds are already in use within the DECam Legacy Survey (DECaLS) and Mayall z-band Legacy Survey (MzLS) reduction pipelines. Finally, much more work still remains in order to fully leverage NEOWISER imaging for astrophysical applications beyond the solar system.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

What can we learn from in-soil imaging of a live plant: X-ray Computed Tomography and 3D numerical simulation of root-soil system

Plant roots play a critical role in plant-soil-microbe interactions that occur in the rhizosphere, as well as processes with important implications to farming, forest management and climate change. X-ray computed tomography (XCT) has been proven to be an effective tool for non-invasive root imaging and analysis. A combination of XCT, open-source software, and our own code was used to noninvasively image a prairie dropseed (Sporobolus heterolepis) specimen, segment the root data to obtain a 3D image of the root structure at 31µm resolution, and extract quantitative information (root volume and surface area) from the 3D data, respectively. Based on the mesh generated from the root structure, computational fluid dynamics (CFD) simulations were applied to numerically investigate the root-soil-groundwater system. The plant root conductivity, soil hydraulic conductivity and transpiration rate were shown to control the groundwater distribution. The flow variability and soil water distributions under different scenarios were investigated. Parameterizations were evaluated to show their impacts on the average conductivity. The pore-scale modeling approach provides realistic simulations of rhizosphere flow processes and provides useful information that can be linked to upscaled models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

FIRM image analysis: A machine learning workflow for quantifying extracellular matrix components from electron microscopy images

The extracellular matrix (ECM) is a complex network of biomolecules that plays an integral role in the structure, processes, and signaling mechanisms of cells and tissues. Identifying and quantifying changes in these matrix components provides insight into the mechanisms behind specific tissue remodeling processes; however, quantifying these changes is challenging due to difficult imaging conditions, complexity of the ECM, and the subtlety of these changes. Current imaging techniques allow us to visualize these critical remodeling events and developments in image analysis have employed a combination of analysis software and machine learning techniques to improve the efficiency and accuracy with which features are measured. Although image analysis has seen much improvement in recent years, there has been no technique developed to address ambiguity in feature edges in electron microscopy images. Presented here is a new machine learning-based workflow for the analysis of microscopy images named FIRM (Feature Identification from Raw Microscopy) that uses a random forest classifier to identify ECM features of interest and generate binary segmentation masks for quantification with ImageJ-FIJI. FIRM performed with an F1 score of 0.794 and greater than 80% accuracy for number and size of features detected. FIRM had similar deviation from the ground truth in the number of identified fibrils, fibril size, and size distributions when compared to human analyses. The results suggest that FIRM performs as well as manual analysis and requires a fraction of the time. This analysis technique is more efficient, eliminates user bias, and can be easily optimized to identify a variety of features, making it useful for any discipline requiring image analysis.

Science & Technology - Other Topics↗
NASA NTRS1989

High compression image and image sequence coding

The digital representation of an image requires a very large number of bits. This number is even larger for an image sequence. The goal of image coding is to reduce this number, as much as possible, and reconstruct a faithful duplicate of the original picture or image sequence. Early efforts in image coding, solely guided by information theory, led to a plethora of methods. The compression ratio reached a plateau around 10:1 a couple of years ago. Recent progress in the study of the brain mechanism of vision and scene analysis has opened new vistas in picture coding. Directional sensitivity of the neurones in the visual pathway combined with the separate processing of contours and textures has led to a new class of coding methods capable of achieving compression ratios as high as 100:1 for images and around 300:1 for image sequences. Recent progress on some of the main avenues of object-based methods is presented. These second generation techniques make use of contour-texture modeling, new results in neurophysiology and psychophysics and scene analysis.

Kunt, Murat↗
NASA NTRS1992

Astro-1 ultraviolet imaging of the 30 Doradus and SN 1987A fields with the Ultraviolet Imaging Telescope

A preliminary analysis of Ultraviolet Imaging Telescope (UIT) images in the 30 Doradus region is reported. Photometry was obtained for the 30 Doradus cluster and its UV-bright core, R136, in various UIT bandpasses. It is found that about 14 percent of the total FUV light and about 16 percent of the total near-UV light of the 3-arcmin diameter 30 Doradus cluster originates from the region within 5 arcsec of R136. The UV magnitudes and colors of R136 and other known O and Wolf-Rayet WN stars in the same field were measured. The UIT data, combined with published observations at longer wavelengths, indicate that R136a1, the brightest component of R136, is not a supermassive stars. A qualitative comparison between the UIT images, Einstein X-ray data, IRAS HiRes images, and ground-based CCD images in forbidden O III 5007 A, H-alpha, B, R, U, and Stromgren u is performed. The extended diffuse UV feature detected in the UIT images is correlated with the IR structure seen in the IRAS 60-micron HiRes image, which suggests the existence of large amounts of widely distributed dust in this region.

Cheng, Kwang-Ping↗
NASA NTRS1992

Instrument requirements for imaging the magnetosphere in extreme-ultraviolet and energetic neutral atoms derived from computer-simulated images

Scientific requirements for He(+)(304 A) and energetic neutral atom (ENA) magnetospheric imaging, as well as the derived instrumental requirements are presented. Both ENA imaging of the hot plasma and EUV imaging of the cold plasma are highlighted. The question of the accuracy with which physically significant parameters can be extracted from actual images using computerized algorithms is addressed. An example of an ENA image analyzed by means of the Powell minimization algorithm is given. Automated unfolding of global magnetospheric images is also discussed. A Mercator projection of a model INA image is shown.

Roelof, Edmond C.↗
NASA NTRS1995

Combining image-processing and image compression schemes

An investigation into the combining of image-processing schemes, specifically an image enhancement scheme, with existing compression schemes is discussed. Results are presented on the pyramid coding scheme, the subband coding scheme, and progressive transmission. Encouraging results are demonstrated for the combination of image enhancement and pyramid image coding schemes, especially at low bit rates. Adding the enhancement scheme to progressive image transmission allows enhanced visual perception at low resolutions. In addition, further progressing of the transmitted images, such as edge detection schemes, can gain from the added image resolution via the enhancement.

Greenspan, H.↗
NASA NTRS1996

Single Transducer Ultrasonic Imaging Method that Eliminates the Effect of Plate Thickness Variation in the Image

This article describes a single transducer ultrasonic imaging method that eliminates the effect of plate thickness variation in the image. The method thus isolates ultrasonic variations due to material microstructure. The use of this method can result in significant cost savings because the ultrasonic image can be interpreted correctly without the need for machining to achieve precise thickness uniformity during nondestructive evaluations of material development. The method is based on measurement of ultrasonic velocity. Images obtained using the thickness-independent methodology are compared with conventional velocity and c-scan echo peak amplitude images for monolithic ceramic (silicon nitride), metal matrix composite and polymer matrix composite materials. It was found that the thickness-independent ultrasonic images reveal and quantify correctly areas of global microstructural (pore and fiber volume fraction) variation due to the elimination of thickness effects. The thickness-independent ultrasonic imaging method described in this article is currently being commercialized under a cooperative agreement between NASA Lewis Research Center and Sonix, Inc.

Roth, Don J.↗