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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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Multiple directed graph large-class multi-spectral processor

Numerical analysis techniques for the interpretation of high-resolution imaging-spectrometer data are described and demonstrated. The method proposed involves the use of (1) a hierarchical classifier with a tree structure generated automatically by a Fisher linear-discriminant-function algorithm and (2) a novel multiple-directed-graph scheme which reduces the local maxima and the number of perturbations required. Results for a 500-class test problem involving simulated imaging-spectrometer data are presented in tables and graphs; 100-percent-correct classification is achieved with an improvement factor of 5.

Casasent, David↗

Turbulent magnetic reconnection

The results of two-dimensional spectral-method MHD simulations of the effect of turbulence on magnetic-reconnection processes are presented in extensive graphs and tables and characterized in detail. In a periodic sheet-pinch configuration, early-onset, persistent turbulence is found to occur when a low level of broadband fluctuations is introduced into the initial data. Features observed include small-scale unsteady coherent electric-current and vorticity structures, enhanced viscous and resistive dissipation, unsteady and spatially asymmetric fluid flow, large-scale and small-scale magnetic islands, multiple X points, large-amplitude electric-field fluctuations, and spectral characteristics indicating that the turbulence is broadband in both spatial directions and similar to homogeneous MHD turbulence. The importance of reconnection for studies of solar, magnetospheric, and laboratory plasmas in inhomogeneous magnetic fields is indicated.

Matthaeus, W. H.↗

Recent Advances in Registration, Integration and Fusion of Remotely Sensed Data: Redundant Representations and Frames

In recent years, sophisticated mathematical techniques have been successfully applied to the field of remote sensing to produce significant advances in applications such as registration, integration and fusion of remotely sensed data. Registration, integration and fusion of multiple source imagery are the most important issues when dealing with Earth Science remote sensing data where information from multiple sensors, exhibiting various resolutions, must be integrated. Issues ranging from different sensor geometries, different spectral responses, differing illumination conditions, different seasons, and various amounts of noise need to be dealt with when designing an image registration, integration or fusion method. This tutorial will first define the problems and challenges associated with these applications and then will review some mathematical techniques that have been successfully utilized to solve them. In particular, we will cover topics on geometric multiscale representations, redundant representations and fusion frames, graph operators, diffusion wavelets, as well as spatial-spectral and operator-based data fusion. All the algorithms will be illustrated using remotely sensed data, with an emphasis on current and operational instruments.

Fusion↗

The role of spatial, spectral and radiometric resolution on information content

The results of a factorial experiment to evaluate the effects of spatial, spectral, and radiometric resolution on training-data spectral separability and classification accuracy are reported. Aircraft scanner data from five flightlines at 19.8 km over California including croplands, rangeland, forest, water, and urban areas were systematically degraded over a range approximately from Landsat MSS to Thematic Mapper specifications. Reference data were collected on the ground and from aerial photography. The degradations, training-site delineation, data-analysis procedures, and accuracy-assessment techniques are described; the results are presented in tables and graphs and discussed. It is found that while accuracy was increased by higher spectral resolution in 70 percent of the cases and uniformly by increased radiometric resolution, it was decreased by higher spatial resolution. This phenomenon is attributed to classification methods.

Buis, J. S.↗

A spectral multi-domain technique applied to stability and transition of incompressible and compressible flows

Techniques for the numerical simulation of compressible and incompressible viscous flows are described and demonstrated. The focus is on a multidomain spectral method based on the flux-balance domain-interface scheme of Macaraeg and Streett (1986). The fundamental principles of the method are reviewed, and it is shown that the multidomain spectral approach facilitates the treatment of instability and the transition to turbulence. Typical numerical results for the Taylor-Couette problem and for bounded compressible high-speed mixing layers are presented in graphs and briefly characterized.

Macaraeg, Michele↗

HARP: A Dynamic Inertial Spectral Partitioner

Partitioning unstructured graphs is central to the parallel solution of computational science and engineering problems. Spectral partitioners, such recursive spectral bisection (RSB), have proven effecfive in generating high-quality partitions of realistically-sized meshes. The major problem which hindered their wide-spread use was their long execution times. This paper presents a new inertial spectral partitioner, called HARP. The main objective of the proposed approach is to quickly partition the meshes at runtime in a manner that works efficiently for real applications in the context of distributed-memory machines. The underlying principle of HARP is to find the eigenvectors of the unpartitioned vertices and then project them onto the eigerivectors of the original mesh. Results for various meshes ranging in size from 1000 to 100,000 vertices indicate that HARP can indeed partition meshes rapidly at runtime. Experimental results show that our largest mesh can be partitioned sequentially in only a few seconds on an SP2 which is several times faster than other spectral partitioners while maintaining the solution quality of the proven RSB method. A parallel WI version of HARP has also been implemented on IBM SP2 and Cray T3E. Parallel HARP, running on 64 processors SP2 and T3E, can partition a mesh containing more than 100,000 vertices into 64 subgrids in about half a second. These results indicate that graph partitioning can now be truly embedded in dynamically-changing real-world applications.

Simon, Horst D.↗

Thematic Conference on Remote Sensing for Exploration Geology - Methods, Integration, Solutions, 7th, Calgary, Canada, Oct. 2-6, 1989, Proceedings. Volumes 1 & 2

Recent advances in airborne and satellite remote-sensing technology for application to geological exploration are discussed in reviews and reports. Sections are devoted to basement tectonics and their surface expressions, spectral geology, hydrocarbon exploration applications, radar applications and future systems, engineering and environment issues, geobotanical remote sensing, advanced image processing, data integration and mapping, and mineral exploration. Extensive diagrams, graphs, and sample images are provided.

Source record↗

Metric Learning for Hyperspectral Image Segmentation

We present a metric learning approach to improve the performance of unsupervised hyperspectral image segmentation. Unsupervised spatial segmentation can assist both user visualization and automatic recognition of surface features. Analysts can use spatially-continuous segments to decrease noise levels and/or localize feature boundaries. However, existing segmentation methods use tasks-agnostic measures of similarity. Here we learn task-specific similarity measures from training data, improving segment fidelity to classes of interest. Multiclass Linear Discriminate Analysis produces a linear transform that optimally separates a labeled set of training classes. The defines a distance metric that generalized to a new scenes, enabling graph-based segmentation that emphasizes key spectral features. We describe tests based on data from the Compact Reconnaissance Imaging Spectrometer (CRISM) in which learned metrics improve segment homogeneity with respect to mineralogical classes.

Compact Reconnaissance Imaging Spectrometer (CRISM↗

Space Station Freedom Disturbance Simulation and Management Tool

The design and functions of the Disturbance Simulation and Management Tool, (DMST), a software package developed to evaluate the effects of design changes and disturbance inputs on the Space Station dynamic environment, are described. DMST is a menu-driven interactive package, written in the PRO-MATLAB, which incorporates methods such as FEM model reduction, mode synthesis, and discrete-time numerical simulation. Particular attention is given to the main-menu options, including building a payload and payload-pointing-system (PPS) configuration, selecting disturbance inputs, running PPS and lab-module microgravity-environment (MGE) simulations, calculating limits to meet PPS and MGE requirements, and performing MGE spectral analyses using power-spectral density or shock spectra. Typical numerical results are presented in graphs.

Lisman, Sima S.↗

Power spectral estimation algorithms

Algorithms to estimate the power spectrum using Maximum Entropy Methods were developed. These algorithms were coded in FORTRAN 77 and were implemented on the VAX 780. The important considerations in this analysis are: (1) resolution, i.e., how close in frequency two spectral components can be spaced and still be identified; (2) dynamic range, i.e., how small a spectral peak can be, relative to the largest, and still be observed in the spectra; and (3) variance, i.e., how accurate the estimate of the spectra is to the actual spectra. The application of the algorithms based on Maximum Entropy Methods to a variety of data shows that these criteria are met quite well. Additional work in this direction would help confirm the findings. All of the software developed was turned over to the technical monitor. A copy of a typical program is included. Some of the actual data and graphs used on this data are also included.

Bhatia, Manjit S.↗

Information content in spectral calculations

Analytical procedures for extracting piecewise smooth solutions of hyperbolic systems from raw oscillatory data obtained by pseudospectral methods are developed. The validity of the approach is demonstrated for the case of linear problems with constant coefficients, and plausibility arguments are presented which indicate its applicability to nonlinear operators when the steady state has been achieved. Numerical results for the development of an oblique shock when a wedge is inserted at zero angle of attack into a uniform supersonic flow of an ideal gas (the time-dependent two-dimensional Euler equations discretized in space by the pseudospectral Chebyshev method) are presented in tables and graphs.

Abarbanel, S.↗

Partitioning of unstructured problems for parallel processing

Many large-scale computational problems are based on unstructured computational domains. Primary examples are unstructured grid calculations based on finite volume methods in computational fluid dynamics, or structural analysis problems based on finite element approximations. The question of how to distribute such unstructured computational domains over a large number of processors in a MIMD machine with distributed memory is addressed. A graph theoretical framework for these problems is established. Based on this framework three decomposition algorithms are introduced. In particular a new decomposition algorithm is discussed, which is based on the computation of an eigenvector of the Laplacian matrix associated with the graph. Numerical comparisons on large-scale two- and three-dimensional problems demonstrate the superiority of the new spectral bisection algorithm.

Simon, H. D.↗

Superpixel-Augmented Endmember Detection for Hyperspectral Images

Superpixels are homogeneous image regions comprised of several contiguous pixels. They are produced by shattering the image into contiguous, homogeneous regions that each cover between 20 and 100 image pixels. The segmentation aims for a many-to-one mapping from superpixels to image features; each image feature could contain several superpixels, but each superpixel occupies no more than one image feature. This conservative segmentation is relatively easy to automate in a robust fashion. Superpixel processing is related to the more general idea of improving hyperspectral analysis through spatial constraints, which can recognize subtle features at or below the level of noise by exploiting the fact that their spectral signatures are found in neighboring pixels. Recent work has explored spatial constraints for endmember extraction, showing significant advantages over techniques that ignore pixels relative positions. Methods such as AMEE (automated morphological endmember extraction) express spatial influence using fixed isometric relationships a local square window or Euclidean distance in pixel coordinates. In other words, two pixels covariances are based on their spatial proximity, but are independent of their absolute location in the scene. These isometric spatial constraints are most appropriate when spectral variation is smooth and constant over the image. Superpixels are simple to implement, efficient to compute, and are empirically effective. They can be used as a preprocessing step with any desired endmember extraction technique. Superpixels also have a solid theoretical basis in the hyperspectral linear mixing model, making them a principled approach for improving endmember extraction. Unlike existing approaches, superpixels can accommodate non-isometric covariance between image pixels (characteristic of discrete image features separated by step discontinuities). These kinds of image features are common in natural scenes. Analysts can substitute superpixels for image pixels during endmember analysis that leverages the spatial contiguity of scene features to enhance subtle spectral features. Superpixels define populations of image pixels that are independent samples from each image feature, permitting robust estimation of spectral properties, and reducing measurement noise in proportion to the area of the superpixel. This permits improved endmember extraction, and enables automated search for novel and constituent minerals in very noisy, hyperspatial images. This innovation begins with a graph-based segmentation based on the work of Felzenszwalb et al., but then expands their approach to the hyperspectral image domain with a Euclidean distance metric. Then, the mean spectrum of each segment is computed, and the resulting data cloud is used as input into sequential maximum angle convex cone (SMACC) endmember extraction.

Thompson, David R.↗