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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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At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

Development of image processing techniques for applications in flow visualization and analysis

A comparison between two flow visualization studies of an axi-symmetric circular jet issuing into still fluid, using two different experimental techniques, is described. In the first case laser induced fluorescence is used to visualize the flow structure, whilst smoke is utilized in the second. Quantitative information was obtained from these visualized flow regimes using two different digital imaging systems. Results are presented of the rate at which the jet expands in the downstream direction and these compare favorably with the more established data.

Disimile, Peter J.↗
NASA NTRS1985

Computer image processing of up-draft flow motion and severe storm formation observed from satellite

Special rapid-scan satellite visible and infrared observations have been used to study the life cycle of the clouds from the initiation of updraft flow motion in the atmosphere, the condensation of humid air, the formation of clouds, the development of towering cumulus, the penetration of the tropopause, the collapsing of an overshooting turret, and the dissipation of cloud. The infrared image provides an indication of the equivalent blackbody temperature of the observed cloud tops. By referencing the temperature, height and humidity profiles from rawinsonde observations as the background meteorological data for the instability of the air mass to the satellite infrared data sets at different time periods, the development of convective clouds can be studied in detail.

Hung, R. J.↗
NASA NTRS2002

Labview Implementation of Image Processing and Phasing Control for the SIBOA Segmented Mirror Testbed

NASA is preparing to launch the Next Generation Space Telescope (NGST). This telescope will be larger than the Hubble Space Telescope, be launched on an Atlas missile rather than the Space Shuttle, have a segmented primary mirror, and be placed in a higher orbit. All these differences pose significant challenges.' This effort addresses the challenge of implementing an algorithm for aligning the segments of the primary mirror during the initial deployment that was designed by Philip Olivier and members of SOMTC (Space Optics Manufacturing Technology Center). The implementation was to be performed on the SIBOA (Systematic Image Based Optical Alignment) test bed. Unfortunately, hardware/software aspect concerning SIBOA and an extended time period for algorithm development prevented testing before the end of the study period. Properties of the digital camera were studied and understood, resulting in the current ability of selecting optimal settings regarding saturation. The study was successful in manually capturing several images of two stacked segments with various relative phases. These images can be used to calibrate the algorithm for future implementation. Currently the system is ready for testing.

James D. Partridge↗
NASA NTRS1975

Photographic image enhancement and processing

Image processing techniques (computer and photographic) are described which are used within the JSC Photographic Technology Division. Two purely photographic techniques used for specific subject isolation are discussed in detail. Sample imagery is included.

Lockwood, H. E.↗
NASA NTRS1979

Azimuth correlator for real-time synthetic aperture radar image processing

An azimuth correlator architecture is defined wherein a number of serial range-line buffer memories are cascaded such that the output stages of all buffer memories together form a complete and unique range bin in the azimuthal dimension at any given time. A range bin is automatically read out of the last stages of the registers in parallel on a range line sample-by-sample basis for subsequent range migration correction and correlation. Range migration correction is performed on the range bins by effectively varying the length of a delay register at the output of each range-line buffer memory. The corrected range bin output from the delay registers is then correlated with a Doppler reference function to form an image element on a real-time basis.

Arens, W. E.↗
NASA NTRSDate not supplied

Identifying Indicators of Harmful Algal Blooms in Coastal Atacama Using Satellite Image Processing Techniques to Improve Industry and Authority Response

Over the past decade, Chile has experienced a significant rise in both the frequency and intensity of coastal Harmful Algal Blooms (HABs). These bloom events are a growing concern for the Atacama Region especially, with potential impacts on human health, aquaculture, and the environment. HABs are caused by an excess proliferation of microalgae, with certain algae species commonly found in Chilean HABs capable of producing toxins which can poison fish, toxify shellfish, and cause illness or death when ingested by humans. Collaborating with the Ministry of Health of Chile, Centro de Información de Recursos Naturales, the University of Atacama, and the Embassy of Chile’s Agricultural Office, this study identifies potential indicators of HABs in the Coastal Atacama Region using NASA Earth observations. Satellite imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument onboard NASA’s Aqua satellite was used for the identification of chlorophyll-a which provides direct estimates of the algae pigment’s concentration in water bodies. In addition, the spatiotemporal patterns of several other parameters were examined to identify correlations with occurrences of HABs, including sea surface temperature and normalized fluorescence line height using Aqua MODIS, Normalized Difference Turbidity Index (NDTI) using Landsat 8, and ocean wind speed measurements from the NOAA Joint Polar Satellite System. Analysis of these patterns revealed hotspots of high chlorophyll-a concentrations from the years 2014 to 2022, the most major of which occurring in the coastal zones of Chañaral, Bahía Inglesa, and Huasco. Also, through the use of a similarity search conducted, the seasonal variation of these indicators was mapped to highlight areas with great likelihood of experiencing HABs in the future. The results can guide future efforts for in-situ water sampling, toxin analysis and assessment, and HAB monitoring and prevention.

Cody O'Ferrall↗
NASA NTRS1981

Application of digital image processing techniques and information systems to water quality monitoring of Lake Tahoe

The Tahoe basin occupies over 500 square miles of territory located in a graben straddling the boundary between California and Nevada. Lake Tahoe contains 126 million acre-feet of water. Since the 1950's the basin has experienced an ever increasing demand for land development at the expense of the natural watershed. Discharge of sediment to the lake has greatly increased owing to accelerated human interference, and alterations to the natural drainage patterns are evident in some areas. In connection with an investigation of the utility of a comprehensive system that takes into account the causes as well as the effects of lake eutrophication, it has been attempted to construct an integrated and workable data base, comprised of currently available data sources for the Lake Tahoe region. Attention is given to the image based information system (IBIS), the construction of the Lake Tahoe basin data base, and the application of the IBIS concept to the Lake Tahoe basin.

Smith, A. Y.↗
DOE OSTI2020

Path-Based Dictionary Augmentation: A Framework for Improving $k$ -Sparse Image Processing

In this study, we have previously shown that augmenting orthogonal matching pursuit (OMP) with an additional step in the identification stage of each pursuit iteration yields improved $k$ -sparse reconstruction and denoising performance relative to baseline OMP. At each iteration a “path” or geodesic, is generated between the two dictionary atoms that are most correlated with the residual and from this path a new atom that has a greater correlation to the residual than either of the two bracketing atoms is selected. Here, we provide new computational results illustrating improvements in sparse coding and denoising on canonical datasets using both learned and structured dictionaries. The two methods of constructing a path are investigated for each dictionary type: the Euclidean geodesic formed by a linear combination of the two atoms and the 2-Wasserstein geodesic corresponding to the optimal transport map between the atoms. We prove here the existence of a higher-correlation atom in the Euclidean case under assumptions on the two bracketing atoms and introduce algorithmic modifications to improve the likelihood that the bracketing atoms meet those conditions. Although, we demonstrate our augmentation on OMP alone, in general it may be applied to any reconstruction algorithm that relies on the selection and sorting of high-similarity atoms during an analysis or identification phase.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Hydrodynamic Characterization of a Shallow Rectangular Spouted Bed Using Bed Pressure Signals and Image Processing Methods

To support the design of spouted bed reactors, experiments are performed in a rectangular spouted bed to measure the peak pressure drop (Δ P max ) and the internal and external spouting velocities ( U is and U es ). Four particle types spanning under Geldart D and B are used. U is and U es are measured from bed pressure drop and expansion ratio profiles, respectively, with the U es / U is ratio of each particle type obtained. Additionally, correlations predicting the Δ P max of Geldart D and B particles are developed by reviewing published correlations and investigating the nozzle effect. Good prediction is achieved with a slope of 0.997 and an adjusted R 2 of 0.998 in a 95% confidence interval. U es is predicted through correlations developed by adding effects of d p / D i and H 0 in the Mathur–Gishler equation. The calculated U es agrees well with the experimental data, achieving a slope of 0.998 and an adjusted R 2 of 0.998 in a 95% confidence interval.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Process Image Analysis using Big Data, Machine Learning, and Computer Vision

The development of algorithms for machine learning and data analysis for the 3013 MIS corrosion surveillance program is a collaborative effort by SRNL, USC and GT. For corrosion detection, LCM image data is extracted from large binary files, with software written to convert the data to physical attributes (i.e. height, color and grayscale values; all as functions of a location in a plane projection). The user interface for the software permits selective downloading of binary data and interrogation of attributes. User input thresholds are used to flag attributes of interest. Machine learning algorithms, developed for this application, are used to determine whether the features are the result of corrosion. To address the fundamental mechanisms of corrosion, machine learning algorithms are being developed to derive interatomic potential force-fields from ab-initio DFT calculations. The goal is to apply molecular modeling on a large enough scale to guide the design of resistant materials.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1969

VICAR-DIGITAL image processing system

Computer program corrects various photometic, geometric and frequency response distortions in pictures. The program converts pictures to a number of elements, with each elements optical density quantized to a numerical value. The translated picture is recorded on magnetic tape in digital form for subsequent processing and enhancement by computer.

Billingsley, F.↗