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At least 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

A visual detection model for DCT coefficient quantization

The discrete cosine transform (DCT) is widely used in image compression and is part of the JPEG and MPEG compression standards. The degree of compression and the amount of distortion in the decompressed image are controlled by the quantization of the transform coefficients. The standards do not specify how the DCT coefficients should be quantized. One approach is to set the quantization level for each coefficient so that the quantization error is near the threshold of visibility. Results from previous work are combined to form the current best detection model for DCT coefficient quantization noise. This model predicts sensitivity as a function of display parameters, enabling quantization matrices to be designed for display situations varying in luminance, veiling light, and spatial frequency related conditions (pixel size, viewing distance, and aspect ratio). It also allows arbitrary color space directions for the representation of color. A model-based method of optimizing the quantization matrix for an individual image was developed. The model described above provides visual thresholds for each DCT frequency. These thresholds are adjusted within each block for visual light adaptation and contrast masking. For given quantization matrix, the DCT quantization errors are scaled by the adjusted thresholds to yield perceptual errors. These errors are pooled nonlinearly over the image to yield total perceptual error. With this model one may estimate the quantization matrix for a particular image that yields minimum bit rate for a given total perceptual error, or minimum perceptual error for a given bit rate. Custom matrices for a number of images show clear improvement over image-independent matrices. Custom matrices are compatible with the JPEG standard, which requires transmission of the quantization matrix.

Ahumada, Albert J., Jr.↗
NASA NTRS1994

Personal cooling systems: Possibilities and limitations

Personal thermal control by means of gas- or liquid-conditioned garments was developed during the 1960s and has been applied in a variety of aerospace and industrial settings. Both USAF fighter pilots and astronauts are required to wear heavy protective clothing which insulates them from the environment and thus creates stress through storage of metabolic heat. The problem is particularly severe in astronauts who perform heavy physical work during extra-vehicular activity (EVA); without artificial cooling they could reach incapacitating hyperthermia in a matter of minutes. This paper reviews the factors which influence the design of personal cooling systems. An important early step is determination of acceptable heat stress level, taking into account possible interactions of heat stress with other physiological problems such as motion sickness, diminished plasma volume, decompression sickness and acceleration tolerance. Other factors which require consideration include the work schedule, the area to be covered by the cooling garment, and the practicalities of a fixed or body-mounted heat sink and its power source. Nearly every imaginable heat sink has been proposed or tried over the past 30 years, including direct gas systems, phase-change systems with open or closed loops and thermoelectric heat sinks. The latter are now the system of choice for aircraft.

Nunneley, Sarah A.↗
NASA NTRS1993

A visual detection model for DCT coefficient quantization

The discrete cosine transform (DCT) is widely used in image compression, and is part of the JPEG and MPEG compression standards. The degree of compression, and the amount of distortion in the decompressed image are determined by the quantization of the transform coefficients. The standards do not specify how the DCT coefficients should be quantized. Our approach is to set the quantization level for each coefficient so that the quantization error is at the threshold of visibility. Here we combine results from our previous work to form our current best detection model for DCT coefficient quantization noise. This model predicts sensitivity as a function of display parameters, enabling quantization matrices to be designed for display situations varying in luminance, veiling light, and spatial frequency related conditions (pixel size, viewing distance, and aspect ratio). It also allows arbitrary color space directions for the representation of color.

Ahumada, Albert J., Jr.↗
NASA NTRS1993

A high-speed lossless data compression system for space applications

This paper reports on the integration of a lossless data compression/decompression chipset into a space data system architecture. For its compression engine, the data system incorporates the Universal Source Encoder (USE) designed for the NASA/Goddard Space Flight Center. Currently, the data compression testbed generates video frames consisting of 512 lines of 512 pixels having 8-bit resolution. Each image is passed through the USE where the lines are internally partitioned into 16-word blocks. These blocks are adaptively encoded across widely varying entropy levels using a Rice 12-option set coding algorithm. The current system operates at an Input/Output rate of 10 Msamples/s or 80 Mbits/s for each buffered input line. Frame and line synchronization for each image are maintained through the use of uniquely decodable command words. Length information of each variable length compressed image line is also included in the output stream. The data and command information are passed to the next stage of the system architecture through a serial fiber-optic transmitter. The initial segment of this stage consists of packetizer hardware which adds an appropriate CCSDS header to the received source data. An uncompressed mode is optionally available to pass image lines directly to the packetizer hardware. A data decompression testbed has also been developed to confirm the data compression operation.

Miko, Joe↗
NASA NTRS1994

An efficient system for reliably transmitting image and video data over low bit rate noisy channels

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.

Costello, Daniel J., Jr.↗
NASA NTRS1994

Extended duration orbiter medical project countermeasure to reduce post space flight orthostatic intolerance (LBNP) (STS-50/USML-1)

During the STS-50/USML-1 mission and five other Shuttle flights, decompression of the legs and lower abdomen ('lower body negative pressure,' LBNP) was used: (1) to apply a standardized stress to the cardiovascular system, to document the loss of orthostatic function during an extended period in weightlessness, and (2) to test its efficacy as a treatment which may be used to protect astronauts from gravitationally-induced fainting during and after reentry on Space Shuttle flights. The loss of orthostatic tolerance (as determined by LBNP) occured even earlier than indicated by similar testing on Skylab (1973-1974). The treatment was shown to be effective in reversing some of the effects of extended weightlessness on the cardiovascular system for at least one day after treatment.

Charles, John B.↗
NASA NTRS1994

Full-scale testing and analysis of fuselage structure

This paper presents recent results from a program in the Boeing Commercial Airplane Group to study the behavior of cracks in fuselage structures. The goal of this program is to improve methods for analyzing crack growth and residual strength in pressurized fuselages, thus improving new airplane designs and optimizing the required structural inspections for current models. The program consists of full-scale experimental testing of pressurized fuselage panels in both wide-body and narrow-body fixtures and finite element analyses to predict the results. The finite element analyses are geometrically nonlinear with material and fastener nonlinearity included on a case-by-case basis. The analysis results are compared with the strain gage, crack growth, and residual strength data from the experimental program. Most of the studies reported in this paper concern the behavior of single or multiple cracks in the lap joints of narrow-body airplanes (such as 727 and 737 commercial jets). The phenomenon where the crack trajectory is curved creating a 'flap' and resulting in a controlled decompression is discussed.

Miller, M.↗
NASA NTRS1994

Compression of regions in the global advanced very high resolution radiometer 1-km data set

The global advanced very high resolution radiometer (AVHRR) 1-km data set is a 10-band image produced at USGS' EROS Data Center for the study of the world's land surfaces. The image contains masked regions for non-land areas which are identical in each band but vary between data sets. They comprise over 75 percent of this 9.7 gigabyte image. The mask is compressed once and stored separately from the land data which is compressed for each of the 10 bands. The mask is stored in a hierarchical format for multi-resolution decompression of geographic subwindows of the image. The land for each band is compressed by modifying a method that ignores fill values. This multi-spectral region compression efficiently compresses the region data and precludes fill values from interfering with land compression statistics. Results show that the masked regions in a one-byte test image (6.5 Gigabytes) compress to 0.2 percent of the 557,756,146 bytes they occupy in the original image, resulting in a compression ratio of 89.9 percent for the entire image.

Kess, Barbara L.↗
NASA NTRS1994

Planning/scheduling techniques for VQ-based image compression

The enormous size of the data holding and the complexity of the information system resulting from the EOS system pose several challenges to computer scientists, one of which is data archival and dissemination. More than ninety percent of the data holdings of NASA is in the form of images which will be accessed by users across the computer networks. Accessing the image data in its full resolution creates data traffic problems. Image browsing using a lossy compression reduces this data traffic, as well as storage by factor of 30-40. Of the several image compression techniques, VQ is most appropriate for this application since the decompression of the VQ compressed images is a table lookup process which makes minimal additional demands on the user's computational resources. Lossy compression of image data needs expert level knowledge in general and is not straightforward to use. This is especially true in the case of VQ. It involves the selection of appropriate codebooks for a given data set and vector dimensions for each compression ratio, etc. A planning and scheduling system is described for using the VQ compression technique in the data access and ingest of raw satellite data.

Short, Nicholas M., Jr.↗
NASA NTRS1994

End-to-end communication test on variable length packet structures utilizing AOS testbed

This paper describes a communication test, which successfully demonstrated the transfer of losslessly compressed images in an end-to-end system. These compressed images were first formatted into variable length Consultative Committee for Space Data Systems (CCSDS) packets in the Advanced Orbiting System Testbed (AOST). The CCSDS data Structures were transferred from the AOST to the Radio Frequency Simulations Operations Center (RFSOC), via a fiber optic link, where data was then transmitted through the Tracking and Data Relay Satellite System (TDRSS). The received data acquired at the White Sands Complex (WSC) was transferred back to the AOST where the data was captured and decompressed back to the original images. This paper describes the compression algorithm, the AOST configuration, key flight components, data formats, and the communication link characteristics and test results.

Miller, Warner H.↗
NASA NTRS1994

Learning random networks for compression of still and moving images

Image compression for both still and moving images is an extremely important area of investigation, with numerous applications to videoconferencing, interactive education, home entertainment, and potential applications to earth observations, medical imaging, digital libraries, and many other areas. We describe work on a neural network methodology to compress/decompress still and moving images. We use the 'point-process' type neural network model which is closer to biophysical reality than standard models, and yet is mathematically much more tractable. We currently achieve compression ratios of the order of 120:1 for moving grey-level images, based on a combination of motion detection and compression. The observed signal-to-noise ratio varies from values above 25 to more than 35. The method is computationally fast so that compression and decompression can be carried out in real-time. It uses the adaptive capabilities of a set of neural networks so as to select varying compression ratios in real-time as a function of quality achieved. It also uses a motion detector which will avoid retransmitting portions of the image which have varied little from the previous frame. Further improvements can be achieved by using on-line learning during compression, and by appropriate compensation of nonlinearities in the compression/decompression scheme. We expect to go well beyond the 250:1 compression level for color images with good quality levels.

Gelenbe, Erol↗
NASA NTRS1995

Rapid deceleration mode evaluation

Aircraft with flight capability above 1.4 normally have an RPM lockup or similar feature to prevent inlet buzz that would occur at low engine airflows. This RPM lockup has the effect of holding the engine thrust level at the intermediate power (maximum non-afterburning). For aircraft such as military fighters or supersonic transports, the need exists to be able to rapidly slow from supersonic to subsonic speeds. For example, a supersonic transport that experiences a cabin decompression needs to be able to slow/descend rapidly, and this requirement may size the cabin environmental control system. For a fighter, there may be a desire to slow/descend rapidly, and while doing so to minimize fuel usage and engine exhaust temperature. Both of these needs can be aided by achieving the minimum possible overall net propulsive force. As the intermediate power thrust levels of engines increase, it becomes even more difficult to slow rapidly from supersonic speeds. Therefore, a mode of the performance seeking control (PSC) system to minimize overall propulsion system thrust has been developed and tested. The rapid deceleration mode reduces the engine airflow consistent with avoiding inlet buzz. The engine controls are trimmed to minimize the thrust produced by this reduced airflow, and moves the inlet geometry to degrade the inlet performance. As in the case of the other PSC modes, the best overall performance (in this case the least net propulsive force) requires an integrated optimization of inlet, engine, and nozzle variables. This paper presents the predicted and measured results for the supersonic minimum thrust mode, including the overall effects on aircraft deceleration.

Conners, Timothy R.↗
NASA NTRS1995

A comparison of model-based VQ compression with other VQ approaches

In our previous work on Model-Based Vector Quantization (MVQ), we presented some performance comparisons (both rate distortion and decompression time) with VQ and JPEG/DCT. In this paper, we compare the MVQ's rate distortion performance with Mean Removed Vector Quantization (MRVQ) and include our previous comparison with VQ. MVQ is similar to MRVQ in many ways. Both of these techniques extract means of the vectors (raster-scanned image blocks) and reduce them to mean removed residuals by subtracting block means from the elements of the vectors. In the case of MRVQ, a codebook of residual vectors is generated using a training set. For every vector from the input image, the block mean and address of the codevector from the codebook that matches the input vector closest are transmitted to the decoder. The codebook is generated using generalized Lloyd algorithm on training set of residual vectors. For MVQ the pairs consist of vector means and address of the closest matching vector from codebook generated by models based on statistical properties of the residuals and Human Visual System (HVS). In our experiments, we found that MVQ performance in rate distortion sense is almost always better than VQ and is comparable to MRVQ. Further, MVQ is much easier to use than either VQ or MRVQ, since the training and managing of explicit codebooks is not required.

Manohar, Mareboyana↗
NASA NTRS1995

A comparison of model-based VQ compression with other VQ approaches

In our previous work on Model-Based Vector Quantization (MVQ), we presented some performance comparisons (both rate distortion and decompression time) with VQ and JPED/DCT. In this paper, we compare the MVQ's rate distortion performance with Mean Removed Vector Quantization (MRVQ) and include our previous comparison with VQ. Both MVQ and MRVQ compute the mean of each vector (raster-scanned image block) and produce mean removed residual vectors by subtracting the block mean from the elements of each vector. In the case of MRVQ, a codebook of residual vectors is generated using a training set. For MVQ, an internal codebook is generated based on the statistical properties of the residual vectors, and upon correlations derived from a Human Visual System (HVS) model. In both MVQ and MRVQ, the block mean and address of the codevector from the codebook that most closely matches each input vector are transmitted to the decoder. MVQ, a single additional statistical parameter is transmitted to the decoder. For MRVQ, we assume that the codebook of residual vectors is available to the decoder. In our experiments, we found that the rate of distortion performance of MVQ is almost always better than VQ, and is comparable to MRVQ. Further, MVQ is much easier to use than either VQ or MRVQ, since the training and management of codebooks is not required.

Manohar, Mareboyana↗
NASA NTRS1996

Quantifying Danger To Spacecraft Crews From Orbital Debris

MSCSurv computer program designed to quantify conditional probability of losing one or more crew members following remote likelihood of penetration of orbital debris into cluster of spacecraft modules containing crew members. Contributions to probability of losing one or more crew members quantified from three significant penetration-induced hazards: rupture of pressure wall (explosive decompression), injuries induced by fragments, and "slow" depressurization. Uses Monte Carlo-style subroutine to simulate penetration of thousands of orbital debris particles of various sizes, velocities, and angles of approach into spacecraft of selected exterior geometry. Written in FORTRAN 77.

Williamsen, Joel↗
NASA NTRS1996

Software For Converting SAR Data Formats

CVERT computer program converts AIRSAR data to SIR-C format, or converts SIR-C data to AIRSAR format. Spaceborne Image Radar-C (SIR-C) successfully images areas at many sites around world. SIRC CEOS-READER software package (NPO-19463, NPO-19543) required for reading CEOS headers and decompressing SIR-C data. Written in FORTRAN 77.

Chapman, Bruce↗
NASA NTRS1996

Digital Data Registration and Differencing Compression System

A process for X-ray registration and differencing results in more efficient compression. Differencing of registered modeled subject image with a modeled reference image forms a differenced image for compression with conventional compression algorithms. Obtention of a modeled reference image includes modeling a relatively unrelated standard reference image upon a three-dimensional model, which three-dimensional model is also used to model the subject image for obtaining the modeled subject image. The registration process of the modeled subject image and modeled reference image translationally correlates such modeled images for resulting correlation thereof in spatial and spectral dimensions. Prior to compression, a portion of the image falling outside a designated area of interest may be eliminated, for subsequent replenishment with a standard reference image. The compressed differenced image may be subsequently transmitted and/or stored, for subsequent decompression and addition to a standard reference image so as to form a reconstituted or approximated subject image at either a remote location and/or at a later moment in time. Overall effective compression ratios of 100:1 are possible for thoracic X-ray digital images.

Ransford, Gary A.↗
NASA NTRS1997

Intelligent System Development Using a Rough Sets Methodology

The purpose of this research was to examine the potential of the rough sets technique for developing intelligent models of complex systems from limited information. Rough sets a simple but promising technology to extract easily understood rules from data. The rough set methodology has been shown to perform well when used with a large set of exemplars, but its performance with sparse data sets is less certain. The difficulty is that rules will be developed based on just a few examples, each of which might have a large amount of noise associated with them. The question then becomes, what is the probability of a useful rule being developed from such limited information? One nice feature of rough sets is that in unusual situations, the technique can give an answer of 'I don't know'. That is, if a case arises that is different from the cases the rough set rules were developed on, the methodology can recognize this and alert human operators of it. It can also be trained to do this when the desired action is unknown because conflicting examples apply to the same set of inputs. This summer's project was to look at combining rough set theory with statistical theory to develop confidence limits in rules developed by rough sets. Often it is important not to make a certain type of mistake (e.g., false positives or false negatives), so the rules must be biased toward preventing a catastrophic error, rather than giving the most likely course of action. A method to determine the best course of action in the light of such constraints was examined. The resulting technique was tested with files containing electrical power line 'signatures' from the space shuttle and with decompression sickness data.

Anderson, Gray T.↗