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At least 397 records · Page 22

Multiseasonal variables in digital image enhancements for geological applications

Examples of enhanced multiseasonal orbital imagery illustrate the influence of multiseasonal changes in their spatial and spectral attributes, and consequently in their application to structural geology and lithological discrimination. Shadow effects associated with appropriate solar elevation and azimuth effects enhance the spatial attributes but not the spectral. In this case, variations in illumination conditions should be minimized by selecting images with high solar elevation and by the use of techniques that minimize illumination conditions. Multiseasonal imagery should be used in the identification of spectral contrast changes of rock-soil-vegetation associations which can provide evidences of related lithological units and structural features. The extraction of maximum geological information requires, at least, a fall/winter and a spring/summer scene from which spatial, spectral and multiseasonal attributes can be adequately explored.

Parada, N. D. J.↗

Computing 3-D structure of rigid objects using stereo and motion

Work performed as a step toward an intelligent automatic machine vision system for 3-D imaging is discussed. The problem considered is the quantitative 3-D reconstruction of rigid objects. Motion and stereo are the two clues considered in this system. The system basically consists of three processes: the low level process to extract image features, the middle level process to establish the correspondence in the stereo (spatial) and motion (temporal) modalities, and the high level process to compute the 3-D coordinates of the corner points by integrating the spatial and temporal correspondences.

Nguyen, Thinh V.↗

Matching of dissimilar radar images using Marr-Hildreth zero crossings

Two alternatives to the classical method for finding corresponding points in opposite-side synthetic aperture radar imagery are presented. These new methods focus on matching the shapes of large-scale features in the images rather than on correlating high-frequency pixel gray values. One of the methods may be of use in matching radar images to optical images. The large-scale features are extracted using the Marr-Hildreth operator.

Mcconnell, Ross M.↗

Parallel implementation and evaluation of motion estimation system algorithms on a distributed memory multiprocessor using knowledge based mappings

Several techniques to perform static and dynamic load balancing techniques for vision systems are presented. These techniques are novel in the sense that they capture the computational requirements of a task by examining the data when it is produced. Furthermore, they can be applied to many vision systems because many algorithms in different systems are either the same, or have similar computational characteristics. These techniques are evaluated by applying them on a parallel implementation of the algorithms in a motion estimation system on a hypercube multiprocessor system. The motion estimation system consists of the following steps: (1) extraction of features; (2) stereo match of images in one time instant; (3) time match of images from different time instants; (4) stereo match to compute final unambiguous points; and (5) computation of motion parameters. It is shown that the performance gains when these data decomposition and load balancing techniques are used are significant and the overhead of using these techniques is minimal.

Choudhary, Alok Nidhi↗

Parallel processing of real-time dynamic systems simulation on OSCAR (Optimally SCheduled Advanced multiprocessoR)

Parallel processing of real-time dynamic systems simulation on a multiprocessor system named OSCAR is presented. In the simulation of dynamic systems, generally, the same calculation are repeated every time step. However, we cannot apply to Do-all or the Do-across techniques for parallel processing of the simulation since there exist data dependencies from the end of an iteration to the beginning of the next iteration and furthermore data-input and data-output are required every sampling time period. Therefore, parallelism inside the calculation required for a single time step, or a large basic block which consists of arithmetic assignment statements, must be used. In the proposed method, near fine grain tasks, each of which consists of one or more floating point operations, are generated to extract the parallelism from the calculation and assigned to processors by using optimal static scheduling at compile time in order to reduce large run time overhead caused by the use of near fine grain tasks. The practicality of the scheme is demonstrated on OSCAR (Optimally SCheduled Advanced multiprocessoR) which has been developed to extract advantageous features of static scheduling algorithms to the maximum extent.

Kasahara, Hironori↗

Health management system for rocket engines

The functional framework of a failure detection algorithm for the Space Shuttle Main Engine (SSME) is developed. The basic algorithm is based only on existing SSME measurements. Supplemental measurements, expected to enhance failure detection effectiveness, are identified. To support the algorithm development, a figure of merit is defined to estimate the likelihood of SSME criticality 1 failure modes and the failure modes are ranked in order of likelihood of occurrence. Nine classes of failure detection strategies are evaluated and promising features are extracted as the basis for the failure detection algorithm. The failure detection algorithm provides early warning capabilities for a wide variety of SSME failure modes. Preliminary algorithm evaluation, using data from three SSME failures representing three different failure types, demonstrated indications of imminent catastrophic failure well in advance of redline cutoff in all three cases.

Nemeth, Edward↗

The change in critical technologies for computational physics

It is noted that the types of technology required for computational physics are changing as the field matures. Emphasis has shifted from computer technology to algorithm technology and, finally, to visual analysis technology as areas of critical research for this field. High-performance graphical workstations tied to a supercommunicator with high-speed communications along with the development of especially tailored visualization software has enabled analysis of highly complex fluid-dynamics simulations. Particular reference is made here to the development of visual analysis tools at NASA's Numerical Aerodynamics Simulation Facility. The next technology which this field requires is one that would eliminate visual clutter by extracting key features of simulations of physics and technology in order to create displays that clearly portray these key features. Research in the tuning of visual displays to human cognitive abilities is proposed. The immediate transfer of technology to all levels of computers, specifically the inclusion of visualization primitives in basic software developments for all work stations and PCs, is recommended.

Watson, Val↗

Tropical Pacific moisture variability

The objectives are to describe synoptic scale variability of moisture over the tropical Pacific Ocean and the systems leading to this variability; implement satellite analysis procedures in support of this effort, and to incorporate additional satellite information into operational analysis forecast systems at the National Meteorological Center (NMC). Composite satellite radiance patterns describe features detectable well before the development of synoptic scale tropical plumes. These typical features were extracted from historical files of Tiros Operational Vertical Sounder (TOVS) radiance observations for a pair of tropical plumes which developed during January 1989. Signals were inserted into the NMC operational medium range forecast model and a suite of model integrations were conducted. Many of the 48 h model errors of the historical forecasts were eliminated by the inclusion of more complete satellite observations. Three studies in satellite radiance analysis progressed. An analysis which blended TOVS moisture channels, OLR observations and European Center for Medium Weather Forecasts (ECMWF) model analysis to generate fields of total precipitable water comparable to those estimated from Scanning Multichannel Microwave Radiometer (SMMR) mu-wave observations. This study demonstrated that a 10 y climatology of precipitable water over the oceans is feasible, using available infrared observations (OLR and TOVS) and model analysis (ECMWF, NMC or similar quality). The estimates are sensitive to model quality and the estimating model must be updated with operational model changes. Coe developed a set of tropical plume and ITCZ composites from TOVS observations, and from NMC and ECMWF analyses which had been passed through a radiative transfer model to simulate TOVS radiances. The composites have been completed as well as many statistical diagnostics of individual TOVS channels. Analysis of the computations is commencing. Chung has initiated a study of the differences between TOVS observed vapor structure during El Nino Southern Oscillation (ENSO) (1983) and non-ENSO (1984) years. Preliminary diagnosis demonstrates gross moisture changes between warm and cold sea surface temperature episodes.

Mcguirk, James P.↗

Pattern classifier for health monitoring of helicopter gearboxes

The application of a newly developed diagnostic method to a helicopter gearbox is demonstrated. This method is a pattern classifier which uses a multi-valued influence matrix (MVIM) as its diagnostic model. The method benefits from a fast learning algorithm, based on error feedback, that enables it to estimate gearbox health from a small set of measurement-fault data. The MVIM method can also assess the diagnosability of the system and variability of the fault signatures as the basis to improve fault signatures. This method was tested on vibration signals reflecting various faults in an OH-58A main rotor transmission gearbox. The vibration signals were then digitized and processed by a vibration signal analyzer to enhance and extract various features of the vibration data. The parameters obtained from this analyzer were utilized to train and test the performance of the MVIM method in both detection and diagnosis. The results indicate that the MVIM method provided excellent detection results when the full range of faults effects on the measurements were included in training, and it had a correct diagnostic rate of 95 percent when the faults were included in training.

Chin, Hsinyung↗

Image segmentation using fuzzy LVQ clustering networks

In this note we formulate image segmentation as a clustering problem. Feature vectors extracted from a raw image are clustered into subregions, thereby segmenting the image. A fuzzy generalization of a Kohonen learning vector quantization (LVQ) which integrates the Fuzzy c-Means (FCM) model with the learning rate and updating strategies of the LVQ is used for this task. This network, which segments images in an unsupervised manner, is thus related to the FCM optimization problem. Numerical examples on photographic and magnetic resonance images are given to illustrate this approach to image segmentation.

Tsao, Eric Chen-Kuo↗

The use of expert systems in combination with active and passive microwave data to classify sea ice

The authors report on a system for sea ice classification which combines passive and active microwave data with algorithmic and heuristic classification techniques in order to classify sea ice unambiguously. They describe initial algorithmic classification, extraction of features and symbolic information, the application of data-dependent expert systems, and the establishment of feature correspondence between data sets.

Haverkamp, Donna↗

Back Propagation Neural Networks for Predicting Ultimate Strengths of Unidirectional Graphite/Epoxy Tensile Specimens

The research presented herein demonstrates the feasibility of predicting ultimate strengths in simple composite structures through a neural network analysis of their acoustic emission (AE) amplitude distribution data. A series of eleven ASTM D-3039 unidirectional graphite/epoxy tensile samples were loaded to failure to generate the amplitude distributions for this analysis. A back propagation neural network was trained to correlate the AE amplitude distribution signatures generated during the first 25% of loading with the ultimate strengths of the samples. The network was trained using two sets of inputs: (1) the statistical parameters obtained from a Weibull distribution fit of the amplitude distribution data, and (2) the event frequency (amplitude) distribution itself. The neural networks were able to predict ultimate strengths with a worst case error of -8.99% for the Weibull modeled amplitude distribution data and 3.74% when the amplitude distribution itself was used to train the network. The principal reason for the improved prediction capability of the latter technique lies in the ability of the neural network to extract subtle features from within the amplitude distribution.

Walker, James L.↗

Extraction of Dry Leaf Spectral Features from Reflectance Spectra of Green Vegetation

Reflectance spectra of green vegetation in the 1.4-2.5 micrometer region are dominated by liquid water absorptions. In this article, we describe the analysis of a set of reflectance spectra of green vegetation, dry vegetation, and liquid water measured in a laboratory using a nonlinear least squares spectral matching technique. We conclude that both the liquid water and the dry materials contribute to the reflectance spectra of green vegetation in the 1.0-2.5 micrometer region. Our matching of data acquired with the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) over two vegetated areas in Oregon Transect with a pure water spectrum also shows a residual absorption feature near 1.72 micrometers.

Gao, Bo-Cai↗

Simultaneous Sensor and Process Fault Diagnostics for Propellant Feed System

The main objective of this research is to extract fault features from sensor faults and process faults by using advanced fault detection and isolation (FDI) algorithms. A tank system that has some common characteristics to a NASA testbed at Stennis Space Center was used to verify our proposed algorithms. First, a generic tank system was modeled. Second, a mathematical model suitable for FDI has been derived for the tank system. Third, a new and general FDI procedure has been designed to distinguish process faults and sensor faults. Extensive simulations clearly demonstrated the advantages of the new design.

Cao, J.↗

Detection of Digital Elevation Model Errors Using X-band Weather Radar

Flight in Instrument Meteorological Conditions requires pilots to manipulate flight controls while referring to a Primary Flight Display. The Primary Flight Display indicates aircraft attitude along with, in some cases, many other state variables such as altitude, speed, and guidance cues. Synthetic Vision Systems have been proposed that overlay the traditional information provided on Primary Flight Displays onto a scene depicting the location of terrain and other geo-spatial features.Terrain models used by these displays must have sufficient quality to avoid providing misleading information. This paper describes how X-band radar measurements can be used as part of a monitor, and/or maintenance system, to quantify the integrity of terrain models that are used by systems such as Synthetic Vision. Terrain shadowing effects, as seen by the radar, are compared in a statistical manner against estimated shadow feature elements extracted from the stored terrain model from the perspective of the airborne observer. A test statistic is defined that enables detection of errors as small as the range resolution of the radar. Experimental results obtained from two aircraft platforms hosting certified commercial-off-the-shelf X-band radars test the premise and illustrate its potential.

Young, Steven D.↗

Method of Real-Time Principal-Component Analysis

Dominant-element-based gradient descent and dynamic initial learning rate (DOGEDYN) is a method of sequential principal-component analysis (PCA) that is well suited for such applications as data compression and extraction of features from sets of data. In comparison with a prior method of gradient-descent-based sequential PCA, this method offers a greater rate of learning convergence. Like the prior method, DOGEDYN can be implemented in software. However, the main advantage of DOGEDYN over the prior method lies in the facts that it requires less computation and can be implemented in simpler hardware. It should be possible to implement DOGEDYN in compact, low-power, very-large-scale integrated (VLSI) circuitry that could process data in real time.

Duong, Tuan↗

Implementation of Pin Point Landing Vision Components in an FPGA System

Pin-point landing is required to enable missions to land close, typically within 10 meters, to scientifically important targets in generally hazardous terrain. In Pin Point Landing both high accuracy and high speed estimation of position and orientation is needed to provide input to the control system to safely choose and navigate to a safe landing site. A proposed algorithm called VISion aided Inertial NAVigation (VISINAV) has shown that the accuracy requirements can be met. [2][3] VISINAV was shown in software only, and was expected to use FPGA enhancements in the future to improve the computational speed needed for pin point landing during Entry Descent and Landing (EDL). Homography, feature detection and spatial correlation are computationally intensive parts of VISINAV. Homography aligns the map image with the descent image so that small correlation windows can be used, and feature detection provides regions that spatial correlation can track from frame to frame in order to estimate vehicle motion. On MER the image Homography, Feature Detection and Correlation would take approximately 650ms tracking 75 features between frames. We implemented Homography, Feature detection and Correlation on a Virtex 4 LX160 FPGA to run in under 25ms while tracking 500 features to improve algorithm reliability and throughput.

aircraft landing guidance↗

Sampling and Analysis of Impact Crater Residues Found on the Wide Field Planetary Camera-2 Radiator

After nearly 16 years in low Earth orbit (LEO), the Wide Field Planetary Camera-2 (WFPC2) was recovered from the Hubble Space Telescope (HST) in May 2009, during the 12 day shuttle mission designated STS-125. The WFPC-2 radiator had been struck by approximately 700 impactors producing crater features 300 microns and larger in size. Following optical inspection in 2009, agreement was reached for joint NASA-ESA study of crater residues, in 2011. Over 480 impact features were extracted at NASA Johnson Space Center's (JSC) Space Exposed Hardware clean-room and curation facility during 2012, and were shared between NASA and ESA. We describe analyses conducted using scanning electron microscopy (SEM) - energy dispersive X-ray spectrometry (EDX): by NASA at JSC's Astromaterials Research and Exploration Science (ARES) Division; and for ESA at the Natural History Museum (NHM), with Ion beam analysis (IBA) using a scanned proton microbeam at the University of Surrey Ion Beam Centre (IBC).

Kearsley, A. T.↗