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At least 613 records · Page 34

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NASA NTRS1989

Performance of concatenated codes using 8-bit and 10-bit Reed-Solomon codes

The performance improvement of concatenated coding systems using 10-bit instead of 8-bit Reed-Solomon codes is measured by simulation. Three inner convolutional codes are considered: (7,1/2), (15,1/4), and (15,1/6). It is shown that approximately 0.2 dB can be gained at a bit error rate of 10(-6). The loss due to nonideal interleaving is also evaluated. Performance comparisons at very low bit error rates may be relevant for systems using data compression.

Pollara, F.↗

NASA NTRS1990

Fast Feature-Recognizing Optoelectronic System

Proposed optoelectronic system recognizes features or classifies images by processing outputs of photosensors rapidly, in parallel, through circuits developed in research on neural networks. Array of photoconductive elements serve as photomodulated connections in electronic neural network, which provides high speed data compression to generate feature vector. System able to "learn" new patterns for subsequent recognition. Potential applications in robotic vision systems and pattern recognition.

Thakoor, S.↗

NASA NTRS1989

Context dependent anti-aliasing image reconstruction

Image Reconstruction has been mostly confined to context free linear processes; the traditional continuum interpretation of digital array data uses a linear interpolator with or without an enhancement filter. Here, anti-aliasing context dependent interpretation techniques are investigated for image reconstruction. Pattern classification is applied to each neighborhood to assign it a context class; a different interpolation/filter is applied to neighborhoods of differing context. It is shown how the context dependent interpolation is computed through ensemble average statistics using high resolution training imagery from which the lower resolution image array data is obtained (simulation). A quadratic least squares (LS) context-free image quality model is described from which the context dependent interpolation coefficients are derived. It is shown how ensembles of high-resolution images can be used to capture the a priori special character of different context classes. As a consequence, a priori information such as the translational invariance of edges along the edge direction, edge discontinuity, and the character of corners is captured and can be used to interpret image array data with greater spatial resolution than would be expected by the Nyquist limit. A Gibb-like artifact associated with this super-resolution is discussed. More realistic context dependent image quality models are needed and a suggestion is made for using a quality model which now is finding application in data compression.

Beaudet, Paul R.↗

NASA NTRS1989

From primal sketches to the recovery of intensity and reflectance representations

A local change in intensity (edge) is a characteristic that is preserved when an image is filtered through a bandpass filter. Primal sketch representations of images, using the bandpass-filtered data, have become a common process since Marr proposed his model for early human vision. Here, researchers move beyond the primal sketch extraction to the recovery of intensity and reflectance representations using only the bandpass-filtered data. Assessing the response of an ideal step edge to the Laplacian of Gaussian (NAb/A squared G) filter, they found that the resulting filtered data preserves the original change of intensity that created the edge in addition to the edge location. Using the filtered data, they can construct the primal sketches and recover the original (relative) intensity levels between the boundaries. It was found that the result of filtering an ideal step edge with the Intensity-Dependent Spatial Summation (IDS) filter preserves the actual intensity on both sides of the edge, in addition to the edge location. The IDS filter also preserves the reflectance ratio at the edge location. Therefore, one can recover the intensity levels between the edge boundaries as well as the (relative) reflectance representation. The recovery of the reflectance representation is of special interest as it erases shadowing degradations and other dependencies on temporal illumination. This method offers a new approach to low-level vision processing as well as to high data-compression coding. High compression can be gained by transmitting only the information associated with the edge location (edge primitives) that is necessary for the recovery

Alter-Gartenberg, Rachel↗

NASA NTRS1989

Design of a monitor and simulation terminal (master) for space station telerobotics and telescience

Based on Space Station and planetary spacecraft communication time delays and bandwidth limitations, it will be necessary to develop an intelligent, general purpose ground monitor terminal capable of sophisticated data display and control of on-orbit facilities and remote spacecraft. The basic elements that make up a Monitor and Simulation Terminal (MASTER) include computer overlay video, data compression, forward simulation, mission resource optimization and high level robotic control. Hardware and software elements of a MASTER are being assembled for testbed use. Applications of Neural Networks (NNs) to some key functions of a MASTER are also discussed. These functions are overlay graphics adjustment, object correlation and kinematic-dynamic characterization of the manipulator.

Lopez, L.↗

NASA NTRS1989

Imaging spectrometry - Technology and applications

The development history and current status of NASA imaging-spectrometer (IS) technology are discussed in a review covering the period 1982-1988. Consideration is given to the Airborne IS first flown in 1982, the second-generation Airborne Visible and IR IS (AVIRIS), the High-Resolution IS being developed for the EOS polar platform, improved two-dimensional focal-plane arrays for the short-wave IR spectral region, and noncollinear acoustooptic tunable filters for use as spectral dispersing elements. Also examined are approaches to solving the data-processing problems posed by the high data volumes of state-of-the-art ISs (e.g., 160 MB per 600 x 600-pixel AVIRIS scene), including intelligent data editing, lossless and lossy data compression techniques, and direct extraction of scientifically meaningful geophysical and biophysical parameters.

Solomon, Jerry E.↗

NASA NTRS1990

Rocket engine diagnostics using neural networks

Two problems in applying neural networks to fault detection and identification are (1) the complexity of the sensor data to fault mapping and (2) the lack of sufficient training data. Here, methods are derived and tested in an architecture which addresses these two problems. First, the sensor data to fault mapping is decomposed into three simpler mappings which perform sensor data compression, hypothesis generation, and sensor fusion. Efficient training is performed for each mapping separately. Second, the neural network which performs sensor fusion is structured to detect new unknown faults for which training examples were not presented. These methods were tested on a task of fault detection and identification in the Space Shuttle Main Engine (SSME). Results indicate that the decomposed neural network architecture can be trained efficiently, can identify faults for which it has been trained, and can detect the occurrence of faults for which it has not been trained.

Whitehead, Bruce A.↗

NASA NTRS1990

The theoretical limits of source and channel coding

The theoretical relationship among signal power, distortion, and bandwidth for several source and channel models is presented. The work is intended as a reference for the evaluation of the performance of specific data compression algorithms.

Dolinar, S. J.↗

NASA NTRS1991

Maximum-entropy probability distributions under Lp-norm constraints

Continuous probability density functions and discrete probability mass functions are tabulated which maximize the differential entropy or absolute entropy, respectively, among all probability distributions with a given L sub p norm (i.e., a given pth absolute moment when p is a finite integer) and unconstrained or constrained value set. Expressions for the maximum entropy are evaluated as functions of the L sub p norm. The most interesting results are obtained and plotted for unconstrained (real valued) continuous random variables and for integer valued discrete random variables. The maximum entropy expressions are obtained in closed form for unconstrained continuous random variables, and in this case there is a simple straight line relationship between the maximum differential entropy and the logarithm of the L sub p norm. Corresponding expressions for arbitrary discrete and constrained continuous random variables are given parametrically; closed form expressions are available only for special cases. However, simpler alternative bounds on the maximum entropy of integer valued discrete random variables are obtained by applying the differential entropy results to continuous random variables which approximate the integer valued random variables in a natural manner. All the results are presented in an integrated framework that includes continuous and discrete random variables, constraints on the permissible value set, and all possible values of p. Understanding such as this is useful in evaluating the performance of data compression schemes.

Dolinar, S.↗

NASA NTRS1991

Differential collision cross-sections for atomic oxygen

Differential collision cross-sections of O on N2 and other gases were measured to understand vehicle-environmental contamination effects in orbit. The following subject areas are also covered: groundbased scientific observations of rocket releases during NICARE-1; data compression study for the UVI; science priorities for UV imaging in the mid-1990's; and assessment of optimizations possible in UV imaging systems.

Torr, Douglas G.↗

NASA NTRS1991

Predicting cloud-to-ground lightning with neural networks

A neural network is being trained to predict lightning at Cape Canaveral for periods up to two hours in advance. Inputs consist of ground based field mill data, meteorological tower data, lightning location data, and radiosonde data. High values of the field mill data and rapid changes in the field mill data, offset in time, provide the forecasts or desired output values used to train the neural network through backpropagation. Examples of input data are shown and an example of data compression using a hidden layer in the neural network is discussed.

Barnes, Arnold A., Jr.↗

NASA NTRS1990

Ulysses - An investigation of the polar regions of the heliosphere

This paper describes the Ulysses mission, a cooperative NASA/ESA mission for exploring the heliosphere within 1 to 2 AU of the sun. The nine instruments of the Ulysses spacecraft will collect information continuously, recording and compressing data for a playback through NASA's Deep Space Network. Prominent features of the Ulysses include the 1.65-m parabolic high-gain antenna pointing continuously toward earth, which will provide the earth-to-spacecraft communications link; the Radioisotope Thermoelectric Generator; and the 5.5-m radial boom which will provide an electromagnetically clean environment for certain experiments. Individual studies will include investigations of solar-wind plasma, solar-wind ion composition, cosmic dust, magnetic field, solar X-rays/cosmic gamma ray bursts, energetic-particle composition, low energy ions and electrons, cosmic rays/solar particles, radio and plasma waves, coronal plasma sounding, and gravitational waves.

Meeks, Willis G.↗

NASA NTRS1990

Volcanism in Northwest Ishtar Terra, Venus

Evidence is presented for a previously undocumented volcanic complex in the highlands of NW Ishtar Terra (74 deg N, 313 deg E). The proposed valcanic center is in mountainous banded terrain thought to have been formed by regional compression. Data used include Soviet Venera 15/16 radar images and topography (Fotokarta Veneri B-4, 1987). An attempt is made to assess the place of this feature in the framework of known volcanic landforms of the Lakshmi Planum and to examine the relationships between volcanism and tectonism in this region.

Gaddis, Lisa R.↗

NASA NTRS1992

Efficient Two-Dimensional-FFT Program

Program computes 64 X 64-point fast Fourier transform in less than 17 microseconds. Optimized 64 X 64 Point Two-Dimensional Fast Fourier Transform combines performance of real- and complex-valued one-dimensional fast Fourier transforms (FFT's) to execute two-dimensional FFT and coefficients of power spectrum. Coefficients used in many applications, including analyzing spectra, convolution, digital filtering, processing images, and compressing data. Source code written in C, 8086 Assembly, and Texas Instruments TMS320C30 Assembly languages.

Miko, J.↗

NASA NTRS1992

Discrete sequence prediction and its applications

Learning from experience to predict sequences of discrete symbols is a fundamental problem in machine learning with many applications. We apply sequence prediction using a simple and practical sequence-prediction algorithm, called TDAG. The TDAG algorithm is first tested by comparing its performance with some common data compression algorithms. Then it is adapted to the detailed requirements of dynamic program optimization, with excellent results.

Laird, Philip↗

NASA NTRS1990

Remote sensing science for the Nineties; Proceedings of IGARSS '90 - 10th Annual International Geoscience and Remote Sensing Symposium, University of Maryland, College Park, May 20-24, 1990. Vols. 1, 2, & 3

Various papers on remote sensing (RS) for the nineties are presented. The general topics addressed include: subsurface methods, radar scattering, oceanography, microwave models, atmospheric correction, passive microwave systems, RS in tropical forests, moderate resolution land analysis, SAR geometry and SNR improvement, image analysis, inversion and signal processing for geoscience, surface scattering, rain measurements, sensor calibration, wind measurements, terrestrial ecology, agriculture, geometric registration, subsurface sediment geology, radar modulation mechanisms, radar ocean scattering, SAR calibration, airborne radar systems, water vapor retrieval, forest ecosystem dynamics, land analysis, multisensor data fusion. Also considered are: geologic RS, RS sensor optical measurements, RS of snow, temperature retrieval, vegetation structure, global change, artificial intelligence, SAR processing techniques, geologic RS field experiment, stochastic modeling, topography and Digital Elevation model, SAR ocean waves, spaceborne lidar and optical, sea ice field measurements, millimeter waves, advanced spectroscopy, spatial analysis and data compression, SAR polarimetry techniques. Also discussed are: plant canopy modeling, optical RS techniques, optical and IR oceanography, soil moisture, sea ice back scattering, lightning cloud measurements, spatial textural analysis, SAR systems and techniques, active microwave sensing, lidar and optical, radar scatterometry, RS of estuaries, vegetation modeling, RS systems, EOS/SAR Alaska, applications for developing countries, SAR speckle and texture.

Source record↗

NASA NTRS1990

Information theoretical assessment of image gathering and coding for digital restoration

The process of image-gathering, coding, and restoration is presently treated in its entirety rather than as a catenation of isolated tasks, on the basis of the relationship between the spectral information density of a transmitted signal and the restorability of images from the signal. This 'information-theoretic' assessment accounts for the information density and efficiency of the acquired signal as a function of the image-gathering system's design and radiance-field statistics, as well as for the information efficiency and data compression that are obtainable through the combination of image gathering with coding to reduce signal redundancy. It is found that high information efficiency is achievable only through minimization of image-gathering degradation as well as signal redundancy.

Huck, Friedrich O.↗

NASA NTRS1992

Maximal codeword lengths in Huffman codes

The following question about Huffman coding, which is an important technique for compressing data from a discrete source, is considered. If p is the smallest source probability, how long, in terms of p, can the longest Huffman codeword be? It is shown that if p is in the range 0 less than p less than or equal to 1/2, and if K is the unique index such that 1/F(sub K+3) less than p less than or equal to 1/F(sub K+2), where F(sub K) denotes the Kth Fibonacci number, then the longest Huffman codeword for a source whose least probability is p is at most K, and no better bound is possible. Asymptotically, this implies the surprising fact that for small values of p, a Huffman code's longest codeword can be as much as 44 percent larger than that of the corresponding Shannon code.

Abu-Mostafa, Y. S.↗