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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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We have determined the densities of Si in the liquid, rho1(T), and solid,rho s(T), states as a function of temperature,T, by employing an image digitizing technique and numerical calculation methods in combination with an electrostatic levitator.
The author has identified the following significant results. Automatic image registration and resampling techniques applied to LANDSAT data achieved accuracies, resulting in mean radial displacement errors of less than 0.2 pixel. The process method utilized recursive computational techniques and line-by-line updating on the basis of feedback error signals. Goodness of local feature matching was evaluated through the implementation of a correlation algorithm. An automatic restart allowed the system to derive control point coordinates over a portion of the image and to restart the process, utilizing this new control point information as initial estimates.
The multiscale retinex with color restoration (MSRCR) has shown itself to be a very versatile automatic image enhancement algorithm that simultaneously provides dynamic range compression, color constancy, and color rendition. A number of algorithms exist that provide one or more of these features, but not all. In this paper we compare the performance of the MSRCR with techniques that are widely used for image enhancement. Specifically, we compare the MSRCR with color adjustment methods such as gamma correction and gain/offset application, histogram modification techniques such as histogram equalization and manual histogram adjustment, and other more powerful techniques such as homomorphic filtering and 'burning and dodging'. The comparison is carried out by testing the suite of image enhancement methods on a set of diverse images. We find that though some of these techniques work well for some of these images, only the MSRCR performs universally well on the test set.
It is desired to simulate natural rain in a wind tunnel in order to investigate its influence on the aerodynamic characteristics of aircraft. Rain simulation nozzles have been developed and tested at JPL. Pulsed laser sheet illumination is used to photograph the droplets in the moving airstream. Digital image processing techniques are applied to these photographs for calculation of rain statistics to evaluate the performance of the nozzles. It is found that fixed hypodermic type nozzles inject too much water to simulate natural rain conditions. A modification uses two aerodynamic spinners to flex a tube in a pseudo-random fashion to distribute the water over a larger area.
Several areas of applications of image processing to astronomy were identified and discussed. These areas include: (1) deconvolution for atmospheric seeing compensation; a comparison between maximum entropy and conventional Wiener algorithms; (2) polarization in galaxies from photographic plates; (3) time changes in M87 and methods of displaying these changes; (4) comparing emission line images in planetary nebulae; and (5) log intensity, hue saturation intensity, and principal component color enhancements of M82. Examples are presented of these techniques applied to a variety of objects.
Devices that respond to radiation on a cell level will produce histograms showing the relative frequency of cell damage as a function of damage. The measured distribution is the convolution of distributions from radiation responses, measurement noise, and manufacturing parameters. A method of extracting device characteristics and parameters from measured distributions via mathematical and image subtraction techniques is described.
PDP 11/40 computer is at the heart of a general purpose interactive data analysis facility designed to permit easy access to data in both visual imagery and graphic representations. The major components consist of: the 11/40 CPU and 256 K bytes of 16-bit memory; two TU10 tape drives; 20 million bytes of disk storage; three user terminals; and the COMTAL image processing display system. The application of image enhancement techniques to two sequences of photographs of Comet Halley taken in Egypt in 1910 provides evidence for eruptions from the comet's nucleus.
Rocket engine hot-fire ground testing is necessary to understand component performance, reliability and engine system interactions during development. The J-2X upper stage engine completed a series of developmental hot-fire tests that derived performance of the engine and components, validated analytical models and provided the necessary data to identify where design changes, process improvements and technology development were needed. The J-2X development engines were heavily instrumented to provide the data necessary to support these activities which enabled the team to investigate any anomalies experienced during the test program. This paper describes the development of an optical digital image correlation technique to augment the data provided by traditional strain gauges which are prone to debonding at elevated temperatures and limited to localized measurements. The feasibility of this optical measurement system was demonstrated during full scale hot-fire testing of J-2X, during which a digital image correlation system, incorporating a pair of high speed cameras to measure three-dimensional, real-time displacements and strains was installed and operated under the extreme environments present on the test stand. The camera and facility setup, pre-test calibrations, data collection, hot-fire test data collection and post-test analysis and results are presented in this paper.
Abstract Dark-field X-ray microscopy (DFXM) is a high-resolution, X-ray-based diffraction microstructure imaging technique that uses an objective lens aligned with the diffracted beam to magnify a single Bragg reflection. DFXM can be used to spatially resolve local variations in elastic strain and orientation inside embedded crystals with high spatial (~ 60 nm) and angular (~ 0.001°) resolution. However, as with many high-resolution imaging techniques, there is a trade-off between resolution and field of view, and it is often desirable to enrich DFXM observations by combining it with a larger field-of-view technique. Here, we combine DFXM with high-resolution X-ray diffraction (HR-XRD) applied to an in-situ investigation of static recrystallization in an 80% hot-compressed Mg–3.2Zn–0.1Ca wt.% (ZX30) alloy. Using HR-XRD, we track the relative grain volume of > 8000 sub-surface grains during annealing in situ. Then, at several points during the annealing process, we “zoom in” to individual grains using DFXM. This combination of HR-XRD and DFXM enables multiscale characterization, used here to study why particular grains grow to consume a large volume fraction of the annealed microstructure. This technique pairing is particularly useful for small and/or highly deformed grains that are often difficult to resolve using more standard diffraction microstructure imaging techniques.
Optical flow visualization techniques such as schlieren and shadowgraph photography are essential to understanding fluid flow when interpreting acquired wind tunnel test data. Output of the standard implementations of these visualization techniques in test facilities are often limited only to qualitative interpretation of the resulting images. Although various quantitative optical techniques have been developed, these techniques often require special equipment or are focused on obtaining very precise and accurate data about the visualized flow. These systems are not practical in small, production wind tunnel test facilities. However, high-speed photography capability has become a common upgrade to many test facilities in order to better capture images of unsteady flow phenomena such as oscillating shocks and flow separation. This paper describes novel techniques utilized by the authors to analyze captured high-speed schlieren and shadowgraph imagery from wind tunnel testing for quantification of observed unsteady flow frequency content. Such techniques have applications in parametric geometry studies and in small facilities where more specialized equipment may not be available.
As spectral imaging techniques are becoming more prominent in science, advanced image segmentation algorithms are required to identify appropriate domains in these images. We present a version of image segmentation called manifold projection image segmentation (MPIS) that is generally applicable to a broad range of systems without the need for training because MPIS uses unsupervised machine learning with a few physically motivated hyperparameters. We apply MPIS to nanoscale x-ray absorption near edge structure (XANES) imaging, where XANES spectra are collected with nanometer spatial resolution. We show the superiority of manifold projection over linear transformations, such as the commonly used principal component analysis (PCA). Moreover, MPIS maintains accuracy while reducing computation time and sensitivity to noise compared to the standard nano-XANES imaging analysis procedure. Finally, we demonstrate how multimodal information, such as x-ray fluorescence data and spatial location of pixels, can be incorporated into the MPIS framework. We propose that MPIS is adaptable for any spectral imaging technique, including scanning transmission x-ray microscopy, where the length scale of domains is larger than the resolution of the experiment.
Liquid jets are found in many applications, from printing to manufacturing to entertainment. Herein this study uses three different noninvasive imaging modalities to compare resulting images of a liquid jet operating at three Reynolds numbers that cover laminar, transitional, and turbulent flow. Selected measurement quantities from each image type are also compared. High-speed backlit (BL) imaging is a simple imaging technique found in many laboratories, and this is compared to two high-speed X-ray imaging techniques, white beam (WB) imaging and focused beam (FB) radiography. BL imaging can provide a wide field of view and is easy to implement, but it only shows the presence or absence of liquid. WB imaging can show detailed contours on the surface of the liquid jet, but the imaging region is much smaller. FB radiography produces a point-source measurement and can provide the quantitative, instantaneous local liquid path length, termed the equivalent path length (EPL). All three techniques provide similar measures of jet thickness, with the FB measurements having less variation. FB measurements can also provide detailed cross sections of the average liquid jet thickness at high spatial resolutions.
The basic concepts of fine-resolution, imaging radar systems are reviewed. Both side-looking and hologram (downward-looking) radars are described and compared. Several examples of microwave imagery obtained with these two types of systems are shown.
This report presents new algorithms for target detection, feature extraction, and image formation with the synthetic aperture radar (SAR) technology. For target detection, we consider target detection with SAR and coherent subtraction. We also study how the image false alarm rates are related to the target template false alarm rates when target templates are used for target detection. For feature extraction from SAR images, we present a computationally efficient eigenstructure-based 2D-MODE algorithm for two-dimensional frequency estimation. For SAR image formation, we present a robust parametric data model for estimating high resolution range signatures of radar targets and for forming high resolution SAR images.
The need for a validation technique for computational fluid dynamics (CFD) codes in STOVL applications has led to research efforts to apply infrared thermal imaging techniques to visualize gaseous flow fields. Specifically, a heated, free-jet test facility was constructed. The gaseous flow field of the jet exhaust was characterized using an infrared imaging technique in the 2 to 5.6 micron wavelength band as well as conventional pitot tube and thermocouple methods. These infrared images are compared to computer-generated images using the equations of radiative exchange based on the temperature distribution in the jet exhaust measured with the thermocouple traverses. Temperature and velocity measurement techniques, infrared imaging, and the computer model of the infrared imaging technique are presented and discussed. From the study, it is concluded that infrared imaging techniques coupled with the radiative exchange equations applied to CFD models are a valid method to qualitatively verify CFD codes used in STOVL applications.
An overview is presented of the evolution of the computer configuration at JPL's Image Processing Laboratory (IPL). The development of techniques for the geometric transformation of digital imagery is discussed and consideration is given to automated and semiautomated image registration, and the registration of imaging and nonimaging data. The increasing complexity of image processing tasks at IPL is illustrated with examples of various applications from the planetary program and earth resources activities. It is noted that the registration of existing geocoded data bases with Landsat imagery will continue to be important if the Landsat data is to be of genuine use to the user community.
Stereo Imaging Velocimetry (SIV) is a NASA Glenn Research Center (GRC) developed fluid physics technique for measuring threedimensional (3-D) velocities in any optically transparent fluid that can be seeded with tracer particles. SIV provides a means to measure 3-D fluid velocities quantitatively and qualitatively at many points. This technique provides full-field 3-D analysis of any optically clear fluid or gas experiment using standard off-the-shelf CCD cameras to provide accurate and reproducible 3-D velocity profiles for experiments that require 3-D analysis. A flame ball is a steady flame in a premixed combustible atmosphere which, due to the transport properties (low Lewis-number) of the mixture, does not propagate but is instead supplied by diffusive transport of the reactants, forming a premixed flame. This flame geometry presents a unique environment for testing combustion theory. We present our analysis of flame ball phenomena utilizing SIV technology in order to accurately calculate the 3-D position of a flame ball(s) during an experiment, which can be used as a direct comparison of numerical simulations.
Brain tumors are often fatal. Therefore, accurate brain tumor image segmentation is critical for the diagnosis, treatment, and monitoring of patients with these tumors. Magnetic resonance imaging (MRI) is a commonly used imaging technique for capturing brain images. Both machine learning and deep learning techniques are popular in analyzing MRI images. This article reviews some commonly used machine learning and deep learning techniques for brain tumor MRI image segmentation. The limitations and advantages of the reviewed machine learning and deep learning methods are discussed. Even though each of these methods has a well-established status in their individual domains, the combination of two or more techniques is currently an emerging trend.