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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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At least 217 records · Page 12

Snow survey and vegetation growth in high mountains (Swiss Alps) and additional ERTS investigations in Switzerland

The author has identified the following significant results. Two different methods, an analog and a digital one, have been developed for rapid and accurate mapping of the areal extent and changes in snow cover in high mountains. The quick-look method is based on individual visual control of each image using a photo quantizer which provides exact references for density slicing with high resolution lith-film. The digital snow classification system is based on discriminant analysis with the data of the four multispectral bands as variables and contains all preprocessing, feature extraction, and mapping steps for an operational application. Two different sets of sampling groups were established which apply to different conditions of snow cover. The first one serves for the normal situation with a uniform dry and new cover. The second one serves for situations with partly thawing and/or frozen snow.

Haefner, H.↗

Joint pattern recognition/data compression concept for ERTS multispectral imaging

This paper describes a new technique which jointly applies clustering and source encoding concepts to obtain data compression. The cluster compression technique basically uses clustering to extract features from the measurement data set which are used to describe characteristics of the entire data set. In addition, the features may be used to approximate each individual measurement vector by forming a sequence of scalar numbers which define each measurement vector in terms of the cluster features. This sequence, called the feature map, is then efficiently represented by using source encoding concepts. A description of a practical cluster compression algorithm is given and experimental results are presented to show trade-offs and characteristics of various implementations. Examples are provided which demonstrate the application of cluster compression to multispectral image data of the Earth Resources Technology Satellite.

Hilbert, E. E.↗

Development of signal processing algorithms for ultrasonic detection of coal seam interfaces

A pattern recognition system is presented for determining the thickness of coal remaining on the roof and floor of a coal seam. The system was developed to recognize reflected pulse echo signals that are generated by an acoustical transducer and reflected from the coal seam interface. The flexibility of the system, however, should enable it to identify pulse-echo signals generated by radar or other techniques. The main difference being the specific features extracted from the recorded data as a basis for pattern recognition.

Purcell, D. D.↗

Linear dimensionality of Landsat agricultural data with implications for classification

A model for the Landsat multispectral scanner data, representing a generalization of the commonly used Gaussian model, has been formulated and analyzed. The model hypothesizes that the data for different crop types essentially lie on distinct hyperplanes in the feature space. Tests of this model reveal that: (1) the agricultural data from any single acquisition (i.e., four-channel) of Landsat are essentially two dimensional, regardless of the crop type; and (2) the data from different sites and different stages of crop development all lie on planes which are parallel. These findings have significant implications for data display, classification, feature extraction, and signature extension.

Wheeler, S. G.↗

Landsat Signature Development Program

The Landsat Signature Development Program, LSDP, is designed to produce an unsupervised classification of a scene from a Landsat tape. This classification is based on the clustering tendencies of the multispectral scanner data processed from the scene. The program will generate a character map that, by identifying each of the general classes of surface features extracted from the scene data with a specific line printer symbol, indicates the approximate locations and distributions of these general classes within the scene. Also provided with the character map are a number of tables each of which describes either some aspect of the spectral properties of the resultant classes, some inter-class relationship, the incidence of picture elements assigned to the various classes in the character map classification of the scene, or some significant intermediate stage in the development of the final classes.

Hall, R. N.↗

Image data-processing system for solar astronomy

The paper describes an image data processing system (IDAPS), its hardware/software configuration, and interactive and batch modes of operation for the analysis of the Skylab/Apollo Telescope Mount S056 X-Ray Telescope experiment data. Interactive IDAPS is primarily designed to provide on-line interactive user control of image processing operations for image familiarization, sequence and parameter optimization, and selective feature extraction and analysis. Batch IDAPS follows the normal conventions of card control and data input and output, and is best suited where the desired parameters and sequence of operations are known and when long image-processing times are required. Particular attention is given to the way in which this system has been used in solar astronomy and other investigations. Some recent results obtained by means of IDAPS are presented.

Wilson, R. M.↗

An image-processing system applied to earth-resource imagery

The Harwell Image Processing System (HIPS) has been adapted for processing earth-resource imagery in either film or tape format. Data from film are obtained using a computer-controlled flying-spot scanner. Local rapid interactive processing is based on a PDP 11/20 minicomputer which has suitable display facilities for immediate visual appraisal of results and also a fast data link to an IBM 370/168 computer complex. An extensive subroutine library is being assembled for data preprocessing and feature extraction. This chapter includes a discussion of the basic principles of image analysis, a description of the HIPS system, and finally, for illustrative purposes, a description of several simple software routines.

Carter, P.↗

Classification and machine recognition of severe weather patterns

Forecasting and warning of severe weather conditions are treated from the vantage point of pattern recognition by machine. Pictorial patterns and waveform patterns are distinguished. Time series data on sferics are dealt with by considering waveform patterns. A severe storm patterns recognition machine is described, along with schemes for detection via cross-correlation of time series (same channel or different channels). Syntactic and decision-theoretic approaches to feature extraction are discussed. Active and decayed tornados and thunderstorms, lightning discharges, and funnels and their related time series data are studied.

Wang, P. P.↗

A scene-analysis approach to remote sensing

The author has identified the following significant results. Geometric correspondance between a sensed image and a symbolic map is established in an initial stage of processing by adjusting parameters of a sensed model so that the image features predicted from the map optimally match corresponding features extracted from the sensed image. Information in the map is then used to constrain where to look in an image, what to look for, and how to interpret what is seen. For simple monitoring tasks involving multispectral classification, these constraints significantly reduce computation, simplify interpretation, and improve the utility of the resulting information. Previously intractable tasks requiring spatial and textural analysis may become straightforward in the context established by the map knowledge. The use of map-guided image analysis in monitoring the volume of water in a reservoir, the number of boxcars in a railyard, and the number of ships in a harbor is demonstrated.

Tenenbaum, J. M.↗

Decision rules for unbiased inventory estimates

An efficient and accurate procedure for estimating inventories from remote sensing scenes is presented. In place of the conventional and expensive full dimensional Bayes decision rule, a one-dimensional feature extraction and classification technique was employed. It is shown that this efficient decision rule can be used to develop unbiased inventory estimates and that for large sample sizes typical of satellite derived remote sensing scenes, resulting accuracies are comparable or superior to more expensive alternative procedures. Mathematical details of the procedure are provided in the body of the report and in the appendix. Results of a numerical simulation of the technique using statistics obtained from an observed LANDSAT scene are included. The simulation demonstrates the effectiveness of the technique in computing accurate inventory estimates.

Argentiero, P. D.↗

Map-guided interpretation of remotely-sensed imagery

A map-guided approach to interpretation of remotely sensed imagery is described, with emphasis on applications involving continuous monitoring of predetermined ground sites. Geometric correspondence between a sensed image and a symbolic reference map is established in an initial stage of processing by adjusting parameters of a sensor model so that image features predicted from the map optimally match corresponding features extracted from the sensed image. Information in the map is then used to constrain where to look in an image and what to look for. With such constraints, previously intractable remote sensing tasks can become feasible, even easy, to automate. Four illustrative examples are given, involving the monitoring of reservoirs, roads, railroad yards, and harbors.

Tenenbaum, J. M.↗

An asymptotic expansion approach to the inverse radiative transfer problem

An iterative technique which recovers density profiles in a nonhomogeneous absorbing atmosphere is derived. The technique is based on the concept of factoring a function of the density profile into the product of a known term and a term which is not known, but whose power series expansion can be found. This series converges rapidly under a wide range of conditions. A demonstration example of simulated data from a high resolution infrared heterodyne instrument is inverted. For the examples studied, the technique is shown to be capable of extracting features of ozone profiles in the troposphere and to be particularly stable.

Gomberg, R. I.↗

Methods for segment wheat area estimation

The major research conducted during the three years of LACIE to solve problems associated with segment wheat area estimation is reviewed. Topics covered include proportion estimation, clustering, feature extraction, and signature extension. It would appear that LANDSAT-1 and LANDSAT-2 data do not contain enough information to discriminate between crop types perfectly all the time and, therefore, a basic problem arises when no ground truth data on crop types in the area are available. New approaches are needed to reduce labeling error. Perhaps better use of multiyear LANDSAT data, a more detailed understanding of the cropping practices in the area, better crop calendar prediction, and a better understanding of the limiting sources of error in LANDSAT data related to crop discrimination may provide the insight required to develop improved designs.

Heydorn, R. P.↗

The suitability of the ILLIAC IV architecture for image processing

The major architectural features of the ILLIAC IV large scale, array processor are summarized along with their applicability to image processing. Several image processing algorithms are considered, including multispectral classification, texture feature extraction, two-dimensional Fourier transform, and synthetic aperture radar processing. The basic parallelism of the ILLIAC IV (64 processing elements acting in lock-step) is usually fully utilized by the image processing applications. The major architectural aspect of the system with respect to image processing is the relatively small local scratch-pad memory and the long latency time to access the main storage device. The major precision used for the image processing applications is the 32-bit floating point, given a choice of 8-bit integers and 64-bit floating point.

Stevenson, D. K.↗

Radar image enhancement and simulation as an aid to interpretation and training

Greatly increased activity in the field of radar image applications in the coming years demands that techniques of radar image analysis, enhancement, and simulation be developed now. Since the statistical nature of radar imagery differs from that of photographic imagery, one finds that the required digital image processing algorithms (e.g., for improved viewing and feature extraction) differ from those currently existing. This paper addresses these problems and discusses work at the Remote Sensing Laboratory in image simulation and processing, especially for systems comparable to the formerly operational SEASAT synthetic aperture radar.

Frost, V. S.↗

Inventory estimation on the massively parallel processor

This paper describes algorithms for efficiently computing inventory estimates from satellite based images. The algorithms incorporate a one dimensional feature extraction which optimizes the pairwise sum of Fisher distances. Biases are eliminated with a premultiplication by the inverse of the analytically derived error matrix. The technique is demonstrated with a numerical example using statistics obtained from an actual Landsat scene. Attention was given to implementation of the Massively Parallel processor (MPP). A timing analysis demonstrates that the inventory estimation can be performed an order of magnitude faster on the MPP than on a conventional serial machine.

Argentiero, P. D.↗

Mobility aid for the blind

A project to develop an effective mobility aid for blind pedestrians which acquires consecutive images of the scenes before a moving pedestrian, which locates and identifies the pedestrian's path and potential obstacles in the path, which presents path and obstacle information to the pedestrian, and which operates in real-time is discussed. The mobility aid has three principal components: an image acquisition system, an image interpretation system, and an information presentation system. The image acquisition system consists of a miniature, solid-state TV camera which transforms the scene before the blind pedestrian into an image which can be received by the image interpretation system. The image interpretation system is implemented on a microprocessor which has been programmed to execute real-time feature extraction and scene analysis algorithms for locating and identifying the pedestrian's path and potential obstacles. Identity and location information is presented to the pedestrian by means of tactile coding and machine-generated speech.

Source record↗

Proceedings of the NASA Workshop on Registration and Rectification

Issues associated with the registration and rectification of remotely sensed data. Near and long range applications research tasks and some medium range technology augmentation research areas are recommended. Image sharpness, feature extraction, inter-image mapping, error analysis, and verification methods are addressed.

Bryant, N. A.↗