Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “imaging”

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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Imaging Electrons in Two Dimensional Materials (Final report)

Two-dimensional (2D) materials have extraordinary characteristics that offer promising new approaches for science and technology. Electrons in graphene can move ballistically through a sheet, even though it is only a single atom thick. And transition metal dichalcogenide materials can be cleaved into 2D flakes of all types – metals, semiconductors, insulators, magnetic materials, and superconductors. To benefit from these discoveries, the science needs to be understood to transform 2D materials into useful new devices and systems. The evolution in time of atomic scale graphene structures has been studied in time with a transmission electron microscope (TEM), and ballistic transport of electrons in graphene was been imaged using a cooled scanning probe microscope (SPM), as well as electron motion in MoS 2 . Graphene is only one atom thick but is extremely strong, creating the opportunity to fabricate atomic scale structures in the lateral direction. Using an atomic resolution TEM, a suspended sheet of graphene can be shaped by a Si impurity atom on its surface that acts like a chisel to open up apertures, one atom at a time. The electrons in the TEM provide both the chiseling energy and the ability to image the results. Electrons and holes in graphene form a new type of electronic system with conical conduction and valence bands that meet at the Dirac point, with no energy gap. For moderate densities, the carriers form a Fermi liquid with ballistic transport over micron-scale distances. Using a cooled SPM the cyclotron orbit of electrons in graphene has been imaged. In the magnetic focusing regime, electrons leaving a point contact circle around and leave from a second point contact when the cyclotron diameter is equal to the contact spacing. The paths of electrons are focused - they enter at different angles but converge again at the exiting contact. When the SPM tip knocks an electron out of its orbit, an imaging signal is created. The ballistic motion of carriers in graphene opens the way for ballistic devices that manipulate beams of electrons and holes. Our collaborator Gil-Ho Lee, in Philip Kim's group, created a collimating contact by placing zig-zag absorbers on either side of entering electrons. Our cooled SPM was used to image the electron beam and determine its 9-degree halfwidth. By changing the gate voltage, a collimated beam of holes was also created, opening the way for colliding beam experiments. Coherent beams of carriers are desirable for quantum information processing. Via Andreev reflection, superconducting contacts can covert Cooper pairs in a superconductor to an ingoing and outgoing electrons and holes. Using our cooled SPM, Andreev reflection was imaged from a superconducting contact on a graphene device. Magnetic focusing was used to create an incoming beam of electrons and an outgoing beam of holes, detected by a third point contact. The images show a clear transition from normal reflection above the superconducting transition temperature to Andreev reflection as the device is cooled. Transition metal dichalcogenides offer a wide array of materials that can be exfoliated into ultrathin 2D sheets. A cooled SPM can be used to detect quantum dots as well as to image electron flow. The tip charge capacitively couples to electrons on the dot, acting as a gate to tune the dot conductance. Coulomb blockade peaks appear as a bullseye pattern in an SPM image as the tip is raster scanned above the dot. This approach was used to detect quantum dots in a MoS 2 channel as the carrier density was reduced and electrons pooled in low energy points. Through our DOE supported research, cooled SPM imaging has proven to be a very useful tool to uncover the motion of electrons and holes in the new quantum materials graphene and MoS 2 .

36 MATERIALS SCIENCE↗
NASA NTRS1986

Automated matching of pairs of SIR-B images for elevation mapping

During the SIR-B mission in October 1984, a significant number of overlapping synthetic aperture radar (SAR) images of various ground areas was collected. This has offered the first opportunity to perform stereo analyses on images from space that cover large ground areas to determine elevation information. This paper presents the preliminary results of an investigation to obtain elevation data from stereo pairs of SIR-B images. First, the accuracy with which elevation information can be derived from SIR-B image pairs is evaluated theoretically. It is shown that elevation accuracy is a function of the slant range resolution, the incidence angles with which the stereo pair is obtained, the accuracies in spacecraft state estimation, and determination of corresponding pixels in the stereo pair. Next, a hierarchical method is developed to match the corresponding pixels. This method involves iterative removal of local distortions and correlations of pairs of local neighborhoods in the two images. Since it is necessary to perform the matching at every pixel in the image, it is very computationally intensive. Therefore, it has been implemented on the Massively Parallel Processor (MPP) at the Goddard Space Flight Center (GSFC). The MPP's speed permits two iterations of this technique to operate on a pair of 512 x 512 images within 7 s. Results of applying this algorithm of SIR-B images of Mount Shasta, CA, are shown. The matching algorithm performs well in regions of the image with significant features. An approximate elevation image derived from the matching process corresponds to published topographic map data, except for certain obvious discontinuities.

Ramapriyan, H. K.↗
NASA NTRS1987

Calibrating AIS images using the surface as a reference

A method of evaluating the initial assumptions and uncertainties of the physical connection between Airborne Imaging Spectrometer (AIS) image data and laboratory/field spectrometer data was tested. The Tuscon AIS-2 image connects to lab reference spectra by an alignment to the image spectral endmembers through a system gain and offset for each band. Images were calibrated to reflectance so as to transform the image into a measure that is independent of the solar radiant flux. This transformation also makes the image spectra directly comparable to data from lab and field spectrometers. A method was tested for calibrating AIS images using the surface as a reference. The surface heterogeneity is defined by lab/field spectral measurements. It was found that the Tuscon AIS-2 image is consistent with each of the initial hypotheses: (1) that the AIS-2 instrument calibration is nearly linear; (2) the spectral variance is caused by sub-pixel mixtures of spectrally distinct materials and shade, and (3) that sub-pixel mixtures can be treated as linear mixtures of pure endmembers. It was also found that the image can be characterized by relatively few endmembers using the AIS-2 spectra.

Smith, M. O.↗
NASA NTRS1988

Autonomous image data reduction by analysis and interpretation

Image data is a critical component of the scientific information acquired by space missions. Compression of image data is required due to the limited bandwidth of the data transmission channel and limited memory space on the acquisition vehicle. This need becomes more pressing when dealing with multispectral data where each pixel may comprise 300 or more bytes. An autonomous, real time, on-board image analysis system for an exploratory vehicle such as a Mars Rover is developed. The completed system will be capable of interpreting image data to produce reduced representations of the image, and of making decisions regarding the importance of data based on current scientific goals. Data from multiple sources, including stereo images, color images, and multispectral data, are fused into single image representations. Analysis techniques emphasize artificial neural networks. Clusters are described by their outlines and class values. These analysis and compression techniques are coupled with decision making capacity for determining importance of each image region. Areas determined to be noise or uninteresting can be discarded in favor of more important areas. Thus limited resources for data storage and transmission are allocated to the most significant images.

Eberlein, Susan↗
NASA NTRS1988

Autonomous image data reduction by analysis and interpretation

Image data is a critical component of the scientific information acquired by space missions. Compression of image data is required due to the limited bandwidth of the data transmission channel and limited memory space on the acquisition vehicle. This need becomes more pressing when dealing with multispectral data where each pixel may comprise 300 or more bytes. An autonomous, real time, on-board image analysis system for an exploratory vehicle such as a Mars Rover is developed. The completed system will be capable of interpreting image data to produce reduced representations of the image, and of making decisions regarding the importance of data based on current scientific goals. Data from multiple sources, including stereo images, color images, and multispectral data, are fused into single image representations. Analysis techniques emphasize artificial neural networks. Clusters are described by their outlines and class values. These analysis and compression techniques are coupled with decision-making capacity for determining importance of each image region. Areas determined to be noise or uninteresting can be discarded in favor of more important areas. Thus limited resources for data storage and transmission are allocated to the most significant images.

Eberlein, Susan↗
NASA NTRS1990

Kalman filter based range estimation for autonomous navigation using imaging sensors

Rotorcraft operating in high-threat environments fly close to the surface of the earth to utilize surrounding terrain, vegetation, or man-made objects to minimize the risk of being detected by the enemy. Two basic requirements for obstacle avoidance are detection and range estimation of the object from the current rotorcraft position. There are many approaches to the estimation of range using a sequence of images. The approach used in this analysis differes from previous methods in two significant ways: an attempt is not made to estimate the rotorcraft's motion from the images; and the interest lies in recursive algorithms. The rotorcraft parameters are assumed to be computed using an onboard inertial navigation system. Given a sequence of images, using image-object differential equations, a Kalman filter (Sridhar and Phatak, 1988) can be used to estimate both the relative coordinates and the earth coordinates of the objects on the ground. The Kalman filter can also be used in a predictive mode to track features in the images, leading to a significant reduction of search effort in the feature extraction step of the algorithm. The purpose is to summarize early results obtained in extending the Kalman filter for use with actual image sequences. The experience gained from the application of this algorithm to real images is very valuable and is a necessary step before proceeding to the estimation of range during low-altitude curvilinear flight. A simple recursive method is presented to estimate range to objects using a sequence of images. The method produces good range estimates using real images in a laboratory set up and needs to be evaluated further using several different image sequences to test its robustness. The feature generation part of the algorithm requires further refinement on the strategies to limit the number of features (Sridhar and Phatak, 1989). The extension of the work reported here to curvilinear flight may require the use of the extended Kalman filter.

Sridhar, Banavar↗
NASA NTRS1990

Infrared images of merging galaxies

Infrared imaging of interacting galaxies is especially interesting because their optical appearance is often so chaotic due to extinction by dust and emission from star formation regions, that it is impossible to locate the nuclei or determine the true stellar distribution. However, at near-infrared wavelengths extinction is considerably reduced, and most of the flux from galaxies originates from red giant stars that comprise the dominant stellar component by mass. Thus near infrared images offer the opportunity to study directly components of galactic structure which are otherwise inaccessible. Such images may ultimately provide the framework in which to understand the activity taking place in many of the mergers with high Infrared Astronomy Satellite (IRAS) luminosities. Infrared images have been useful in identifying double structures in the nuclei of interacting galaxies which have not even been hinted at by optical observations. A striking example of this is given by the K images of Arp 220. Graham et al. (1990) have used high resolution imaging to show that it has a double nucleus coincident with the radio sources in the middle of the dust lane. The results suggest that caution should be applied in the identification of optical bright spots as multiple nuclei in the absence of other evidence. They also illustrate the advantages of using infrared imaging to study the underlying structure in merging galaxies. The authors have begun a program to take near infrared images of galaxies which are believed to be mergers of disk galaxies because they have tidal tails and filaments. In many of these the merger is thought to have induced exceptionally luminous infrared emission (cf. Joseph and Wright 1985, Sanders et al. 1988). Although the optical images of the galaxies show spectacular dust lanes and filaments, the K images all have a very smooth distribution of light with an apparently single nucleus.

Wright, G. S.↗
NASA NTRS1991

Analysis of objects in binary images

Digital image processing techniques are typically used to produce improved digital images through the application of successive enhancement techniques to a given image or to generate quantitative data about the objects within that image. In support of and to assist researchers in a wide range of disciplines, e.g., interferometry, heavy rain effects on aerodynamics, and structure recognition research, it is often desirable to count objects in an image and compute their geometric properties. Therefore, an image analysis application package, focusing on a subset of image analysis techniques used for object recognition in binary images, was developed. This report describes the techniques and algorithms utilized in three main phases of the application and are categorized as: image segmentation, object recognition, and quantitative analysis. Appendices provide supplemental formulas for the algorithms employed as well as examples and results from the various image segmentation techniques and the object recognition algorithm implemented.

Leonard, Desiree M.↗
NASA NTRS1993

An operational method for estimating signal to noise ratios from data acquired with imaging spectrometers

A method, using the concept of local means and local standard deviations of small imaging blocks and using a box counting procedure, has been developed for unsupervised estimation of the average signal to noise ratios of images in which the noise is additive. The method has been applied to simulated images with Gaussian noise, to images acquired with the Airborne Visible Infrared Imaging Spectrometer and with the Geophysical and Environmental Research Imaging Spectrometer. The method is compared with other techniques for estimating signal to noise ratios from imaging data. It is believed that the method is generally applicable to images having many small homogeneous blocks. Because the method does not take into account interband effects, it is not appropriate to use the method to estimate signal to noise ratios from images having nonnegligible interband radiometric calibration errors at spatial scales less than or equal to the size of the small imaging blocks used in the noise estimation.

Gao, Bo-Cai↗
NASA NTRS1993

A summary of image segmentation techniques

Machine vision systems are often considered to be composed of two subsystems: low-level vision and high-level vision. Low level vision consists primarily of image processing operations performed on the input image to produce another image with more favorable characteristics. These operations may yield images with reduced noise or cause certain features of the image to be emphasized (such as edges). High-level vision includes object recognition and, at the highest level, scene interpretation. The bridge between these two subsystems is the segmentation system. Through segmentation, the enhanced input image is mapped into a description involving regions with common features which can be used by the higher level vision tasks. There is no theory on image segmentation. Instead, image segmentation techniques are basically ad hoc and differ mostly in the way they emphasize one or more of the desired properties of an ideal segmenter and in the way they balance and compromise one desired property against another. These techniques can be categorized in a number of different groups including local vs. global, parallel vs. sequential, contextual vs. noncontextual, interactive vs. automatic. In this paper, we categorize the schemes into three main groups: pixel-based, edge-based, and region-based. Pixel-based segmentation schemes classify pixels based solely on their gray levels. Edge-based schemes first detect local discontinuities (edges) and then use that information to separate the image into regions. Finally, region-based schemes start with a seed pixel (or group of pixels) and then grow or split the seed until the original image is composed of only homogeneous regions. Because there are a number of survey papers available, we will not discuss all segmentation schemes. Rather than a survey, we take the approach of a detailed overview. We focus only on the more common approaches in order to give the reader a flavor for the variety of techniques available yet present enough details to facilitate implementation and experimentation.

Spirkovska, Lilly↗
NASA NTRS1993

Identification of an interstellar oxide grain from the Murchison meteorite by ion imaging

We report here the first use of a new ion-imaging system to locate a rare interstellar aluminum oxide grain in a Murchison acid residue. While several types of carbon-rich interstellar grains, including graphite, diamond, SiC, and TiC, have previously been found, isotopically anomalous interstellar oxide grains have proven more elusive. We have developed an ion imaging system which allows us to map the isotopic composition of large numbers of grains relatively quickly and is, thus, ideally suited to search for isotopically exotic subsets of grains. The system consists of a PHOTOMETRICS CCD camera coupled to the microchannel plate/fluorescent screen of the WU modified CAMECA IMS-3F ion microprobe. Isotopic images of the sample surface are focused on the CCD and digitized. Subsequent image processing identifies individual grains in the images and determines isotopic ratios for each. For the present work, we have imaged in O-16 and O-18; negligible contributions of (17)OH(-) and (16)OH2(-) signals to the O-18 signal allow the use of low mass resolution, simplifying the measurements. Repeated imaging runs on terrestrial corundum particles showed that the system measures isotopic ratios reproducibly to about +/- 40%. Each imaging run took about six minutes to complete, and for this study there were on average 5-15 grains in each image. We have conducted imaging searches in 2-4 micron size separates of both Orgueil and Murchison.

Nittler, L. R.↗
NASA NTRS1993

Instantaneous velocity field imaging instrument for supersonic reacting flows

The technical tasks conducted to develop and demonstrate a new gas velocity measurement technique for high enthalpy reacting flows is described. The technique is based on Doppler-shifted Planar Laser-induced Fluorescence (PLIF) imaging of the OH radical. The imaging approach permits, in principle, single-shot measurements of the 2-D distribution of a single velocity component in the measurement plane, and is thus a technique of choice for applications in high enthalpy transient flow facilities. In contrast to previous work in this area, the present program demonstrated an approach which modified the diagnostic technique to function under the constraints of practical flow conditions of engineering interest, rather than vice-versa. In order to accomplish the experimental demonstrations, the state-of-the-art in PLIF diagnostic techniques was advanced in several ways. Each of these tasks is described in detail and is intended to serve as a reference in supporting the transition of this new capability to the fielded PLIF instruments now installed at several national test facilities. Among the new results of general interest in LlF-based flow diagnostics, a detailed set of the first measurements of the collisional broadening and shifting behavior of OH (1,0) band transitions in H7-air combustion environments is included. Such measurements are critical in the design of a successful strategy for PLIF velocity imaging; they also relate to accurate concentration and temperature measurements, particularly in compressible flow regimes. Furthermore, the results shed new light on the fundamental relationship between broadening and energy transfer collisions in OH A(sup 2)Sigma(+)v(sup ') = 1. The first single-pulse, spectrally-resolved measurements of the output of common pulsed dye lasers were also produced during the course of this effort. As with the OH broadening measurements, these data are a significant aspect of a successful velocity imaging strategy, and also have potential implications for many other LIF measurement techniques. Our results indicated the need to modify the commercially available laser cavity in order to accommodate the constraints imposed by typical SCRAMJET combustion characteristics as well as to increase the instrument's velocity dynamic range to span an intra-image range in excess of 2 km/s. The various technical efforts were brought together in a series of experiments demonstrating the applicability of the technique in a high pressure, high temperature H2-air combustion system. The resultant images were compared with 2-D flow simulations in order to determine the accuracy of the instrument. Mean velocity imaging in flows with an axis of symmetry was demonstrated with an accuracy of +/- 50 m/s out of an intra-image dynamic range of 1600 m/s, including reversed flow. A more complex configuration amenable to single-shot imaging in flows without an axis of symmetry was also demonstrated. Limitations imposed by available equipment resulted in an accuracy of about +/- 200 m/s out of 1750 m/s in these demonstrations. Minor modifications to the present configuration were suggested to improve this performance. Each technical task is described in detail, along with significance of the results for the overall imaging velocimeter configuration. This report should allow the user community to integrate this new measurement capability in their existing instrumentation platforms.

Allen, M. G.↗
NASA NTRS1992

Image pattern recognition supporting interactive analysis and graphical visualization

Image Pattern Recognition attempts to infer properties of the world from image data. Such capabilities are crucial for making measurements from satellite or telescope images related to Earth and space science problems. Such measurements can be the required product itself, or the measurements can be used as input to a computer graphics system for visualization purposes. At present, the field of image pattern recognition lacks a unified scientific structure for developing and evaluating image pattern recognition applications. The overall goal of this project is to begin developing such a structure. This report summarizes results of a 3-year research effort in image pattern recognition addressing the following three principal aims: (1) to create a software foundation for the research and identify image pattern recognition problems in Earth and space science; (2) to develop image measurement operations based on Artificial Visual Systems; and (3) to develop multiscale image descriptions for use in interactive image analysis.

Coggins, James M.↗
NASA NTRS1995

Fine-resolution imaging of solar features using Phase-Diverse Speckle

Phase-diverse speckle (PDS) is a novel imaging technique intended to overcome the degrading effects of atmospheric turbulence on fine-resolution imaging. As its name suggests, PDS is a blend of phase-diversity and speckle-imaging concepts. PDS reconstructions on solar data were validated by simulation, by demonstrating internal consistency of PDS estimates, and by comparing PDS reconstructions with those produced from well accepted speckle-imaging processing. Several sources of error in data collected with the Swedish Vacuum Solar Telescope (SVST) were simulated: CCD noise, quantization error, image misalignment, and defocus error, as well as atmospheric turbulence model error. The simulations demonstrate that fine-resolution information can be reliably recovered out to at least 70% of the diffraction limit without significant introduction of image artifacts. Additional confidence in the SVST restoration is obtained by comparing its spatial power spectrum with previously-published power spectra derived from both space-based images and earth-based images corrected with traditional speckle-imaging techniques; the shape of the spectrum is found to match well the previous measurements. In addition, the imagery is found to be consistent with, but slightly sharper than, imagery reconstructed with accepted speckle-imaging techniques.

Paxman, Richard G.↗
NASA NTRS2000

The Extended-Image Tracking Technique Based on the Maximum Likelihood Estimation

This paper describes an extended-image tracking technique based on the maximum likelihood estimation. The target image is assume to have a known profile covering more than one element of a focal plane detector array. It is assumed that the relative position between the imager and the target is changing with time and the received target image has each of its pixels disturbed by an independent additive white Gaussian noise. When a rotation-invariant movement between imager and target is considered, the maximum likelihood based image tracking technique described in this paper is a closed-loop structure capable of providing iterative update of the movement estimate by calculating the loop feedback signals from a weighted correlation between the currently received target image and the previously estimated reference image in the transform domain. The movement estimate is then used to direct the imager to closely follow the moving target. This image tracking technique has many potential applications, including free-space optical communications and astronomy where accurate and stabilized optical pointing is essential.

Tsou, Haiping↗
NASA NTRS2000

High-Definition Television (HDTV) Images for Earth Observations and Earth Science Applications

As part of Detailed Test Objective 700-17A, astronauts acquired Earth observation images from orbit using a high-definition television (HDTV) camcorder, Here we provide a summary of qualitative findings following completion of tests during missions STS (Space Transport System)-93 and STS-99. We compared HDTV imagery stills to images taken using payload bay video cameras, Hasselblad film camera, and electronic still camera. We also evaluated the potential for motion video observations of changes in sunlight and the use of multi-aspect viewing to image aerosols. Spatial resolution and color quality are far superior in HDTV images compared to National Television Systems Committee (NTSC) video images. Thus, HDTV provides the first viable option for video-based remote sensing observations of Earth from orbit. Although under ideal conditions, HDTV images have less spatial resolution than medium-format film cameras, such as the Hasselblad, under some conditions on orbit, the HDTV image acquired compared favorably with the Hasselblad. Of particular note was the quality of color reproduction in the HDTV images HDTV and electronic still camera (ESC) were not compared with matched fields of view, and so spatial resolution could not be compared for the two image types. However, the color reproduction of the HDTV stills was truer than colors in the ESC images. As HDTV becomes the operational video standard for Space Shuttle and Space Station, HDTV has great potential as a source of Earth-observation data. Planning for the conversion from NTSC to HDTV video standards should include planning for Earth data archiving and distribution.

Robinson, Julie A.↗
NASA NTRS2000

The Proton and Electron Aurora as Seen by Image-FUV and FAST

The Far Ultraviolet (FUV) instrument on IMAGE images the aurora in three different wavelength regions. The Wideband Imaging Camera (WIC) observes the molecular Lyman-Birge-Hopfield (LBH) and atomic Nitrogen emissions at 140-190 nm. The two channels of the Spectrographic Imager (SI) observe the Doppler shifted Lyman Alpha emission of precipitating protons at 121.8 nm (SI 12) and the mostly electron produced emission from oxygen OI at 135.6 nm (SI13). The major advantage of FUV compared to previously flown UV imagers is the simultaneous operation of all three imaging systems without the need for filter changes and the uncertainty of temporal changes of the aurora between exposures. The FAST satellite passes every two hours through FUV images during apogee operations. This enables a comparison between the remotely imaged particle precipitation and the in-situ measurements along the FAST track. The detailed analysis of images from all three systems together with a full simulation of auroral emissions based on in-situ measurements by FAST confirms the laboratory calibrations of FUV. The spatial resolution and image quality of WIC permits the observation of a good correspondence between in-situ and remote measurements of precipitation boundaries. The clear separation between the lower latitude proton precipitation and the more structured higher latitude electron precipitation is obtained with both SI-channels.

Gerard, J.-C.↗
NASA NTRS1996

Perceptual Classification Images from Vernier Acuity Masked by Noise

Letting external noise rather than internal noise limit discrimination performance allows information to be extracted about the observer's stimulus classification rule. A perceptual classification image is the correlation over trials between the noise amplitude at a spatial location and the observer's responses. If, for example, the observer followed the rule of the ideal observer, the perceptual classification image would be an estimate of the ideal observer filter, the difference between the two unmasked images being discriminated. Perceptual classification images were estimated for a vernier discrimination task. The display screen had 48 pixels per degree horizontally and vertically. The no-offset image had a dark horizontal line of 4 pixels, a 1 pixel space, and 4 more dark pixels. Classification images were based on 1600 discrimination trials with the line contrast adjusted to keep the error rate near 25 percent. In the offset image, the second line was one pixel higher. Unlike the ideal observer filter (a horizontal dipole), the observer perceptual classification images are strongly oriented. Fourier transforms of the classification images had a peak amplitude near one cycle per degree and an orientation near 25 degrees. The spatial spread is much more than image blur predicts, and probably indicates the spatial position uncertainty in the task.

Ahumada, A. J.↗