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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 described a challenging neural-network hardware implementation that would mate a 64x64-pixel infrared sensor directly on to a 3-dimensionally packaged set of neural processing chips with parallel input for high speed image processing. Non linearity effects and range compression are also discussed.
Photorefractive semiconductors are attractive for information processing, becuase of fast material response, compatibility with semiconductor lasers, and availability of cross polarization diffraction for enhancing signal-to-noise ration. This paper presents recent experimental results on information processing using photorefractive GaAs, InP and CdTe, including image processing with semiconductor lasers.
One of the new projects by NASA to explore environmental change is the Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) spacecraft. The primary instrument aboard the PACE spacecraft is the Ocean Color Instrument (OCI), an advanced optical spectrometer that will measure the color of the ocean from the ultraviolet to shortwave infrared range for the purpose of observing and monitoring ocean and coastal biology. As part of the optical alignment testing that must be completed before the instrument is built, the measurement stability of the detectors at space flight operating temperatures must be determined to ensure alignment is maintained. Therefore, this project focuses on the development of an imaging technique that adheres to testing requirements and can be used to determine the stability of the OCI detector. The movements of targets affixed to a high-precision stage were analyzed through an image processing program to test the ability of the imaging technique to detect very small (under 10 micrometers) movements. It was found that movements as small as half a pixel (~6 microns) and 1 pixel (~12 microns) were able to be accurately and consistently detected with this imaging technique. This project found that the designed image analysis technique fulfills testing and measurement requirements and will be an effective metrology technique for the OCI detector stability test.
A method of identifying grains in polycrystalline materials, the method including (a) identifying local crystal structure of the polycrystalline material based on neighbor coordination or pattern recognition machine learning, the local crystal structure including grains and grain boundaries, (b) pre-processing the grains and the grain boundaries using image processing techniques, (c) conducting grain identification using unsupervised machine learning; and (d) refining a resolution of the grain boundaries.
Optical microscopy imaging of single molecules and single particles is an essential method for studying fundamental biological and chemical processes at the molecular and nanometer scale. The best spatial resolution (~ λ/2) achievable in traditional optical microscopy is governed by the diffraction of light. However, single molecule-based super-localization and super-resolution microscopy imaging techniques have emerged in the past decade. Individual molecules can be localized with nanometer scale accuracy and precision for studying of biological and chemical processes.This work uncovered the heterogeneous properties of the pore structures. In this dissertation, the coupling of molecular transport and catalytic reaction at the single molecule and single particle level in multilayer mesoporous nanocatalysts was elucidated. Most previous studies dealt with these two important phenomena separately. A fluorogenic oxidation reaction of non-fluorescent amplex red to highly fluorescent resorufin was tested. The diffusion behavior of single resorufin molecules in aligned nanopores was studied using total internal reflection fluorescence microscopy (TIRFM).
Position and orientation of target measured in six degrees of freedom. Robotic vision subsystem measures relative position and orientation of specially designed target. Uses standard image-processing algorithms implemented directly in circuitry instead of computer programs. This feature makes it possible to extract complete sets of target-tracking data from successive image frames at rate of 30 frames per second. Five bright circles of target positioned in such way that video images of them processed into data on position and orientation of target relative to camera. Subsystem useful in industrial assembly operation requiring automatic joining of parts initially oriented and moving randomly.
Techniques, systems, and devices are disclosed for non-invasive monitoring and imaging of nuclear fuel inside a nuclear reactor using muon detector arrays. In one aspect, these detector arrays are placed outside the reactor vessel or building for investigating the reactors without access to the cores, therefore the imaging process is non-invasive. In some implementation, these detector arrays measure both muon scattering and absorption to enable imaging and characterizing not only the very high-Z fuel materials, but also other materials in the reactor, thereby obtaining a more complete picture of reactor status. When applied to damaged reactors, the disclosed proposed techniques, systems, and devices, through the process of providing an image, can reveal the presence (or absence) of damage to fuel rod assemblies or puddles of molten fuel at the bottom of the containment vessel, thus providing crucial information to guide decisions about remedial actions.
Greatly increased activity in the field of radar image applications in the coming years demands that techniques of radar image analysis, enhancement, and simulation be developed now. Since the statistical nature of radar imagery differs from that of photographic imagery, one finds that the required digital image processing algorithms (e.g., for improved viewing and feature extraction) differ from those currently existing. This paper addresses these problems and discusses work at the Remote Sensing Laboratory in image simulation and processing, especially for systems comparable to the formerly operational SEASAT synthetic aperture radar.
Physical characteristics of the combustion of metal particle groups have been addressed in this research. The combustion behavior and interaction effects of multiple metal particles has been studied using a microgravity environment, which presents a unique opportunity to create an "aerosol" consisting of relatively large particles, i.e., 50-300 m diameter. Combustion behavior of such an aerosol could be examined using methods adopted from well-developed single particle combustion research. The experiment included fluidizing relatively large (order of 100 m diameter) uniform metal particles under microgravity and igniting such an "aerosol" using a hot wire igniter. The flame propagation and details of individual particle combustion and particle interaction have been studied using a high speed movie and video-imaging with cameras coupled with microscope lenses to resolve individual particles. Interference filters were used to separate characteristic metal and metal oxide radiation bands from the thermal black body radiation. Recorded flame images were digitized and various image processing techniques including flame position tracking, color separation, and pixel by pixel image comparison were employed to understand the processes occurring in the burning aerosol. The development of individual particle flames, merging or separation, and extinguishment as well as induced particle motion have been analyzed to identify the mechanisms governing these processes. Size distribution, morphology, and elemental compositions of combustion products were characterized and used to link the observed in this project aerosol combustion phenomena with the recently expanded mechanism of single metal particle combustion.
The main objective of this research is to understand the mechanisms by which particle interactions affect ignition and combustion in the two-phase systems. Combustion of metal aerosols representing the two-phase systems is carried out in the microgravity environment enabling one to avoid the buoyant flows that mask the particle motion due to the particle-particle interaction effects. In addition, relatively large, e.g., 100 micron diameter particles can be used, that remain aerosolized (i.e., do not fall down as they would at normal gravity) so that their behavior ahead, behind, and within the propagating flame can be resolved optically. An experimental apparatus exploiting this approach has been designed for the 2.2-s drop tower microgravity experiments. A typical experiment includes fluidizing metal particles under microgravity in an acoustic field, turning off the acoustic exciter, and igniting the created aerosol at a constant pressure using a hot wire igniter. The flame propagation and details of the individual particle combustion and particle interactions are studied using high-speed movie and video cameras coupled with microscope lenses to resolve individual particles. Recorded flame images are digitized and various image processing techniques including flame position tracking, color separation, and pixel by pixel image comparisons are employed to understand the processes occurring in the burning aerosols. Condensed combustion products are collected after each experiment for the phase, composition, and morphology analyses. New experiments described in this paper address combustion of Ti and Al particle clouds in air and combustion of Mg particle clouds in CO2. In addition, microgravity combustion experiments have been conducted with the particles of the newly produced Al-Mg mechanical alloys aerosolized in air.
A handheld biometric imaging device having an array of cameras configured to simultaneously capture face, iris and fingerprint biometrics of a subject. The device includes a plurality of visible-light cameras and a plurality of infrared-light cameras capable of being triggered simultaneously to obtain a plurality of images from which a 3D image of the light field can be constructed. The device includes a plurality of visible-light illuminators and a plurality of infrared-light illuminators that allow images of a subject to be captured under different lighting profiles. The device may include an onboard control system that is capable of reconstructing a face region, an iris region and a fingerprint region from the 3D light-field image, and then extract a corresponding face template, an iris template, and a fingerprint template from the respective reconstructed regions. The extracted face, iris, and fingerprint templates may be used for enrollment and/or comparison against a biometric-template database associated with one or more watchlists.
Images processed rapidly in rugged, compact device. Conceptual integrated optical image processor performs complicated analog calculations, including Fourier transforms, convolutions, correlations, and matrix multiplications. Compact and rugged on account of monolithic structure, processor faster than equivalent all-electronic devices because calculations require only time for light to travel across device; processing speed limited by electronic input and output circuits.
The TSPT (Time Series Product Tool) software was custom-designed for NASA to rapidly create and display single-band and band-combination time series, such as NDVI (Normalized Difference Vegetation Index) images, for wide-area crop surveillance and for other time-critical applications. The TSPT, developed in MATLAB, allows users to create and display various MODIS (Moderate Resolution Imaging Spectroradiometer) or simulated VIIRS (Visible/Infrared Imager Radiometer Suite) products as single images, as time series plots at a selected location, or as temporally processed image videos. Manually creating these types of products is extremely labor intensive; however, the TSPT development tool makes the process simplified and efficient. MODIS is ideal for monitoring large crop areas because of its wide swath (2330 km), its relatively small ground sample distance (250 m), and its high temporal revisit time (twice daily). Furthermore, because MODIS imagery is acquired daily, rapid changes in vegetative health can potentially be detected. The new TSPT technology provides users with the ability to temporally process high-revisit-rate satellite imagery, such as that acquired from MODIS and from its successor, the VIIRS. The TSPT features the important capability of fusing data from both MODIS instruments onboard the Terra and Aqua satellites, which drastically improves cloud statistics. With the TSPT, MODIS metadata is used to find and optionally remove bad and suspect data. Noise removal and temporal processing techniques allow users to create low-noise time series plots and image videos and to select settings and thresholds that tailor particular output products. The TSPT GUI (graphical user interface) provides an interactive environment for crafting what-if scenarios by enabling a user to repeat product generation using different settings and thresholds. The TSPT Application Programming Interface provides more fine-tuned control of product generation, allowing experienced programmers to bypass the GUI and to create more user-specific output products, such as comparison time plots or images. This type of time series analysis tool for remotely sensed imagery could be the basis of a large-area vegetation surveillance system. The TSPT has been used to generate NDVI time series over growing seasons in California and Argentina and for hurricane events, such as Hurricane Katrina.
Purpose: To propose a new method for estimating scatter in x-ray imaging. Conventional antiscatter grids reject scatter at an efficiency that is constant or slowly varying over the surface of the grid. A striped ratio antiscatter grid, composed of stripes that alternate between high and low grid ratio, could be used instead. Such a striped ratio grid would reduce scatter-to-primary ratio as a conventional grid would, but more importantly, the signal discontinuities at the boundaries of stripes can be used to estimate local scatter content. Methods: Signal discontinuities provide information on scatter, but are contaminated by variation in primary radiation. A nonlinear image processing algorithm is used to estimate the scatter content in the presence of primary variation. We emulated a striped ratio grid by imaging phantoms with two sequential CT scans, one with and one without a conventional grid. These two scans are processed together to mimic a striped ratio grid. This represents a best case limit of the striped ratio grid, in that the extent of grid ratio modulation is very high and the scatter contrast is maximized. Results: In a uniform cylinder, the striped ratio grid virtually eliminates cupping. Artifacts from scatter are improved in an anthropomorphic phantom. Some banding artifacts are induced by the striped ratio grid. Conclusions: Striped ratio grids could be a simple and effective evolution of conventional antiscatter grids. Construction and validation of a physical prototype remains an important future step.
JPL's Multimission Operations Systems Office (MOSO) provides a multimission facility at JPL for processing science instrument data from NASA's planetary missions. This facility, the Multimission Image Processing System (MIPS), is developed and maintained by MOSO to meet requirements that span the NASA family of planetary missions. Although the word 'image' appears in the title, MIPS is used to process instrument data from a variety of science instruments. This paper describes the design of a new system architecture now being implemented within the MIPS to support future planetary mission activities at significantly reduced operations and maintenance cost.
Researchers described a new representation, the local geometry, for early visual processing which is motivated by results from biological vision. This representation is richer than is often used in image processing. It extracts more of the local structure available at each pixel in the image by using receptive fields that can be continuously rotated and that go to third order spatial variation. Early visual processing algorithms such as edge detectors and ridge detectors can be written in terms of various local geometries and are computationally tractable. For example, Canny's edge detector has been implemented in terms of a local geometry of order two, and a ridge detector in terms of a local geometry of order three. The edge detector in local geometry was applied to synthetic and real images and it was shown using simple interpolation schemes that sufficient information is available to locate edges with sub-pixel accuracy (to a resolution increase of at least a factor of five). This is reasonable even for noisy images because the local geometry fits a smooth surface - the Taylor series - to the discrete image data. Only local processing was used in the implementation so it can readily be implemented on parallel mesh machines such as the MPP. Researchers expect that other early visual algorithms, such as region growing, inflection point detection, and segmentation can also be implemented in terms of the local geometry and will provide sufficiently rich and robust representations for subsequent visual processing.
Applying the same LANDSAT-1 data to three substantially different image processing systems, a snow mapping task was performed. LARSYS Ver.3, STANSORT-2, and General Electric Image-100 did all the jobs of detecting the snowline in forested mountainous terrain, and to determine the snowcovered area. While the control and accuracy achieved with LARSYS is remarkable, time and effort to perform the processing favor the systems STANSORT and Image-100. The experiences and results demonstrate the need for a fast interactive system for operational snowmapping with multispectral satellite data.
Several sets of LANDSAT image segments and a set of simple image processing programs operating in batch mode are being used to teach an introductory course in digital image analysis and classification. The image data sets contain only a small number of pixels and can be run quickly on most university computing systems. A number of image data sets derived from the raw spectral bands (smoothed data sets, band ratios and texture data sets) allows the student to examine and include these extracted variables in the classification process. Another data set consists of three registered LANDSAT image segments for three different dates so that the student may experiment with multitemporal data processing. The three LANDSAT scenes used in the class are described and the image data sets available for class exercises are listed.