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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Thermographic Imaging of the Space Shuttle During Re-Entry Using a Near Infrared Sensor

High resolution calibrated near infrared (NIR) imagery of the Space Shuttle Orbiter was obtained during hypervelocity atmospheric re-entry of the STS-119, STS-125, STS-128, STS-131, STS-132, STS-133, and STS-134 missions. This data has provided information on the distribution of surface temperature and the state of the airflow over the windward surface of the Orbiter during descent. The thermal imagery complemented data collected with onboard surface thermocouple instrumentation. The spatially resolved global thermal measurements made during the Orbiter s hypersonic re-entry will provide critical flight data for reducing the uncertainty associated with present day ground-to-flight extrapolation techniques and current state-of-the-art empirical boundary-layer transition or turbulent heating prediction methods. Laminar and turbulent flight data is critical for the validation of physics-based, semi-empirical boundary-layer transition prediction methods as well as stimulating the validation of laminar numerical chemistry models and the development of turbulence models supporting NASA s next-generation spacecraft. In this paper we provide details of the NIR imaging system used on both air and land-based imaging assets. The paper will discuss calibrations performed on the NIR imaging systems that permitted conversion of captured radiant intensity (counts) to temperature values. Image processing techniques are presented to analyze the NIR data for vignetting distortion, best resolution, and image sharpness. Keywords: HYTHIRM, Space Shuttle thermography, hypersonic imaging, near infrared imaging, histogram analysis, singular value decomposition, eigenvalue image sharpness

Zalameda, Joseph N.↗
NASA NTRS1992

Multiresolution image gathering and restoration

In this paper we integrate multiresolution decomposition with image gathering and restoration. This integration leads to a Wiener-matrix filter that accounts for the aliasing, blurring, and noise in image gathering, together with the digital filtering and decimation in signal decomposition. Moreover, as implemented here, the Wiener-matrix filter completely suppresses the blurring and raster effects of the image-display device. We demonstrate that this filter can significantly improve the fidelity and visual quality produced by conventional image reconstruction. The extent of this improvement, in turn, depends on the design of the image-gathering device.

Fales, Carl L.↗
DOE OSTI2021

Distributed Training for High Resolution Images: A Domain and Spatial Decomposition Approach

In this work we developed two Pytorch libraries using the PyTorch RPC interface for distributed deep learning approaches on high resolution images. The spatial decomposition library allows for distributedtraining on very large images, which otherwise won’t be possible on a single GPU. The domain parallelism library allows for distributed training across multiple domain unlabeled data, by leveraging the domain separation architecture. Both of those libraries were tested on the Summit supercomputer at a moderate scale, and we are releasing the code for both of them.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Distributed Training for High Resolution Images: A Domain and Spatial Decomposition Approach

In this work we developed two Pytorch libraries using the PyTorch RPC interface for distributed deep learning approaches on high resolution images. The spatial decomposition library allows for distributed training on very large images, which otherwise wouldn’t be possible on a single GPU. The domain parallelism library allows for distributed training across multiple domain unlabeled data, by leveraging the domain separation architecture. Both of those libraries where tested on the Summit supercomputer at Oak Ridge National Laboratory at a moderate scale.

Tsaris, Aristeidis (aris)↗
NASA NTRS2004

An Integrated Centroid Finding and Particle Overlap Decomposition Algorithm for Stereo Imaging Velocimetry

An integrated algorithm for decomposing overlapping particle images (multi-particle objects) along with determining each object s constituent particle centroid(s) has been developed using image analysis techniques. The centroid finding algorithm uses a modified eight-direction search method for finding the perimeter of any enclosed object. The centroid is calculated using the intensity-weighted center of mass of the object. The overlap decomposition algorithm further analyzes the object data and breaks it down into its constituent particle centroid(s). This is accomplished with an artificial neural network, feature based technique and provides an efficient way of decomposing overlapping particles. Combining the centroid finding and overlap decomposition routines into a single algorithm allows us to accurately predict the error associated with finding the centroid(s) of particles in our experiments. This algorithm has been tested using real, simulated, and synthetic data and the results are presented and discussed.

McDowell, Mark↗
DOE OSTI2025

Physics-guided dual implicit neural representations for source separation

Significant challenges exist in efficient data analysis of most advanced experimental and observational techniques because the collected signals often include unwanted contributions, such as background and signal distortions, that can obscure the physically relevant information of interest. To address this, we have developed a self-supervised machine-learning approach for source separation using a dual implicit neural representation framework that jointly trains two neural networks: one for approximating distortions of the physical signal of interest and the other for learning the effective background contribution. Our method learns directly from the raw data by minimizing a reconstruction-based loss function without requiring labeled data or pre-defined dictionaries. We demonstrate the effectiveness of our framework by considering a challenging case study involving large-scale simulated, as well as experimental, momentum-energy-dependent inelastic neutron scattering data in a four-dimensional parameter space, characterized by heterogeneous background contributions and unknown distortions to the target signal. The method is found to successfully separate physically meaningful signals from a complex or structured background even when the signal characteristics vary across all four dimensions of the parameter space. An analytical approach that informs the choice of the regularization parameter is presented. Our method offers a versatile framework for addressing source separation problems across diverse domains, ranging from superimposed signals in astronomical measurements to structural features in biomedical image reconstructions.

47 OTHER INSTRUMENTATION↗
NASA NTRS1983

The geometric correction of Landsat-type imagery using perturbation techniques

A method for geometric correction data calculation is based on decomposition of image distortions into nominal distortions and perturbations, caused by deviations from the nominal spacecraft motion and sensor pointing. The maximal errors of the method are of the order of 5 m, and the average errors are less than 0.6 m (sigma).

Levine, I.↗
NASA NTRS1993

Compression through decomposition into browse and residual images

Economical archival and retrieval of image data is becoming increasingly important considering the unprecedented data volumes expected from the Earth Observing System (EOS) instruments. For cost effective browsing the image data (possibly from remote site), and retrieving the original image data from the data archive, we suggest an integrated image browse and data archive system employing incremental transmission. We produce our browse image data with the JPEG/DCT lossy compression approach. Image residual data is then obtained by taking the pixel by pixel differences between the original data and the browse image data. We then code the residual data with a form of variable length coding called diagonal coding. In our experiments, the JPEG/DCT is used at different quality factors (Q) to generate the browse and residual data. The algorithm has been tested on band 4 of two Thematic mapper (TM) data sets. The best overall compression ratios (of about 1.7) were obtained when a quality factor of Q=50 was used to produce browse data at a compression ratio of 10 to 11. At this quality factor the browse image data has virtually no visible distortions for the images tested.

Novik, Dmitry A.↗
DOE OSTI2021

Vector elastic deconvolution migration with dual wavefield decomposition

Here, we report elastic-wave imaging using multicomponent data can provide more useful subsurface information than acoustic-wave imaging, but it is usually algorithmically challenging. We have developed a vector elastic deconvolution migration method for high-resolution imaging of subsurface structures in isotropic and anisotropic elastic media. Our new method uses a vector deconvolution imaging condition based on dual wavefield decomposition, including an explicit directional wavefield separation using the Hilbert transform and a P/S vector wavefield decomposition using the low-rank decomposition method. Using three elastic models, we numerically determine that our new method produces notably higher resolution and more amplitude-balanced elastic images compared with a crosscorrelation-based vector elastic reverse time migration method.

58 GEOSCIENCES↗
NASA NTRS1993

Evaluation of C-band SAR data from SAREX 1992: Tapajos study site

As part of the SAREX'92 (South American Radar Experiment), the Tapajos study site, located in Para State, Brazil was imaged by the Canada Center for Remote Sensing (CCRS) Convair 580 SAR system using a C-band frequency in HH and VV polarization and 3 different imaging modes (nadir, narrow, and wide swath). A preliminary analysis of this dataset is presented. The wide swath C-band HH polarized image was enlarged to 1:100,000 in a photographic form for manual interpretation. This was compared with a vegetation map produced primarily from Landsat Thematic Mapper (TM) data and with single-band and color composite images derived from a decomposition analysis of TM data. The Synthetic Aperture Radar (SAR) image shows well the topography and drainage network defining the different geomorphological units, and canopy texture differences which appear to be related to the size and maturity of the forest canopy. Areas of recent clearing of the primary forest can also be identified on the SAR image. The SAR system appears to be a source of information for monitoring tropical forest which is complementary to the Landsat Thematic Mapper.

Shimabukuro, Yosio Edemir↗
NASA NTRS1987

AIS-2 spectra of California wetland vegetation

Spectral data gathered by Airborne Imaging Spectrometers-2 from wetlands were analyzed. Spectra representing stands of green Salicornia virginica, green Sesuvium verrucosum, senescing Distichlis spicata, a mixture of senescing Scirpus acutus and Scirpus californicus, senescing Scirpus paludosus, senescent S. paludosus, mowed senescent S. paludosus, and soil were isolated. No difference among narrowband spectral reflectance of the cover types was apparent between 0.8 to 1.6 micron. There were, however, broadband differences in brightness. These differences were sufficient to permit a fairly accurate decomposition of the image into its major cover type components using a procedure that assumes an additive linear mixture of surface spectra.

Gross, Michael F.↗
DOE OSTI2025

Precipitation of gadolinium from magnetic resonance imaging contrast agents may be the Brass tacks of toxicity

The formation of gadolinium-rich nanoparticles in multiple tissues from intravenous magnetic resonance imaging contrast agents may be the initial step in rare earth metallosis. The mechanism of gadolinium-induced diseases is poorly understood, as is how these characteristic nanoparticles are formed. Gadolinium deposition has been observed with all magnetic resonance imaging contrast agent brands. Aside from endogenous metals and acidic conditions, little attention has been paid to the role of the biological milieu in the degradation of magnetic resonance imaging contrast agents into nanoparticles. Herein, we describe the decomposition of the commercial magnetic resonance imaging contrast agents Omniscan and Dotarem in the presence of oxalic acid, a well-known endogenous compound. Omniscan dechelated rapidly and preluded measurement by the means available, while Dotarem underwent a two-step decomposition process. The decomposition of both magnetic resonance imaging contrast agents by oxalic acid formed gadolinium oxalate (Gd 2 [C 2 O 4 ] 3 , Gd 2 Ox 3 ). Furthermore, both observed steps of the Dotarem reaction involved the associative addition of oxalic acid. Adding protein (bovine serum albumin) increased the rate of dechelation. Displacement reactions could occur at lysosomal pH. Through these studies, we have demonstrated that magnetic resonance imaging contrast agents can be dissociated by endogenous molecules, thus illustrating a metric by which gadolinium-based contrast agents (GBCAs) might be destabilized in vivo.

Gadodiamide↗
DOE OSTI2023

Multiwavelength Bulge–Disk Decomposition for the Galaxy M81 (NGC 3031). I. Morphology

A panchromatic investigation of morphology for the early-type spiral galaxy M81 is presented in this paper. We perform bulge–disk decomposition in M81 images at a total of 20 wave bands from far-UV to near-IR (NIR) obtained with GALEX, Swift, Sloan Digital Sky Survey, WIYN, Two Micron All Sky Survey, Wide-field Infrared Survey Explorer, and Spitzer. Morphological parameters such as Sérsic index, effective radius, position angle, and axis ratio for the bulge and the disk are thus derived at all of the wave bands, which enables quantifying the morphological K -correction for M81 and makes it possible to reproduce images for the bulge and the disk in the galaxy at any wave band. The morphology as a function of wavelength appears as a variable-slope trend of the Sérsic index and the effective radius, in which the variations are steep at UV–optical and shallow at optical–NIR bands; the position angle and the axis ratio keep invariable at least at optical–NIR bands. It is worth noting that the Sérsic index for the bulge reaches ~4–5 at optical and NIR bands, but drops to ~1 at UV bands. This difference brings forward a caveat that a classical bulge is likely misidentified for a pseudobulge or no bulge at high redshifts where galaxies are observed through rest-frame UV channels with optical telescopes. The next work of this series is planned to study spatially resolved spectral energy distributions for the bulge and the disk, respectively, and thereby explore stellar population properties and star formation/quenching history for the galaxy composed of the subsystems.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1993

Dynamically reconfigurable optical morphological processor and its applications

An innovative optically implemented morphological processor is introduced. With the use of a large space-bandwidth-product Dammann grating and a high-speed shutter spatial light modulator, effective structuring element with large size and arbitrary shape can be constructed with dynamic reconfigurability. This reconfigurability is a major improvement over the conventional correlator-based morphological processor in which fixed holographic filters are used as structuring elements (Casasent and Botha, 1988). A novel two-dimensional thresholding photodetector array, capable of performing parallel thresholding and feedback, is utilized in this system and makes possible the implementation of many complex morphological operations requiring iterative feedbacks and full programmability. The optical architecture and the principle of operation are presented. Experimental demonstration of binary image morphological erosion, dilation, opening, and closing are also demonstrated. A technique for extending this technique to gray-scale image using thresholding decomposition technique is also discussed.

Chao, Tien-Hsin↗
NASA NTRS1974

Optimum adaptive imaging through atmospheric turbulence

Recent results for the atmospheric mode decomposition are applied to an idealized imaging problem in which the receiver has a priori knowledge of the channel impulse response and mode decomposition. It is shown that a channel-matched filter receiver is essentially optimum and, on the average, achieves diffraction-limited performance. Furthermore, when the transmitting aperture lies within a single isoplanatic patch, this system may be realized without a priori channel knowledge by transmitted reference techniques.

Shapiro, J. H.↗
NASA NTRS1994

Optical Implementation of Matching Pursuit for Image Representation

We have developed a technique for image analysis, representation, and decomposition. This technique was motivated by Stephane Mallat's matching-pursuit algorithm. We've altered and simplified the mechanics of his algorithm to enable an extremely fast implementation via optical processing. Initial computer simulations show that our algorithm is capable of decomposing and representing a 2-D image as a linear combination of basis images with both high speed and high fidelity.

matching pursuit adaptive wavelet transform image ↗