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Hilbert, E. E.

Publications and source records attributed to Hilbert, E. E..

Compressing TV-image data

Compressing technique calculates activity estimator for each segment of image line. Estimator is used in conjunction with allowable bits per line, N, to determine number of bits necessary to code each segment and which segments can tolerate truncation. Preprocessed line data are then passed to adaptive variable-length coder, which selects optimum transmission code. Method increases capacity of broadcast and cable television transmissions and helps reduce size of storage medium for video and digital audio recordings.

Hilbert, E. E.

An image-data-compression algorithm

Cluster Compression Algorithm (CCA) preprocesses Landsat image data immediately following satellite data sensor (receiver). Data are reduced by extracting pertinent image features and compressing this result into concise format for transmission to ground station. This results in narrower transmission bandwidth, increased data-communication efficiency, and reduced computer time in reconstructing and analyzing image. Similar technique could be applied to other types of recorded data to cut costs of transmitting, storing, distributing, and interpreting complex information.

Hilbert, E. E.

Basic cluster compression algorithm

Feature extraction and data compression of LANDSAT data is accomplished by BCCA program which reduces costs associated with transmitting, storing, distributing, and interpreting multispectral image data. Algorithm uses spatially local clustering to extract features from image data to describe spectral characteristics of data set. Approach requires only simple repetitive computations, and parallel processing can be used for very high data rates. Program is written in FORTRAN IV for batch execution and has been implemented on SEL 32/55.

Hilbert, E. E.

A sensor for control of arterials and networks

The sensor for control of arterials and networks (SCAN) uses imaging technology and processing technology to jointly provide real-time quantification. The SCAN concept consists of a television camera mounted on a pole to obtain images of the traffic, and a microprocessor to process the image data into traffic parameters. The current activities focus on the development of SCAN for surveillance of arterials or urban highways. If these efforts are successful, an attempt will be made to extend the concept to network applications. The key software developed for the SCAN is a vehicle detection and tracking algorithm which reduces the TV image data to vehicle descriptions and trajectories. These preprocessed trajectory data can be transmitted over a phone line or can be easily reduced to a wide range of traffic parameters. A SCAN breadboard has been implemented and installed in a van which enables remote field tests and evaluations. The SCAN breadboard and its operation, evaluation, and potential applications are described.

Hilbert, E. E.

Wide area detection system: Conceptual design study

An integrated sensor for traffic surveillance on mainline sections of urban freeways is described. Applicable imaging and processor technology is surveyed and the functional requirements for the sensors and the conceptual design of the breadboard sensors are given. Parameters measured by the sensors include lane density, speed, and volume. The freeway image is also used for incident diagnosis.

Hilbert, E. E.

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.

Advanced imaging communication system

Key elements of system are imaging and nonimaging sensors, data compressor/decompressor, interleaved Reed-Solomon block coder, convolutional-encoded/Viterbi-decoded telemetry channel, and Reed-Solomon decoding. Data compression provides efficient representation of sensor data, and channel coding improves reliability of data transmission.

Hilbert, E. E.

Space communication system for compressed data with a concatenated Reed-Solomon-Viterbi coding channel

A space communication system incorporating a concatenated Reed Solomon Viterbi coding channel is discussed for transmitting compressed and uncompressed data from a spacecraft to a data processing center on Earth. Imaging (and other) data are first compressed into source blocks which are then coded by a Reed Solomon coder and interleaver, followed by a convolutional encoder. The received data is first decoded by a Viterbi decoder, followed by a Reed Solomon decoder and deinterleaver. The output of the latter is then decompressed, based on the compression criteria used in compressing the data in the spacecraft. The decompressed data is processed to reconstruct an approximation of the original data-producing condition or images.

Rice, R. F.

Joint Classification and Data Compression of multidimensional information sources - Application to ERTS

This paper describes a concept of Joint Classification and Data Compression of multidimensional information sources in the context of applications to Earth Resources Technology Satellites. The concept is used to define an Information Extraction System intended to remove data redundancy early in the sensor to user link in both classification and film interpretation applications. The approach uses cascaded partially supervised clustering to extract spectral intensity features from spatially local sources. Data compression is then used to efficiently represent spatial features within the spectral intensity feature map.

Hilbert, E. E.

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.

Data multiplexer using a tree switch

Self-decoding FET-hybrid or integrated-circuit tree configuration uses minimum number of components and can be sequenced by clock or computer. Redundancy features can readily be incorporated into tree configuration; as tree grows in size and more sensors are included, percentage of parts that will affect given percentage of sensors steadily decreases.

Easton, R. A.

Flexible format, computer accessed telemetry system

With this system, it is possible to sample and generate two or more simultaneous formats; one can be transmitted to ground station in real time, and other is stored for later transmission. Sensor output comparison data, plus information to control format, compression algorithm, and allowable degree of sensor activity, are stored in memory.

Easton, R. A.

Transistor current and voltage limiting switch

Limiting circuit protects the main power supply of electronic modules and limits the current drawn by each module should a short circuit occur. It limits current within one mA when used with direct current of either polarity, or with pulse or ac power sources from direct current to 100 kHz.

Hilbert, E. E.