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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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The real-time operational requirements for SARCOM translation into a high speed image data handler and processor to achieve the desired compression ratios and the selection of a suitable image data compression technique with as low as possible fidelity (information) losses and which can be implemented in an algorithm placing a relatively low arithmetic load on the system are described.
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.
A task order was written by the High Resolution, High Frame Rate Video Technology (HHVT) project engineers to investigate data compression techniques that could be applied to the HHVT system, and both existing and planned downlink/uplink capabilities of the Space Shuttle and Space Station Freedom. The following tasks were included: (1) Investigate signal channel availability and determine both the maximum possible data rate and the average data rate; (2) Identify time blocks for HHVT video transmission assuming time sharing and interruptions in the communication links; (3) Determine the bit error rates to be expected; and (4) Define the transmit and receive interfaces. A summary chart of the data transmission capabilities for Tracking and Data Relay Satellite System (TDRSS), the Space Shuttle, Space Station Freedom, Spacelab, and USLab are also presented.
Numerous design concepts, materials, and manufacturing methods were investigated for the covers and spars of a transport box wing. Cover panels and spar segments were fabricated and tested to verify the structural integrity of design concepts and fabrication techniques. Compression tests on stiffened panels demonstrated the ability of graphite/epoxy wing upper cover designs to achieve a 35 percent weight savings compared to the aluminum baseline. The impact damage tolerance of the designs and materials used for these panels limits the allowable compression strain and therefore the maximum achievable weight savings. Bending and shear tests on various spar designs verified an average weight savings of 37 percent compared to the aluminum baseline. Impact damage to spar webs did not significantly degrade structural performance. Predictions of spar web shear instability correlated well with measured performance. The structural integrity of spars manufactured by filament winding equalled or exceeded those fabricated by hand lay-up. The information obtained will be applied to the design, fabrication, and test of a full-scale section of a wing box. When completed, the tests on the technology integration box beam will demonstrate the structural integrity of an advanced composite wing design which is 25 percent lighter than the metal baseline.
Trapping of magnetic fields and subsequent flux compression have been realized in sintered bulk Ba2YCu3O7 superconductors at 77 K. The field is trapped in two interconnected holes of 0.95-cm and 0.52-cm diameter, respectively. By inserting a superconducting plunger with a diameter of 0.93 cm into the larger hole, the trapped flux is compressed into the smaller hole, where the flux density is measured with a Hall probe. The ratio of the areas available for the magnetic flux before and after compression is 3.7. Deviations from this compression ratio are observed to increase as the trapped field is increased, demonstrating penetration of magnetic flux into the interior of the superconductor. Using a simple extension of the critical state model, the authors demonstrate how the flux compression technique can be used to test the validity of the model and also to calculate the critical current density of the superconductor directly from the measurements.
Soon after space and Earth science data is collected, it is stored in one or more archival facilities for later retrieval and analysis. Since the purpose of the archival process is to keep an accurate and complete record of data, any data compression used in an archival system must be lossless, and protect against propagation of error in the storage media. A browse capability for space and Earth science data is needed to enable scientists to check the appropriateness and quality of particular data sets before obtaining the full data set(s) for detailed analysis. Browse data produced for these purposes could be used to facilitate the retrieval of data from an archival facility. Quick-look data is data obtained directly from the sensor for either previewing the data or for an application that requires very timely analysis of the space or Earth science data. Two main differences between data compression techniques appropriate to browse and quick-look cases, are that quick-look can be more specifically tailored, and it must be limited in complexity by the relatively limited computational power available on space platforms.
The semiannual report is included. Topics covered include communication, information science, data compression, remote sensing, color mapped images, robust coding scheme for packet video, recursively indexed differential pulse code modulation, image compression technique for use on token ring networks, and joint source/channel coder design.
A survey of current data compression techniques which are being used to reduce the amount of data in remote sensing applications is provided. The survey aspect is far from complete, reflecting the substantial activity in this area. The purpose of the survey is more to exemplify the different approaches being taken rather than to provide an exhaustive list of the various proposed approaches.
The High Density Digital Data Storage System was designed to provide a cost effective means for storing real-time data from the field-deployable digital acoustic measurement system. However, the high density data storage system is a standalone system that could provide a storage solution for many other real time data acquisition applications. The storage system has inputs for up to 20 channels of 16-bit digital data. The high density tape recorders presently being used in the storage system are capable of storing over 5 gigabytes of data at overall transfer rates of 500 kilobytes per second. However, through the use of data compression techniques the system storage capacity and transfer rate can be doubled. Two tape recorders have been incorporated into the storage system to produce a backup tape of data in real-time. An analog output is provided for each data channel as a means of monitoring the data as it is being recorded.
Recent experience with airborne imaging spectrometers demonstrated the advantages of narrow band sensors over broad band scanners for characterizing the nature, extent, and physical status of typical land surfaces. Information on key spectral features associated with various land surfaces can be obtained from the data of such instruments, which can be used to simulate spaceborne imaging spectrometer data and to assess their information content if comprehensive underpinning is provided by ground data. The collection of such information was an issue of airborne imaging spectrometer campaigns like the NASA MAC-Europe 1991. Airborne and ground data obtained from different test sites in Europe are utilized for a comparative analysis of the spectral signatures of various land surfaces (vegetation, bare soils and rocks, and mixed soil/rock-vegetation) as seen from different imaging spectrometers like Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), GERIS 63 band scanner, and CASI. The following items are discussed: (1) the significance of different spectral regions within the wavelength interval between 0.4 m and 2.5 m for the differentiation of different land units; (2) recommendations on the optimum band selection and band-widths to be used for the application of future satellite-based imaging spectrometers for land applications; (3) the boundaries for the detection of plant features in mixed-soil plant spectra and the influence of different soil properties on the mixture of the spectra; (4) recommendations on the optimum spatial resolution and recording dates for the discrimination of spectral features of various surface types; and (5) evaluation of different data compressing techniques for the optimum extraction of spectral information from imaging spectrometry data.
This paper first provides an overview of an adaptive, lossless, data compression algorithm originally devised by Rice in the early '70s. It then reports the development of a VLSI encoder/decoder chip set developed which implements this algorithm. A recent effort in making a space qualified version of the encoder is described along with several enhancements to the algorithm. The performance of the enhanced algorithm is compared with those from other currently available lossless compression techniques on multiple sets of test data. The results favor our implemented technique in many applications.
A VLSI architecture for an adaptive data compression encoder capable of sustaining fixed or variable bit-rate output has been developed. There are three modes of operation: lossless with variable bit-rate, lossy with fixed bit-rate and lossy with variable bit-rate. For lossless encoding, the implementation is identical to the USES chip designed for Landsat 7. Obtaining a fixed bit-rate is achieved with a lossy DPCM algorithm using adaptive, nonuniform scalar quantization. In lossy mode, variable bit-rate coding uses the lossless sections of the encoder for post-DPCM entropy coding. The encoder shows excellent compression performance in comparison to other current data compression techniques. No external tables or memory are required for operation.
Methods are needed for evaluating the quality of augmented visual displays (AVID). Computational quality metrics will help summarize, interpolate, and extrapolate the results of human performance tests with displays. The FLM Vision group at NASA Ames has been developing computational models of visual processing and using them to develop computational metrics for similar problems. For example, display modeling systems use metrics for comparing proposed displays, halftoning optimizing methods use metrics to evaluate the difference between the halftone and the original, and image compression methods minimize the predicted visibility of compression artifacts. The visual discrimination models take as input two arbitrary images A and B and compute an estimate of the probability that a human observer will report that A is different from B. If A is an image that one desires to display and B is the actual displayed image, such an estimate can be regarded as an image quality metric reflecting how well B approximates A. There are additional complexities associated with the problem of evaluating the quality of radar and IR enhanced displays for AVID tasks. One important problem is the question of whether intruding obstacles are detectable in such displays. Although the discrimination model can handle detection situations by making B the original image A plus the intrusion, this detection model makes the inappropriate assumption that the observer knows where the intrusion will be. Effects of signal uncertainty need to be added to our models. A pilot needs to make decisions rapidly. The models need to predict not just the probability of a correct decision, but the probability of a correct decision by the time the decision needs to be made. That is, the models need to predict latency as well as accuracy. Luce and Green have generated models for auditory detection latencies. Similar models are needed for visual detection. Most image quality models are designed for static imagery. Watson has been developing a general spatial-temporal vision model to optimize video compression techniques. These models need to be adapted and calibrated for AVID applications.
A number of quality measures are evaluated for gray scale image compression. They are all bivariate exploiting the differences between corresponding pixels in the original and degraded images. It is shown that although some numerical measures correlate well with the observers' response for a given compression technique, they are not reliable for an evaluation across different techniques. The two graphical measures (histograms and Hosaka plots), however, can be used to appropriately specify not only the amount, but also the type of degradation in reconstructed images.
A focus on qualitative methods of presenting data shows that visualization provides a mechanism for browsing independent of the source of data and is an effective alternative to traditional image-based browsing of image data. To be generally applicable, such visualization methods, however, must be based upon an underlying data model with support for a broad class of data types and structures. Interactive, near-real-time browsing for data sets of interesting size today requires a browse server of considerable power. A symmetric multi-processor with very high internal and external bandwidth demonstrates the feasibility of this concept. Although this technology is likely to be available on the desktop within a few years, the increase in the size and complexity of achieved data will continue to exceed the capacity of 'worksation' systems. Hence, a higher class of performance, especially in bandwidth, will generally be required for on-demand browsing. A few experiments with differing digital compression techniques indicates that a MPEG-1 implementation within the context of a high-performance browse server (i.e., parallized) is a practical method of converting a browse product to a form suitable for network or CD-ROM distribution.
This research project is intended to develop an efficient system for reliably transmitting image and video data over low bit rate noisy channels. The basic ideas behind the proposed approach are the following: employ statistical-based image modeling to facilitate pre- and post-processing and error detection, use spare redundancy that the source compression did not remove to add robustness, and implement coded modulation to improve bandwidth efficiency and noise rejection. Over the last six months, progress has been made on various aspects of the project. Through our studies of the integrated system, a list-based iterative Trellis decoder has been developed. The decoder accepts feedback from a post-processor which can detect channel errors in the reconstructed image. The error detection is based on the Huber Markov random field image model for the compressed image. The compression scheme used here is that of JPEG (Joint Photographic Experts Group). Experiments were performed and the results are quite encouraging. The principal ideas here are extendable to other compression techniques. In addition, research was also performed on unequal error protection channel coding, subband vector quantization as a means of source coding, and post processing for reducing coding artifacts. Our studies on unequal error protection (UEP) coding for image transmission focused on examining the properties of the UEP capabilities of convolutional codes. The investigation of subband vector quantization employed a wavelet transform with special emphasis on exploiting interband redundancy. The outcome of this investigation included the development of three algorithms for subband vector quantization. The reduction of transform coding artifacts was studied with the aid of a non-Gaussian Markov random field model. This results in improved image decompression. These studies are summarized and the technical papers included in the appendices.
The Students for the Exploration and Development of Space Satellite (SEDSAT-1) is an ambitious project to design, build, and fly a generally-accessible low-cost satellite which will 1) act as a technology demonstration to verify the suitability of novel optical, battery, microprocessor, and memory hardware for space flight environments, (2) to advance the understanding of tether dynamics and environmental science through the development of advanced imaging experiments, (3) to act as a communication link for radio amateurs, and (4) to provide graduate and undergraduate students with a unique multi-disciplinary experience in designing complex real-world hardware/software. This report highlights the progress made on this project during the time period from January 2, 1996 to June 1, 1996 at the end of which time the SEASIS 0.7 version software was completed and integrated on the SEASIS breadboard, a functional prototype of the Panoramic Annual Lenses (PAL) camera was developed, the preferred image compression technique was selected, the layout of the SEASIS board was begun, porting of the SCOS operating system to the command data system (CDS) board was begun, a new design for a tether release mechanism was developed, safety circuitry to inhibit tether cutting was developed and prototyped, material was prepared to support a comprehensive safety review of the project which was held at Johnson Space Center (JSC) (which was personally attended by one of the Principal Investigators), and prototype ground software was developed.
Over the last 25 years, a tremendous progress has been made in the Earth science space-based remote sensing observations, technologies and algorithms. Such advancements have improved the predictability by providing lead-time and accuracy of forecast in weather, climate, natural hazards, and natural resources. It has further reduced or bounded the overall uncertainties by partially improving our understanding of planet Earth as an integrated system that is governed by non-linear and chaotic behavior. Many countries such US, European Community, Japan, China and others have invested billions of dollars in developing and launching space-based assets in the low earth (LEO) and geostationary (GEO) orbits. However, the wealth of this scientific knowledge that has potential of extracting monumental socio-economic benefits from such large investments have been slow in reaching to public and decision makers. For instance, there are a number of areas such as energy forecasting, aviation safety, agricultural competitiveness, disaster management, security, air quality and public health can directly take advantage. Nevertheless, we all live in a global economy that depends on access to the best available Earth Science information for all inhabitants of this planet. This paper surveys and examines a number such applications in terms of their architecture, maturity and economic applicability as they apply to the societal needs. A detailed analysis is also presented of various challenges and issues that pertain to a number of areas such as: (1) difficulties in making a speedy transition of data and information from observations and models to relevant Decision Support Systems (DSS) or tools, (2) data and models inter-operability issues, (3) limitations of spatial, spectral and temporal resolution, (4) communication limitations as dictated by the availability of image processing and data compression techniques. Additionally, the most critical element amongst all is the organizational and management boundaries that must be resolved at local, state, national and international levels to implement and realize free flow of such vital information. This paper also makes attempts to address this topic and discuss possible approaches to deal with this quandary.