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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 379 records · Page 21

An image compression survey and algorithm switching based on scene activity

Data compression techniques are presented. A description of these techniques is provided along with a performance evaluation. The complexity of the hardware resulting from their implementation is also addressed. The compression effect on channel distortion and the applicability of these algorithms to real-time processing are presented. Also included is a proposed new direction for an adaptive compression technique for real-time processing.

Hart, M. M.↗

The New Galileo Communication System

ave been developed to get as much data as possible from the Galileo spacecraft even without the high gain antenna. These methods include extensive data compression, a new packetized telemetry format, new error-correcting codes, new modulation, new ground receivers, and antenna arraying. (abstract only).

Galileo data compression spacecraft mission operat↗

An adaptable recursive binary entropy coding technique

We present a novel data compression technique, called recursive interleaved entropy coding, that is based on recursive interleaving of variable-to-variable length binary source codes.

data compression entrophy coding biliary adaptive ↗

Science-based Region-of-Interest Image Compression

As the number of currently active space missions increases, so does competition for Deep Space Network (DSN) resources. Even given unbounded DSN time, power and weight constraints onboard the spacecraft limit the maximum possible data transmission rate. These factors highlight a critical need for very effective data compression schemes. Images tend to be the most bandwidth-intensive data, so image compression methods are particularly valuable. In this paper, we describe a method for prioritizing regions in an image based on their scientific value. Using a wavelet compression method that can incorporate priority information, we ensure that the highest priority regions are transmitted with the highest fidelity.

Wagstaff, K. L.↗

On the computational cost of approximating and recognizing noise-perturbed straight lines and quadratic arcs in the plane

Recognition of underlying straight lines and quadratic arcs in line drawings, and approximation of very noisy data by such line/curve segments, is addressed as a subproblem of the more general problem of optimum recognition of complicated line/curve drawings. Some specific algorithms are presented with extensions and interpretations for more complicated applications, and a data generation model is developed for the problem. Data are generated as a perturbation of a single underlying straight line or an elliptic or hyperbolic arc. Recursive estimation techniques, minimization of central processing unit time, decision making with controlled error probabilities, and modeling and recognition of pictures consisting of noisy curves are dealt with. Applications envisaged include: picture data compression, contour line representation in maps, intelligent data searches, and ballistic missile decoy tracking.

Cooper, D. B.↗

Introduction to the concepts of TELEDEMO and TELEDIMS

An introduction to the system concepts: TELEDEMO and TELEDIMS is provided. TELEDEMO is derived primarily from computer graphics and, via incorporation of sophisticated image data compression, enables effective low cost teleconferencing at data rates as low as 1K bit/second using dial-up phone lines. Combining TELEDEMO's powerful capabilities for the development of presentation material with microprocessor-based Information Management Systems (IMS) yields a truly all electronic IMS called TELEDIMS.

Rice, R. F.↗

The imaging spectrometer approach

Two important sensor design drivers are the requirement for spatial registration of the spectral components and the implementation of the advanced multispectral capability, including spectral band width, number of bands and programmability. The dispersive approach, fundamental to the imaging spectrometer concept, achieves these capabilities by utilizing a spectrometer to disperse the spectral content while preserving the spatial identity of the information in the cross-track direction. Area array detectors in the spectrometer focal plane detect and store the spatial and multispectral content for each line of the image. The choice of spectral bands, image IFOV and swath width is implemented by programmed readout of the focal plane. These choices in conjunction with data compression are used to match the output data rate with the telemetry link capability. Progress in the key technologies of optics, focal plane detector arrays, onboard processing, and focal plane cooling supports the viability of the imaging spectrometer approach.

Wellman, J. B.↗

Coding for Efficient Image Transmission

NASA publication second in series on data-coding techniques for noiseless channels. Techniques used even in noisy channels, provided data further processed with Reed-Solomon or other error-correcting code. Techniques discussed in context of transmission of monochrome imagery from Voyager II spacecraft but applicable to other streams of data. Objective of this type coding to "compress" data; that is, to transmit using as few bits as possible by omitting as much as possible of portion of information repeated in subsequent samples (or picture elements).

Rice, R. F.↗

JPL multipolarization workstation - Hardware, software and examples of data analysis

A low-cost stand-alone interactive image processing workstation has been developed for operations on multipolarization JPL aircraft SAR data, as well as data from future spaceborne imaging radars. A recently developed data compression technique is used to reduce the data volume to 10 Mbytes, for a typical data set, so that interactive analysis may be accomplished in a timely and efficient manner on a supermicrocomputer. In addition to presenting a hardware description of the work station, attention is given to the software that has been developed. Three illustrative examples of data analysis are presented.

Burnette, Fred↗

System and Method for Monitoring Distributed Asset Data

A computer-based monitoring system and monitoring method implemented in computer software for detecting, estimating, and reporting the condition states, their changes, and anomalies for many assets. The assets are of same type, are operated over a period of time, and outfitted with data collection systems. The proposed monitoring method accounts for variability of working conditions for each asset by using regression model that characterizes asset performance. The assets are of the same type but not identical. The proposed monitoring method accounts for asset-to-asset variability; it also accounts for drifts and trends in the asset condition and data. The proposed monitoring system can perform distributed processing of massive amounts of historical data without discarding any useful information where moving all the asset data into one central computing system might be infeasible. The overall processing is includes distributed preprocessing data records from each asset to produce compressed data.

Gorinevsky, Dimitry↗

Lossless compression of AVIRIS data: Comparison of methods and instrument constraints

A family of lossless compression methods, allowing exact image reconstruction, are evaluated for compressing Airborne Visible/Infrared Imaging Spectrometers (AVIRIS) image data. The methods are used on Differential Pulse Code Modulation (DPCM). The compressed data have an entropy of order 6 bits/pixel. A theoretical model indicates that significantly better lossless compression is unlikely to be achieved because of limits caused by the noise in the AVIRIS channels. AVIRIS data differ from data produced by other visible/near-infrared sensors, such as LANDSAT-TM or SPOT, in several ways. Firstly, the data are recorded at a greater resolution (12 bits, though packed into 16-bit words). Secondly, the spectral channels are relatively narrow and provide continuous coverage of the spectrum so that the data in adjacent channels are generally highly correlated. Thirdly, the noise characteristics of the AVIRIS are defined by the channels' Noise Equivalent Radiances (NER's), and these NER's show that, at some wavelengths, the least significant 5 or 6 bits of data are essentially noise.

Roger, R. E.↗

A bandwidth-compressive modulation system

The phrase 'bandwidth-compressive modulation' means that the compression is achieved not by removing redundancy from the data (data compression), but rather by modulating the carrier phase and amplitude with blocks of data bits. The modulation described here is quadrature amplitude shift keying (QASK), a logical extension of quadrature phase shift keying, (QPSK, or quadriphase). QASK is a cost-effective form of combined phase-and-amplitude modulation. That is, n-bit QASK, like most phase-amplitude forms of modulation, requires considerably less transmitter power than comparably performing n-PSK, while among the class of all n-bit phase-modulation types, n-bit QASK performs nearly optimally but requires the least circuit complexity. A simple, unique microwave transmitter is described which provides high-rate QASK modulation with 4:1 bandwidth compression. A suppressed carrier multiple-loop QASK receiver provides the necessary phase tracking, automatic gain control (AGC), and symbol timing.

Smith, J. G.↗

Spatial degradation of satellite data

Consideration is given to a technique for spatially degrading high-resolution satellite data to produce comparable data sets over a range of coarser resolutions. Landsat MSS data is used to produce seven spatial resolution data sets by applying a spatial filter designed to simulate sensor response. Also, spatial degradation of coarse resolution data to provide data compression for the production of global-scale data sets is examined. NOAA AVHRR Global Area Coverage data is compared to other sampling procedures. It is found that sampling procedures that incorporate averaging result in decreased variance, while sampling procedures adopting single-value selection have higher variances and produce data values comparable with those from the original data.

Justice, C. O.↗

Method of Real-Time Principal-Component Analysis

Dominant-element-based gradient descent and dynamic initial learning rate (DOGEDYN) is a method of sequential principal-component analysis (PCA) that is well suited for such applications as data compression and extraction of features from sets of data. In comparison with a prior method of gradient-descent-based sequential PCA, this method offers a greater rate of learning convergence. Like the prior method, DOGEDYN can be implemented in software. However, the main advantage of DOGEDYN over the prior method lies in the facts that it requires less computation and can be implemented in simpler hardware. It should be possible to implement DOGEDYN in compact, low-power, very-large-scale integrated (VLSI) circuitry that could process data in real time.

Duong, Tuan↗

Real-Time Principal-Component Analysis

A recently written computer program implements dominant-element-based gradient descent and dynamic initial learning rate (DOGEDYN), which was described in Method of Real-Time Principal-Component Analysis (NPO-40034) NASA Tech Briefs, Vol. 29, No. 1 (January 2005), page 59. To recapitulate: DOGEDYN is a method of sequential principal-component analysis (PCA) suitable for such applications as data compression and extraction of features from sets of data. In DOGEDYN, input data are represented as a sequence of vectors acquired at sampling times. The learning algorithm in DOGEDYN involves sequential extraction of principal vectors by means of a gradient descent in which only the dominant element is used at each iteration. Each iteration includes updating of elements of a weight matrix by amounts proportional to a dynamic initial learning rate chosen to increase the rate of convergence by compensating for the energy lost through the previous extraction of principal components. In comparison with a prior method of gradient-descent-based sequential PCA, DOGEDYN involves less computation and offers a greater rate of learning convergence. The sequential DOGEDYN computations require less memory than would parallel computations for the same purpose. The DOGEDYN software can be executed on a personal computer.

Duong, Vu↗

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.↗