Digital Commons Network^™

Development Of A Field Portable Bi-Channel Real Time Hybrid Image Processing System, Nelson Corby, Lester A. Gerhardt, Edward Sims

LARS Symposia

A bichannel, portable, low cost, hybrid processor capable of interactive real-time image processing for use in the field or laboratory is described. Major features of the Programmable Video Processor (PVP) such as operation as a remote pre-processor controlled by a host image processing computer facility or manual operation as a stand-alone processor, digitally programmed operating mode control and internal image statistic generation are discussed. Finally, selected applications in which the PVP has proven useful are outlined.

Skolem Rings And Their Varieties, J. R. Buchi, T. M. Owens

Department of Computer Science Technical Reports

No abstract provided.

Modeling And Performance Evaluation Of Physical Data Base Structures, S. B. Yao

Department of Computer Science Technical Reports

No abstract provided.

The Essential Design Criterion For Computer Languages: Software Science, M. H. Halstead

Department of Computer Science Technical Reports

No abstract provided.

Collocation Methods For Linear Elliptic Problems, Elias N. Houstis

Department of Computer Science Technical Reports

No abstract provided.

Magnetoelastic Rayleigh Wave Convolver, William P. Robbins, Mark S. Lundstrom

Department of Electrical and Computer Engineering Faculty Publications

An epoxy-bonded LiNb03-YIG-LiNb03 composite structure has been constructed and operated as a magnetoelastic Rayleigh wave convolver with 50-MHz input signals. The acoustic signals were propagated on a (110) YIG surface and the convolution characteristics were studied as a function of the magnitude and direction of the applied magnetic field. Nonuniform demagnetizing fields limited convolution pulses to less than 1.5 /-Lsec duration. Relatively efficient operation was observed corresponding to an internal efficiency F int of -53 dBm

Adaptive Bayes Classifiers For Remotely Sensed Data, H. S. Raulston, M. O. Pace, R. C. Gonzalez

LARS Symposia

A new technique for the adaptive estimation of statistics necessary for Bayesian classification is developed. The basic approach to the adaptive estimation procedure consists of two steps: (1) an optimal stochastic approximation of the parameters of interest and (2) a projection of the parameters in time or space. Comparative results of a practical application are shown.

Data Resolution Versus Forestry Classification And Modeling, E. P. Kan, D. L. Ball, J. P. Basu, R. L. Smelser

LARS Symposia

This paper examines the effects on timber stand computer classification accuracies caused by changes in the resolution of remotely sensed multispectral data. This investigation is valuable, especially for determining optimal sensor and platform designs.

Theoretical justification and experimental verification support the finding that classification accuracies for low resolution data could be better than the accuracies for data with higher resolution. The increase in accuracy is construed as due to the reduction of scene inhomogeneity at lower resolution. The computer classification scheme was a maximum likelihood classifier.

Image Registration Error Variance As A Measure Of Overlay Quality, C. D. Mcgillem, M. Svedlow

LARS Symposia

When one image (the signal) is to be registered with a second image (the signal plus noise) of the same scene, one would like to know the accuracy possible for this registration. This paper derives an estimate of the variance of the registration error that can be expected via two approaches. The solution in each instance is found to be a function of the effective bandwidth of the signal and the noise, and the signal-to-noise ratio. Application of these results to ERTS data indicates that for most cases registration variances will be significantly less than the diameter of one picture …

The Use Of The Analysis Of Covariance Model In Spatial Point Estimation, Randall W. Thomas

LARS Symposia

In many resource management oriented disciplines, a spatial array of point estimates for ecosystem parameters and productive capacities is required over a given political/administrative unit. Statistical statements of confidence about these point estimates must be made and the relative importance of factors involved in their prediction should be testable. Moreover, the point estimates must be generated in such a way that differences between values over space can be assessed for statistical significance.

Current remote sensing data automatic classification algorithms employ weighted probability density comparisons of clustered/unclustered hypervolume look up functions for class selection. As such. these discriminant models do not …

A General Non-Parametric Classifier Applied To Discriminating Surface Water From Terrain Shadows, W. G. Eppler

LARS Symposia

A general non-parametric classifier is described in the context of discriminating surface water from terrain shadows. In addition to using non-parametric statistics, this classifier permits the use of a cost matrix to assign different penalties to various types of misclassifications. The approach also differs from conventional classifiers in that it applies the maximum-likelihood criterion to overall class probabilities as opposed to the standard practice of choosing the most likely individual subclass. The classifier performance is evaluated using two different effectiveness measures for a specific set of ERTS data.

Interfacing Of A Color-Tv-Monitor And A Processor With The Aid Of An External Core-Memory For Interactive Picture Processing, R. Buecklein, E. Krauth, M. Mozer, R. Stoiber

LARS Symposia

An interactive picture processing system was developed for semi-automatic processing of the NOAA-3-type weather satellites picture data. This can be helpful in cases where the experiences and the knowledge of the meteorologists can support the digital data processing. Also the system serves as a quick-look image display.

A precision color-TV monitor is used with a 19-inch screen, operating according to the TV-standards. This monitor receives the picture data from a core-memory which is the interface to a PDP 11/45 digital data-processor. The separate core-memory comprises 163 840 18-bit-locations and is organized as a random access memory with respect to a …

Satellite On-Board Processing Of Earth Resources Data, Paul Wintz, Robert Rochelle, Robert Bodenheimer, Ralph Gonzalez

LARS Symposia

Earth resources data processing is presently in a research phase. Scientific spacecraft collect data and telemeter it to ground stations for processing. It is becoming apparent that significant amounts of useful information can-be extracted from the multispectral scanner images by ERTS-1.

It appears that in the 1980-1990 decade operational spacecraft will be launched to continuously monitor crop production, severe weather systems, earth and water pollutants, etc., in order to provide operational information to the users of this information on a near-real time basis. It appears that it may be more cost effective to process the data on-board the satellite and …

Combined Sequential Analysis Of Multiple Features, J. D. Nichols, W. M. Senkus

LARS Symposia

A new technique, which greatly facilitates the computer analysis of large-area multi-feature imagery, has been developed at the R.S.R.P. Called OWNMASK, the technique permits previous classification results for an area to be used to control new classifications of that area in such a way that both the number of features and the number of classes which must be considered for each pixel are reduced significantly, thereby reducing both human labor and computer costs.

The Decision Tree Classifier: Design And Potential, Hans Hauska, Philip H. Swain

LARS Symposia

The basic concepts of a multi-stage classification strategy, the decision tree classifier, are presented. The two main methods to design decision trees are presented and discussed along with some experimental results. An attempt is made to describe an Applicable Logic for the design of decision trees. Advantages and disadvantages of the both design approaches are discussed.

Processing Remotely Sensed Data For Dimensional Analysis, T. L. Cox, H. C. Hitchcock, S. G. Weber

LARS Symposia

Forest inventory data was interpreted from color IR photography, transferred to base maps, and digitized for machine processing. The data was registered to geodetic coordinates providing the capability to perform several types of dimensional analysis. Processing data by this technique allowed: (1) Spatial or single variable analysis, (2) overlay or composite analysis (in combination with other variables), and (3) temporal analysis. Information derived from this procedure was input for a land management decision system used to construct a forest management plan for 25,000 acres in east Tennessee.

An Incisive Neighborhood Discerning Iteratively Aggregating Nomenclator (Indian) System For Pattern Recognition In Unsupervised Environments, Belur V. Dasarathy

LARS Symposia

A novel system for pattern recognition in unsupervised environments, which combines the conceptual elegance of clustering schemes based on inter-sample distance measures with the computational simplicity of histogram approaches, is presented in this study. The multi-dimensional histogram of the entire data set is first derived and by scanning this histogram space, the significant hills therein are identified. The centroids of these hills are deemed to be representative of the given input sample set. This representative pseudo-sample set is then input to the CURRY system (International Journal of System Science, Vol. 6, No. 1, January 1975, pp 23-32), which has the …

A Study Utilizing Automatically Processed Multispectral Data To Delineate A Flood Plain, George R. Harker

LARS Symposia

The delineation of flood plains using current techniques is both costly and time-consuming. This paper explores the application of a remote sensing technique that may permit the determination of flood plain areas without the extensive work associated with existing techniques.

In this study multispectral scanner data were simulated utilizing the density differences in a color infrared transparency for a section of the Navasota River in Texas. The simulated data were processed by an automatic classification technique previously developed in the remote sensing field.

The technique used involves the application of the maximum likelihood rule to categorize the data being processed. …

A Layered Classification Technique For Water Resources Applications, Luis A. Bartolucci, Roger M. Hoffer, Stephen G. Luther

LARS Symposia

The use of computer-aided analysis techniques (CAAT) and multispectral scanner data from aircraft and satellite altitudes has shown considerable promise for water resources applications. Two areas of particular interest are: (1) temperature mapping of surface water to study the environmental impact of thermal effluents and (2) snow-cover mapping in mountainous regions to improve water yield predictions. The conventional LARSYS classifier has proven to be inadequate for these purposes. Therefore, a layered classification approach was utilized to overcome the limitations of the conventional LARSYS classifier.

Digital Processing Of Infra-Red Scanner Data For Radiometric Temperature Analysis Of Thermal Plumes, D. Langner, J. Michael, D. Wright

LARS Symposia

A method for digitally reducing thermal plume data obtained from a Bendix Thermal Mapper is presented. This method includes a distortion removal technique and the calculation of apparent blackbody temperature from the scanner's output film. This method is illustrated using data obtained with a Bendix scanner over the Surry Station nuclear power generating facility located on the James River in Surry, Virginia.

Exploiting The Temporal Coherence Of Repetitive Satellite Imagery, William E. Evans

LARS Symposia

Imagery from ERTS or the Synchronous Meteorological Satellites, because of its precisely repetitive nature, is ideally suited both for subjective enhancement via time-lapse display and for objective measurements of changes with time. The SRI ESIAC, a hybrid system providing both viewing and image processing functions, is described. A representative application involves the measurement of changes in aerial extent of snow cover within specified mountain watersheds.

Subjective viewing of time-lapse sequences of the snow scenes provides valuable insight into the nature of numerous extraneous signals, permitting the interim implementation of operationally useful snow measuring systems while hopefully leading toward the design …

Mapping Wetlands From Their Spectral Properties Recorded By Erts System, S. J. Kristof, R. A. Weismiller

LARS Symposia

No abstract provided.

Erts Direct Digital Printing & Multitemporal Data Registration, Robert F. Burke, William Marshall

LARS Symposia

The objective of this study was to determine if the quality of the ERTS imagery could be improved by averaging successive passes over the same physical area.

The U.S.G.S. designated five passes over two areas of study: Washington, D. C. and Phoenix, Ariz., with the requirement that optimized imagery be derived directly from the EROS Data Center Bulk CCT's. The Mead system goes directly from the Bulk CCT's to hard-copy print-out, thereby by-passing any intermediate electronic, electro-optical, or photographic processes which may lead to image deterioration.

Description Of An Image Processing System For Multispectral Scanner Data, J. Gredel, W. Rattei

LARS Symposia

No abstract provided.

Computer-Aided Geologic Mapping Using Landsat-1 Data, A Feasible Task?, H. Hauska, B. Follestad, D. Levandowski

LARS Symposia

No abstract provided.

Resolution Enhancement Of Erts Imagery, C. D. Mcgillem, T. E. Riemer, G. Mobasseri

LARS Technical Reports

A method is described for combined interpolation and enhancement of ERTS multispectral scanner data sets. Previous research has shown that good enhancement is not easily achieved when there are a large number of data points contained within the radius of gyration of the system point spread function. This requirement can be met using ERTS data by interpolating the data before enhancement. By varying the interpolation scale factor the data set can be empirically matched to a precalculated optimum restoration filter. Once the proper match of data and filter has been found the enhancement can be carried out directly or the …

Evaluation Of All-Digital Precision Registration Methods For Landsat Mss Data, S. Rifman, B. Peavey, R. Caron, K. Simon

LARS Symposia

A major factor contributing to the utility of LANDSAT data is the repetitive coverage of each spot on the earth's surface within the sensor's field of view at least once every 18 days. This repeat coverage makes possible: studies of crop growth: monitoring urban development and land use: and predicting water runoff from melting ice and snow, just to name a few examples. Of central importance to investigators performing these studies is the requirement that imagery and/or image data on computer compatible tapes (CCT's) register to a fraction of a pixel. This paper describes the application of all digital processing …

Considerations & Techniques For Making A High Quality Three-Color Print From Skylab 5192 Data, Margery Harris, Kenneth Livermore

LARS Symposia

This paper outlines several simple data processing algorithms for enhancing the 5192 data, including rectilinearization and filtering techniques suitable for minicomputers. Additional enhancement techniques for the die transfer printing process are also discussed.

The Use Of Landsat Data In A Large Area Crop Inventory Experiment (Lacie), R. B. Macdonald, F. G. Hall, R. B. Erb

LARS Symposia

A Large Area Crop Inventory Experiment (LACIE) has been under taken jointly by the U.S. Department of Agriculture, the National Oceanic and Atmospheric Administration (NOAA) of the Department of Commerce and the National Aeronautics and Space Administration (NASA) to prove out an economically important application of remote sensing from space. At the outset LACIE will concentrate on wheat grown in the North American area. The experiment will combine crop area measurements obtained from LANDSAT data and meteorological information from NOAA satellites and from ground stations designed to relate weather conditions to yield assessment and ultimately to production forecasts. The Department …

Classification Of Multispectral Image Data By Extraction And Classification Of Homogeneous Objects, R. L. Kettig, D. A. Landgrebe

LARS Symposia

A method of classification of digitized multispectral image data is described. It is designed to exploit a particular type of dependence between adjacent states of nature that is characteristic of the data. The advantages of this, as opposed to the conventional "per point" approach, are greater accuracy and efficiency, and the results are in a more desirable form. Experimental results from both aircraft and satellite data are included.