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At least 217 records · Page 12

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NASA NTRS1972

Layered 'recognition cone' networks that pre-process, classify, and describe.

Discussion of pattern recognition programs for input data preprocessing with simultaneous or subsequent characterization, or characterization into a 'recognition cone,' or description and naming, interrelated descriptions, and conversion. A computer program is described that transforms and characterizes the input through the successive layers of a recognition cone. The program can choose and put forth names of parts of the input scene. It combines pieces of a description into interrelated wholes by using n-tuple characterizers and conducts a simple and stylized conversation about what it has seen. The technique of combining recognition cones with preprocessing transformations and characterizations is expected to contribute to technology in this field.

Uhr, L.↗

NASA NTRS1971

Automatic Computer Mapping of Terrain

Computer processing of 17 wavelength bands of visible, reflective infrared, and thermal infrared scanner spectrometer data, and of three wavelength bands derived from color aerial film has resulted in successful automatic computer mapping of eight or more terrain classes in a Yellowstone National Park test site. The tests involved: (1) supervised and non-supervised computer programs; (2) special preprocessing of the scanner data to reduce computer processing time and cost, and improve the accuracy; and (3) studies of the effectiveness of the proposed Earth Resources Technology Satellite (ERTS) data channels in the automatic mapping of the same terrain, based on simulations, using the same set of scanner data. The following terrain classes have been mapped with greater than 80 percent accuracy in a 12-square-mile area with 1,800 feet of relief; (1) bedrock exposures, (2) vegetated rock rubble, (3) talus, (4) glacial kame meadow, (5) glacial till meadow, (6) forest, (7) bog, and (8) water. In addition, shadows of clouds and cliffs are depicted, but were greatly reduced by using preprocessing techniques.

Smedes, H. W.↗

NASA NTRS1973

Signature extension techniques applied to multispectral scanner data.

Review of a number of spectral radiance signature extension techniques based on the concept of preprocessing the data to reduce the effects due to atmospheric effects, scanner look angle, etc. One of the promising methods studied to date involves using a ratio preprocessing transformation wherein the signals generated in adjacent spectral bands are ratioed on a point-by-point basis prior to classification. This method is easily and efficiently implemented and tests to date have yielded excellent results. Signatures have been successfully extended over 100+ miles, four days, different times of day, and very different atmospheric conditions.

Nalepka, R. F.↗

NASA NTRS1973

Constrained optimization of image restoration filters.

A preprocessing method to correct for image degradation is proposed which can be thought of as a generalization and extension of previous work by Smith (1966) and Stuller (1972). This method accomodates the problem of noncircularly symmetric imaging system point-spread functions, provides for controlled extent of the preprocessing filter to minimize distortion due to transients resulting from truncation errors and edge effects, can be used with various kinds of system noise, and can be readily extended to provide constraint of other system parameters. The analysis relates to a line-scanner system, although it is applicable in principle to many other system configurations.

Riemer, T. E.↗

NASA NTRS1973

Machine processing methods for earth observational data

A brief review of the development over the last decade of earth resource information systems is presented. Machine data preprocessing and analysis methods are surveyed and illustrated. These include preprocessing steps intended to modify geometric and radiometric aspects of earth observational image data to enhance the ability of either human interpreters or machine algorithms to extract information from the data. Illustrations of processed and analyzed images from spaceborne sensors including the Earth Resources Technology Satellite are discussed.

Landgrebe, D. A.↗

NASA NTRS1976

User data dissemination concepts for earth resources: Executive summary

The impact of the future capabilities of earth-resources data sensors (both satellite and airborne) and their requirements on the data dissemination network were investigated and optimum ways of configuring this network were determined. The scope of this study was limited to the continental U.S.A. (including Alaska) and to the 1985-1995 time period. Some of the conclusions and recommendations reached were: (1) Data from satellites in sun-synchronous polar orbits (700-920 km) will generate most of the earth-resources data in the specified time period. (2) Data from aircraft and shuttle sorties cannot be readily integrated in a data-dissemination network unless already preprocessed in a digitized form to a standard geometric coordinate system. (3) Data transmission between readout stations and central preprocessing facilities, and between processing facilities and user facilities are most economically performed by domestic communication satellites. (4) The effect of the following factors should be studied: cloud cover, expanded coverage, pricing strategies, multidiscipline missions.

Davies, R.↗

NASA NTRS1976

User data dissemination concepts for earth resources

Domestic data dissemination networks for earth-resources data in the 1985-1995 time frame were evaluated. The following topics were addressed: (1) earth-resources data sources and expected data volumes, (2) future user demand in terms of data volume and timeliness, (3) space-to-space and earth point-to-point transmission link requirements and implementation, (4) preprocessing requirements and implementation, (5) network costs, and (6) technological development to support this implementation. This study was parametric in that the data input (supply) was varied by a factor of about fifteen while the user request (demand) was varied by a factor of about nineteen. Correspondingly, the time from observation to delivery to the user was varied. This parametric evaluation was performed by a computer simulation that was based on network alternatives and resulted in preliminary transmission and preprocessing requirements. The earth-resource data sources considered were: shuttle sorties, synchronous satellites (e.g., SEOS), aircraft, and satellites in polar orbits.

Davies, R.↗

NASA NTRS1977

Altimeter waveform software design

Techniques are described for preprocessing raw return waveform data from the GEOS-3 radar altimeter. Topics discussed include: (1) general altimeter data preprocessing to be done at the GEOS-3 Data Processing Center to correct altimeter waveform data for temperature calibrations, to convert between engineering and final data units and to convert telemetered parameter quantities to more appropriate final data distribution values: (2) time "tagging" of altimeter return waveform data quantities to compensate for various delays, misalignments and calculational intervals; (3) data processing procedures for use in estimating spacecraft attitude from altimeter waveform sampling gates; and (4) feasibility of use of a ground-based reflector or transponder to obtain in-flight calibration information on GEOS-3 altimeter performance.

Hayne, G. S.↗

NASA NTRS1977

Cluster compression algorithm: A joint clustering/data compression concept

The Cluster Compression Algorithm (CCA), which was developed to reduce costs associated with transmitting, storing, distributing, and interpreting LANDSAT multispectral image data is described. The CCA is a preprocessing algorithm that uses feature extraction and data compression to more efficiently represent the information in the image data. The format of the preprocessed data enables simply a look-up table decoding and direct use of the extracted features to reduce user computation for either image reconstruction, or computer interpretation of the image data. Basically, the CCA uses spatially local clustering to extract features from the image data to describe spectral characteristics of the data set. In addition, the features may be used to form a sequence of scalar numbers that define each picture element in terms of the cluster features. This sequence, called the feature map, is then efficiently represented by using source encoding concepts. Various forms of the CCA are defined and experimental results are presented to show trade-offs and characteristics of the various implementations. Examples are provided that demonstrate the application of the cluster compression concept to multi-spectral images from LANDSAT and other sources.

Hilbert, E. E.↗

NASA NTRS1978

New languages for numerical software

Existing languages for numerical software are not altogether satisfactory. FORTRAN, even preprocessed, has troublesome limitations. Unfortunately, proposed replacements are discouragingly large, or omit essential features like variably dimensioned arrays and FORTRAN capability. A new language was designed to include such crucial features, but otherwise be as small as possible. This language, called T, includes: indention to indicate block structure, novel loop syntax, and engineering format for real constants. By preprocessing into PL/1, implementation cost was kept low.

Grosse, E.↗

NASA NTRS1979

Nonterrestrial material processing and manufacturing of large space systems

Nonterrestrial processing of materials and manufacturing of large space system components from preprocessed lunar materials at a manufacturing site in space is described. Lunar materials mined and preprocessed at the lunar resource complex will be flown to the space manufacturing facility (SMF), where together with supplementary terrestrial materials, they will be final processed and fabricated into space communication systems, solar cell blankets, radio frequency generators, and electrical equipment. Satellite Power System (SPS) material requirements and lunar material availability and utilization are detailed, and the SMF processing, refining, fabricating facilities, material flow and manpower requirements are described.

Von Tiesenhausen, G.↗

NASA NTRS1980

NEEDS - Information Adaptive System

The Information Adaptive System (IAS) is an element of the NASA End-to-End Data System (NEEDS) Phase II and is focused toward onboard image processing. The IAS is a data preprocessing system which is closely coupled to the sensor system. Some of the functions planned for the IAS include sensor response nonuniformity correction, geometric correction, data set selection, data formatting, packetization, and adaptive system control. The inclusion of these sensor data preprocessing functions onboard the spacecraft will significantly improve the extraction of information from the sensor data in a timely and cost effective manner, and provide the opportunity to design sensor systems which can be reconfigured in near real-time for optimum performance. The purpose of this paper is to present the preliminary design of the IAS and the plans for its development.

Kelly, W. L.↗

NASA NTRS1980

NASA End-to-End Data System /NEEDS/ information adaptive system - Performing image processing onboard the spacecraft

The Information Adaptive System (IAS) is an element of the NASA End-to-End Data System (NEEDS) Phase II and is focused toward onbaord image processing. Since the IAS is a data preprocessing system which is closely coupled to the sensor system, it serves as a first step in providing a 'Smart' imaging sensor. Some of the functions planned for the IAS include sensor response nonuniformity correction, geometric correction, data set selection, data formatting, packetization, and adaptive system control. The inclusion of these sensor data preprocessing functions onboard the spacecraft will significantly improve the extraction of information from the sensor data in a timely and cost effective manner and provide the opportunity to design sensor systems which can be reconfigured in near real time for optimum performance. The purpose of this paper is to present the preliminary design of the IAS and the plans for its development.

Kelly, W. L.↗

NASA NTRS1982

Investigating tectonic and bathymetric features of the Indian Ocean using MAGSAT magnetic anomaly data

MAGSAT Investigator-B tapes were preprocessed by (1) removing all data points with obvious erroneous values and location errors; (2) removing smaller spikes (typically 15 nT or more), and deleting data tracks with fewer than 20 points; and (3) removing a linear trend from each track. The remaining data were recorded on tape for use by the equivalent source mapping (ESMAP) program which uses a least squares algorithm to fit the magnetization parameter of the grid of equivalent source dipoles in the crust to satellite data acquired at different times and locations. ESMAP was implemented on the TASC computing system and modified to read preprocessed MAGSAT tapes and interface with TASC plotting software. Some verification of the software was accomplished. Gridded 1-degree mean values of gravity anomaly and sea surface undulation computed from SEASAT radar altimeter were obtained and brought on line.

Lazarewicz, A. R.↗

NASA NTRS1982

Evaluation of temporal registration of Landsat scenes

The registration of Landsat images is important for multitemporal classification and for detecting change. Landsat data are now rectified to a ground coordinate system during preprocessing, hence scenes obtained over the same area are registered. The machine responsible for preprocessing the Landsat multispectral scanner data is the master data processor (MDP). This paper describes the rectification approach taken by the MDP, reviews the accuracy standards of the resultant product, and provides an assessment of the accuracy of the scene to scene registration of two Landsat images.

Nelson, R.↗

NASA NTRS1981

Improved land use classification from Landsat and Seasat satellite imagery registered to a common map base

In the case of Landsat Multispectral Scanner System (MSS) data, ambiguities in spectral signature can arise in urban areas. A study was initiated in the belief that Seasat digital SAR could help provide the spectral separability needed for a more accurate urban land use classification. A description is presented of the results of land use classifications performed on Landsat and preprocessed Seasat imagery that were registered to a common map base. The process of registering imagery and training site boundary coordinates to a common map has been reported by Clark (1980). It is found that preprocessed Seasat imagery provides signatures for urban land uses which are spectrally separable from Landsat signatures. This development appears to significantly improve land use classifications in an urban setting for class 12 (Commercial and Services), class 13 (Industrial), and class 14 (Transportation, Communications, and Utilities).

Clark, J.↗

NASA NTRS1982

Radar image processing for rock-type discrimination

Image processing and enhancement techniques for improving the geologic utility of digital satellite radar images are reviewed. Preprocessing techniques such as mean and variance correction on a range or azimuth line by line basis to provide uniformly illuminated swaths, median value filtering for four-look imagery to eliminate speckle, and geometric rectification using a priori elevation data. Examples are presented of application of preprocessing methods to Seasat and Landsat data, and Seasat SAR imagery was coregistered with Landsat imagery to form composite scenes. A polynomial was developed to distort the radar picture to fit the Landsat image of a 90 x 90 km sq grid, using Landsat color ratios with Seasat intensities. Subsequent linear discrimination analysis was employed to discriminate rock types from known areas. Seasat additions to the Landsat data improved rock identification by 7%.

Blom, R. G.↗

NASA NTRS1981

Software for universal noiseless coding

An overview is provided of the universal noiseless coding algorithms as well as their relationship to the now available FORTRAN implementations. It is suggested that readers considering investigating the utility of these algorithms for actual applications should consult both NASA's Computer Software Management and Information Center (COSMIC) and descriptions of coding techniques provided by Rice (1979). Examples of applying these techniques have also been given by Rice (1975, 1979, 1980). Attention is given to reversible preprocessing, general implementation instructions, naming conventions, and calling arguments. A general applicability of the considered algorithms to solving practical problems is obtained because most real data sources can be simply transformed into the required form by appropriate preprocessing.

Rice, R. F.↗