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NASA NTRS1985

A star camera aspect system suitable for use in balloon experiments

A balloon-borne experiment containing a star camera aspect system was designed, built, and flown. This system was designed to provide offset corrections to the magnetometer and inclinometer readings used to control an azimuth and elevation pointed experiment. The camera is controlled by a microprocessor, including commendable exposure and noise rejection threshold, as well as formatting the data for telemetry to the ground. As a background program, the microprocessor runs the aspect program to analyze a fraction of the pictures taken so that aspect information and offset corrections are available to the experiment in near real time. The analysis consists of pattern recognition of the star field with a star catalog in ROM memory and a least squares calculation. The performance of this system in ground based tests is described. It is part of the NASA/GSFC High Energy Gamma-Ray Balloon Instrument (2).

Hunter, S. D.↗

NASA NTRS1983

Improving our understanding of the remote sensing process

Plans for two fundamental research programs aimed at improving an understanding of the physics and mathematics of remote sensing are discussed. The first program, Scene Radiation and Atmospheric Research Program, is concerned with developing the capability to determine biophysical attributes of terrestrial scenes through an improved understanding of the relationships between those properties and remotely sensed radiation. The research issues in the second program, Mathematical Pattern Recognition and Image Analysis, are discussed with reference to the following five categories: preprocessing, digital image representation, object scene inference, computational structures, and continuing studies.

Calabrese, M. A.↗

NASA NTRS1985

Synoptic cryosphere-atmosphere interactions in the Northern Hemisphere from DMSP image analysis

A climatology of Northern Hemisphere cyclonic cloud vortices is developed from high-resolution Defense Meteorological Satellite Program (DMSP) infrared imagery for mid-season months. The technique which is described involves pattern recognition using a detailed vortex classification system. Variations in hemispheric frequencies of successive vortex types are dominantly seasonal rather than latitudinal and imply a close association with surface (mainly cryosphere) variations. More extensive sea ice or snow cover in April and January is associated with increased cyclogenesis, indicating enhanced surface-atmosphere feedback. A significant relationship exists between cloud-vortex variations and the sea ice boundary, but not with the continental snowline.

Carleton, A. M.↗

NASA NTRS1983

Prediction of structures and magnetic orientations in solid alpha and beta-O2

A quasi-harmonic-lattice-dynamics method coupled with a pattern-recognition optimization scheme is used to determine the minimum energy structures and magnetic orientations of solid oxygen. It is shown that the magnetic interaction is responsible for the stability of alpha-O2 with respect to beta-O2 at zero temperature and pressure. The calculated alpha-O2 lattice parameters, magnetic orientations, and sublimation energy are in good agreement with experiment. Phonon dispersion curves are calculated at vector k not equal to zero and the acoustic sound velocities are determined. The rms translational and orientational fluctuations from equilibrium are also calculated. The beta-O2 phase is described by constraining the magnetic moments so that the magnetic Hamiltonian preserves the hexagonal symmetry of the crystal. The calculated lattice parameters are in good agreement with the experiments, and a three-sublattice, quasi-helical magnetic orientation is predicted from structural and energetic considerations.

Etters, R. D.↗

NASA NTRS1985

Characterization of coherent structures in a turbulent mixing layer by digital image analysis

Digital image analysis has been applied to a shadowgraph motion picture of a helium nitrogen mixing layer in order to characterize the coherent vortex structures in the flow. Both the primary spanwise coherent vortices and secondary streamwise vortices are considered. Pattern recognition algorithms were designed to take advantage of the more pronounced features of the vortices and of their temporal coherence to isolate them and to measure their characteristics. The resulting data base permits a deterministic description of the evolution of primary and seconary vortices.

Bernal, L. P.↗

NASA NTRS1986

Overview of the NASA SETI Program

The NASA Search of Extraterrestrial Intelligence (SETI) program plan is to scan the microwave window from 1 to 10 GHz with existing radio telescopes and sophisticated signal processing equipment looking for narrow band features that might represent artificial signals. A microwave spectrometer was built and is being field tested. A pattern recognition computer to search for drifting continuous wave signals and pulse trains in the output spectra is being designed. Equipment to characterize the radio frequency interference environment was also built. The plan is to complete the hardware and software by FY-88. Then, with increased funding, this equipment will be replicated in Very Large Scale Integration form. Observations, both a complete sky survey and a search fo nearby solar type stars, will begin in about 1990. The hypothesis that very powerful signals exist or that signals are being beamed at us will be tested. To detect the kinds of signals radiated at distances of 100 light years will require a collecting area kilometers in diameter.

Oliver, B. M.↗

NASA NTRS1984

A comparison of Landsat point and rectangular field training sets for land-use classification

Rectangular training fields of homogeneous spectroreflectance are commonly used in supervised pattern recognition efforts. Trial image classification with manually selected training sets gives irregular and misleading results due to statistical bias. A self-verifying, grid-sampled training point approach is proposed as a more statistically valid feature extraction technique. A systematic pixel sampling network of every ninth row and ninth column efficiently replaced the full image scene with smaller statistical vectors which preserved the necessary characteristics for classification. The composite second- and third-order average classification accuracy of 50.1 percent for 331,776 pixels in the full image substantially agreed with the 51 percent value predicted by the grid-sampled, 4,100-point training set.

Tom, C. H.↗

NASA NTRS1986

Noise in remote-sensing systems - The effect on classification error

Several types of noise in remote-sensing systems are treated. The purpose is to provide enhanced understanding of the relationship of noise sources to both analysis results and sensor design. The context of optical sensors and spectral pattern recognition analysis methods is used to enable tractability for quantitative results. First, the concept of multispectral classification is reviewed. Next, stochastic models are discussed for both signals and noise, including thermal, shot and quantization noise along with atmospheric effects. A model enabling the study of the combined effect of these sources is presented, and a system performance index is defined. Theoretical results showing the interrelated effects of the noise sources on system performance are given. Results of simulations using the system model are presented for several values of system parameters, using some noise parameters of the Thematic Mapper scanner as an illustration. Results show the relative importance of each of the noise sources on system performance, including how sensor noise interacts with atmospheric effects to degrade accuracy.

Landgrebe, D. A.↗

NASA NTRS1986

Regional-scale estimates of surface moisture availability and thermal inertia using remote thermal measurements

A review is presented of numerical models which were developed to interpret thermal IR data and to identify the governing parameters and surface energy fluxes recorded in the images. Analytic, predictive, diagnostic and empirical models are described. The limitations of each type of modeling approach are explored in terms of the error sources and inherent constraints due to theoretical or measurement limitations. Sample results of regional-scale soil moisture or evaporation patterns derived from the Heat Capacity Mapping Mission and GOES satellite data through application of the predictive model devised by Carlson (1981) are discussed. The analysis indicates that pattern recognition will probably be highest when data are collected over flat, arid, sparsely vegetated terrain. The soil moisture data then obtained may be accurate to within 10-20 percent.

Carlson, T. N.↗

NASA NTRS1986

Optical processing and Space Station automation

Optical information processing research aimed at Space Station automation applications is reviewed. The emphasis of the NASA Ames Research Center program is on intelligent optical pattern recognition and optical control processing. Attention is given to the primary functions of an overall scene understanding system: distortion-invariant optical feature generation, dimensionality reduction, object classification, and contextual information processing. A method of using synthetic discriminant functions to facilitate learning in a high-speed optical correlator is described. A discussion is presented of candidate analog and digital architectures for the optical implementation of state-estimation algorithms needed for the control of high-dimension dynamic systems. The multivariate system chosen for the optical control technology demonstration - a segmented, adaptive mirror and interferometrically based wavefront sensor - is also described.

Ennis, D. J.↗

NASA NTRS1986

Microcomputer-based programmable optical signal processor

A microcomputer-based real-time programmable optical signal processing system utilizing a magneto-optic spatial light modulator (MOSLM) and a liquid crystal light valve (LCLV) is described. This system can perform a myriad of complicated optical operations, such as image correlation, image subtraction, and matrix multiplication. Its important asserts are its programmability and the capability of real-time addressing. These are important for telerobotic vision in space automation applications. Design specifications and suggestions for practical implementation of the system are discussed. Some preliminary experimental demonstrations are conducted to demonstrate applications of the proposed system to image correlation for optical pattern recognition, image subtraction for lC chip inspection, and matrix multiplication for optical computing.

Yu, F. T. S.↗

NASA NTRS1986

Canopy reflectance modeling in a tropical wooded grassland

Geometric/optical canopy reflectance modeling and spatial/spectral pattern recognition are used to study the form and structure of savanna in West Africa. An invertible plant canopy reflectance model is tested for its ability to estimate the amount of woody vegetation cover in areas of sparsely wooded grassland from remotely sensed data. Dry woodlands and wooded grasslands, commonly referred to as savannas, are important ecologically and economically in Africa, and cover approximately forty percent of the continent by some estimates. The Sahelian and Sudanian savanna make up the important and sensitive transition zone between the tropical forests and the arid Saharan region. The depletion of woody cover, used for fodder and fuel in these regions, has become a very severe problem for the people living there. LANDSAT Thematic Mapper (TM) data is used to stratify woodland and wooded grassland into areas of relatively homogeneous canopy cover, and then by applying an invertible forest canopy reflectance model to estimate directly the height and spacing of the trees in the stands. Since height and spacing are proportional to biomass in some cases, a successful application of the segmentation/modeling techniques will allow direct estimation of woody biomass, as well as cover density, over significant areas of these valuable and sensitive ecosystems. Sahelian savanna sites in the Gourma area of Mali being used by the NASA/GIMMS project (Global Inventory Modeling and Monitoring System, at Goddard Space Flight Center), in conjunction with CIPEA/Mali (Centre International pour l'Elevage en Afrique) will be used for testing the canopy model. The model will also be tested in a Sudanian zone crop/woodland area in the Region of Segou, Mali.

Simonett, D.↗

NASA NTRS1986

Canopy reflectance modeling in a tropical wooded grassland

Geometric/optical canopy reflectance modeling and spatial/spectral pattern recognition is used to study the form and structure of savanna in West Africa. An invertible plant canopy reflectance model is tested for its ability to estimate the amount of woody vegetation from remotely sensed data in areas of sparsely wooded grassland. Dry woodlands and wooded grasslands, commonly referred to as savannas, are important ecologically and economically in Africa, and cover approximately forty percent of the continent by some estimates. The Sahel and Sudan savannas make up the important and sensitive transition zone between the tropical forests and the arid Sahara region. The depletion of woody cover, used for fodder and fuel in these regions, has become a very severe problem for the people living there. LANDSAT Thematic Mapper (TM) data is used to stratify woodland and wooded grassland into areas of relatively homogeneous canopy cover, and then an invertible forest canopy reflectance model is applied to estimate directly the height and spacing of the trees in the stands. Because height and spacing are proportional to biomass in some cases, a successful application of the segmentation/modeling techniques will allow direct estimation of tree biomass, as well as cover density, over significant areas of these valuable and sensitive ecosystems. The model being tested in sites in two different bioclimatic zones in Mali, West Africa, will be used for testing the canopy model. Sudanian zone crop/woodland test sites were located in the Region of Segou, Mali.

Simonett, David↗

NASA NTRS1987

Turbulence control on an airborne laser platform

An active flow control device to generate large-scale, periodic structures in a turbulent shear flow is developed. Together with adaptive optics, the device may be used on airborne laser platforms to reduce or eliminate optical distortion caused by the turbulence in the aircraft's boundary layer. A cyclic jet issuing from a spanwise slot is used to collect the turbulent boundary layer for a finite time and then release all of the flow instantaneously in one large eddy that convects downstream. Flow visualization and hot-film probe measurements are used together with pattern recognition algorithms to demonstrate the viability of the flow control method. A flat plate towed in a water channel is used as a test bed. The instantaneous velocity signal is used to compute important statistical quantities of the random velocity field, such as the mean, the root-mean-square, the spectral distribution, and the probability density function. When optimized for a given boundary layer, it is shown that the cyclic jet will produce periodic structures that are similar to the random, naturally occurring ones. These structures seem to trigger the onset of bursting events near the wall of the plate. Thus, the present device generates periodic structures in both the outer and inner regions of a turbulent boundary layer.

Gad-El-hak, Mohamed↗

NASA NTRS1986

Fuzzy automata and pattern matching

A wide-ranging search for articles and books concerned with fuzzy automata and syntactic pattern recognition is presented. A number of survey articles on image processing and feature detection were included. Hough's algorithm is presented to illustrate the way in which knowledge about an image can be used to interpret the details of the image. It was found that in hand generated pictures, the algorithm worked well on following the straight lines, but had great difficulty turning corners. An algorithm was developed which produces a minimal finite automaton recognizing a given finite set of strings. One difficulty of the construction is that, in some cases, this minimal automaton is not unique for a given set of strings and a given maximum length. This algorithm compares favorably with other inference algorithms. More importantly, the algorithm produces an automaton with a rigorously described relationship to the original set of strings that does not depend on the algorithm itself.

Setzer, C. B.↗

NASA NTRS1985

Vision requirements for Space Station applications

Problems which will be encountered by computer vision systems in Space Station operations are discussed, along with solutions be examined at Johnson Space Station. Lighting cannot be controlled in space, nor can the random presence of reflective surfaces. Task-oriented capabilities are to include docking to moving objects, identification of unexpected objects during autonomous flights to different orbits, and diagnoses of damage and repair requirements for autonomous Space Station inspection robots. The approaches being examined to provide these and other capabilities are television IR sensors, advanced pattern recognition programs feeding on data from laser probes, laser radar for robot eyesight and arrays of SMART sensors for automated location and tracking of target objects. Attention is also being given to liquid crystal light valves for optical processing of images for comparisons with on-board electronic libraries of images.

Crouse, K. R.↗

NASA NTRS1986

Intelligent information extraction from reflectance spectra Absorption band positions

A multiple high-order derivative analysis algorithm has been developed which can automatically extract absorption band positions from low-quality reflectance spectra with little degredation of accuracy. Overlapping bands with comparable widths and intensities can be resolved whose centers are as close as 0.3-0.5 W, with safer resolution limits of 0.6-1.0 W band center separations suggested for overlapping bands that are dissimilar. The segment length for smoothing is continually adjusted to about 0.5 W to minimize signal distortion, and a spectral pattern recognition algorithm predicts the signal spectrum and calculates approximate W across the spectrum using its second derivative. A single-pass cubic spline is applied to the smoothed data, and a sliding segment sixth-order polynomial is fit to the spectrum, with the length of the segment being continuously locally adjusted to 1.0 W across the spectrum. Good reliability and consistency of the algorithm is demonstrated with application to laboratory and earth-based telescope spectra.

Huguenin, R. L.↗

NASA NTRS1987

A drag reduction method for turbulent boundary layers

A novel method to reduce skin friction drag in a turbulent boundary layer is presented. The technique combines the beneficial effects of a longitudinally ribbed surface and suction. The streamwise grooves act as a nucleation site causing a focusing of low-speed streaks over the peaks. Suction is then applied intermittently through longitudinal slots located at selected locations along those peaks to obliterate the low-speed regions and to prevent bursting. During the first phase of the present research, selective suction from a single streamwise slot was used to eliminate either a single burst-like event or a periodic train of artificially generated bursts in laminar and turbulent boundary layers. The experiments were conducted using a flat plate towed in an 18-m water channel. Flow visualization and hot-film probe measurements were used together with pattern recognition algorithms to demonstrate the feasibility of the drag-reducing method.

Gad-El-hak, Mohamed↗