Search NASA⌕ Search

Engineering topics

Crane, R. B.

Publications and source records attributed to Crane, R. B..

11 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1975

Adaptive processing for LANDSAT data

Analytical and test results on the use of adaptive processing on LANDSAT data are presented. The Kalman filter was used as a framework to contain different adapting techniques. When LANDSAT MSS data were used all of the modifications made to the Kalman filter performed the functions for which they were designed. It was found that adaptive processing could provide compensation for incorrect signature means, within limits. However, if the data were such that poor classification accuracy would be obtained when the correct means were used, then adaptive processing would not improve the accuracy and might well lower it even further.

Crane, R. B.↗
NASA NTRS1973

Discrimination techniques employing both reflective and thermal multispectral signals

Recent improvements in remote sensor technology carry implications for data processing. Multispectral line scanners now exist that can collect data simultaneously and in registration in multiple channels at both reflective and thermal (emissive) wavelengths. Progress in dealing with two resultant recognition processing problems is discussed: (1) More channels mean higher processing costs; to combat these costs, a new and faster procedure for selecting subsets of channels has been developed. (2) Differences between thermal and reflective characteristics influence recognition processing; to illustrate the magnitude of these differences, some explanatory calculations are presented. Also introduced, is a different way to process multispectral scanner data, namely, radiation balance mapping and related procedures. Techniques and potentials are discussed and examples presented.

Malila, W. A.↗
NASA NTRS1973

A study of techniques for processing multispectral scanner data

A linear decision rule to reduce the time required for processing multispectral scanner data is developed. Test results are presented which justify the use of the new rule for digital processing whenever both accuracy and processing time are important. A method of evaluating the performance of the rule is also developed and applied to the problem of choosing a subset of channels. A technique used to find linear combinations of channels is described. The ability to extend signatures throughout a small area of approximately fifty square miles is tested. After preprocessing, signatures derived from the first of seven overlapping data sets are applied to all data sets. The test results show that the average probability of misclassification tends to increase with an increase in the number of data sets over which the signatures are extended.

Crane, R. B.↗
NASA NTRS1973

Feature extraction of multispectral data

A method is presented for feature extraction of multispectral scanner data. Non-training data is used to demonstrate the reduction in processing time that can be obtained by using feature extraction rather than feature selection.

Crane, R. B.↗
NASA NTRS1973

A Kalman filter approach to adaptive estimation of multispectral signatures

The signatures of remote sensing data from agricultural crops exhibit significant non-stationarity, so that the performance of fixed parameter classifiers degenerates with time and distance from the initial training data. A class of adaptive decision-directed classifiers are being developed, based on Kalman filter theory. Limited results to date on two data sets indicate approximately a 25 to 40% reduction in rates of misclassification.

Crane, R. B.↗
NASA NTRS1973

Signature estimation from satellite multispectral scanner data

A method for estimating signatures from satellite multispectral scanner data for areas containing mixtures of specified object classes is presented and evaluated. Each signature is assumed to be a Gaussian distribution. The estimation procedure is simple, and the estimates represent maximum likelihood estimates. Formulae to compute variances for an estimated signature are also given.

Crane, R. B.↗
NASA NTRS1972

Information extraction techniques for multispectral scanner data

The applicability of recognition-processing procedures for multispectral scanner data from areas and conditions used for programming the recognition computers to other data from different areas viewed under different measurement conditions was studied. The reflective spectral region approximately 0.3 to 3.0 micrometers is considered. A potential application of such techniques is in conducting area surveys. Work in three general areas is reported: (1) Nature of sources of systematic variation in multispectral scanner radiation signals, (2) An investigation of various techniques for overcoming systematic variations in scanner data; (3) The use of decision rules based upon empirical distributions of scanner signals rather than upon the usually assumed multivariate normal (Gaussian) signal distributions.

Malila, W. A.↗
NASA NTRS1972

Information extraction techniques for multi-spectral scanner data

Multispectral data recognition and information extraction problems considered are: (1) signature extension for improved recognition processing over large areas; (2) choice of density functions for recognition decision rules; (3) channel selection for cost reduction; and (4) radiation balance mapping for interpretation of wide spectrum scanner data. The formulation of a simulation model and reprocessing of both aircraft and space data reduces scan angle variations and extends signatures from one altitude to another. Comparison of the usefulness of empirical density functions and that of Gaussian density functions for recognition processing establishes the advantages of normal assumption for individual fields in processing of multispectral scanner data. Also reported is a procedure for producing radiation balance maps from wide spectra by analyzing energy budgets of vegetation and other surface materials through partitioning net absorbed radiant energy and estimating incoming power density at both short and long wavelengths.

Malila, W. A.↗
NASA NTRS1972

Rapid processing of multispectral scanner data using linear techniques.

Tests have been made to compare linear and quadratic techniques for processing multispectral scanner data. The tests have been limited to a few selected sets of agricultural data. Two aspects of processing were studied. The first, the selection of a subset of channels to be used in the decision function, was found to be faster by a factor of 50 when a linear method was used. Second, in recognition processing, our linear decision rule produced a lower error rate and utilized a larger number of channels for equal processing times. Nevertheless, when the criterion is lowest possible error rate, irregardless of processing time, the quadratic rule is preferable.

Crane, R. B.↗
NASA NTRS1971

Preprocessing techniques to reduce atmospheric and sensor variability in multispectral scanner data.

Multispectral scanner data are potentially useful in a variety of remote sensing applications. Large-area surveys of earth resources carried out by automated recognition processing of these data are particularly important. However, the practical realization of such surveys is limited by a variability in the scanner signals that results in improper recognition of the data. This paper discusses ways by which some of this variability can be removed from the data by preprocessing with resultant improvements in recognition results.

Crane, R. B.↗