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At least 109 records · Page 6

An adaptive technique to maximize lossless image data compression of satellite images

Data compression will pay an increasingly important role in the storage and transmission of image data within NASA science programs as the Earth Observing System comes into operation. It is important that the science data be preserved at the fidelity the instrument and the satellite communication systems were designed to produce. Lossless compression must therefore be applied, at least, to archive the processed instrument data. In this paper, we present an analysis of the performance of lossless compression techniques and develop an adaptive approach which applied image remapping, feature-based image segmentation to determine regions of similar entropy and high-order arithmetic coding to obtain significant improvements over the use of conventional compression techniques alone. Image remapping is used to transform the original image into a lower entropy state. Several techniques were tested on satellite images including differential pulse code modulation, bi-linear interpolation, and block-based linear predictive coding. The results of these experiments are discussed and trade-offs between computation requirements and entropy reductions are used to identify the optimum approach for a variety of satellite images. Further entropy reduction can be achieved by segmenting the image based on local entropy properties then applying a coding technique which maximizes compression for the region. Experimental results are presented showing the effect of different coding techniques for regions of different entropy. A rule-base is developed through which the technique giving the best compression is selected. The paper concludes that maximum compression can be achieved cost effectively and at acceptable performance rates with a combination of techniques which are selected based on image contextual information.

Stewart, Robert J.↗

Exploring the Mass-loss Histories of the Red Supergiants

We report mid- to far-infrared imaging and photometry from 7 to 37 μm with SOFIA/FORCAST and 2 μm adaptive optics imaging with LBTI/LMIRCam of a large sample of red supergiants (RSGs) in four Galactic clusters: RSGC1, RSGC2 = Stephenson 2, RSGC3, and NGC 7419. The RSGs in these clusters cover their expected range in luminosity and initial mass from ≈9 to more than 25 M {sub ⊙}. The population includes examples of very late-type RSGs such as MY Cep, which may be near the end of the RSG stage, high-mass-losing maser sources, yellow hypergiants, and post-RSG candidates. Many of the stars and almost all of the most luminous have spectral energy distributions (SEDs) with extended infrared excess radiation at the longest wavelengths. To best model their SEDs, we use the DUSTY code with a variable radial density distribution function to estimate their mass-loss rates. Our M-dot –luminosity relation for 42 RSGs basically follows the classical de Jager curve, but at luminosities below 10{sup 5} L{sub ⊙}, we find a significant population of RSGs with M-dot below the de Jager relation. At luminosities above 10{sup 5} L {sub ⊙}, there is a rapid transition to higher mass-loss rates that approximates and overlaps the de Jager curve. We recommend that instead of using a linear relation or single curve, the empirical M-dot –luminosity relation is better represented by a broad band. Interestingly, the transition to much higher M-dot at about 10{sup 5} L {sub ⊙} corresponds approximately to an initial mass of 18–20 M {sub ⊙}, which is close to the upper limit for RSGs becoming Type II supernovae.

79 ASTRONOMY AND ASTROPHYSICS↗

Advanced technology optical telescopes IV; Proceedings of the Meeting, Tucson, AZ, Feb. 12-16, 1990. Parts 1 & 2

The present conference on the current status of large, advanced-technology optical telescope development and construction projects discusses topics on such factors as their novel optical system designs, the use of phased arrays, seeing and site performance factors, mirror fabrication and testing, pointing and tracking techniques, mirror thermal control, structural design strategies, mirror supports and coatings, and the control of segmented mirrors. Attention is given to the proposed implementation of the VLT Interferometer, the first diffraction-limited astronomical images with adaptive optics, a fiber-optic telescope using a large cross-section image-transmitting bundle, the design of wide-field arrays, Hartmann test data reductions, liquid mirrors, inertial drives for telescope pointing, temperature control of large honeycomb mirrors, evaporative coatings for very large telescope mirrors, and the W. M. Keck telescope's primary mirror active control system software.

Barr, Lawrence D.↗

High-Resolution Detector For X-Ray Diffraction

Proposed x-ray-sensitive imaging detector offers superior spatial resolution, counting-rate capacity, and dynamic range. Instrument based on laser-stimulated luminescence and reusable x-ray-sensitive film. Detector scans x-ray film line by line. Extracts latent image in film and simultaneously erases film for reuse. Used primarily for protein crystallography. Principle adapted to imaging detectors for electron microscopy and fluorescence spectroscopy and general use in astronomy, engineering, and medicine.

Carter, Daniel C.↗

Implementation of Multispectral Image Classification on a Remote Adaptive Computer

As the demand for higher performance computers for the processing of remote sensing science algorithms increases, the need to investigate new computing paradigms its justified. Field Programmable Gate Arrays enable the implementation of algorithms at the hardware gate level, leading to orders of m a,gnitude performance increase over microprocessor based systems. The automatic classification of spaceborne multispectral images is an example of a computation intensive application, that, can benefit from implementation on an FPGA - based custom computing machine (adaptive or reconfigurable computer). A probabilistic neural network is used here to classify pixels of of a multispectral LANDSAT-2 image. The implementation described utilizes Java client/server application programs to access the adaptive computer from a remote site. Results verify that a remote hardware version of the algorithm (implemented on an adaptive computer) is significantly faster than a local software version of the same algorithm implemented on a typical general - purpose computer).

Figueiredo, Marco A.↗

Validation of Image-Based Neural Network Controllersthrough Adaptive Stress Testing

Neural networks have become state-of-the-art for computer vision problems because of their ability to efficiently model complex functions from large amounts of data. While neural networks can be shown to perform well empirically fora variety of tasks, their performance is difficult to guarantee.Neural network verification tools have been developed that can certify robustness with respect to a given input image; however,for neural network systems used in closed-loop controllers,robustness with respect to individual images does not address multi-step properties of the neural network controller and itsenvironment. Furthermore, neural network systems interacting in the physical world and using natural images are operating in a black-box environment, making formal verification in-tractable. This work combines the adaptive stress testing (AST)framework with neural network verification tools to search for the most likely sequence of image disturbances that cause the neural network controlled system to reach a failure. Anautonomous aircraft taxi application is presented, and results show that the AST method finds failures with more likely image disturbances than baseline methods. Further analysis of AST results revealed an explainable cause of the failure, giving insight into the problematic scenarios that should be addressed.

Adaptive Stress Testing, Marabou, Deep Neural Netw↗

Infrared Astronomy with Arrays: The Next Generation; Sunset Village, Los Angeles, CA, Oct. 1993

Conference papers on infrared array techniques and methods for infrared astronomy are presented. Topics covered include the following: infrared telescopes; infrared spectrometers; spaceborne astronomy; astronomical observatories; infrared cameras; imaging techniques; sky surveys; infrared photography; infrared photometry; infrared spectroscopy; equipment specifications; data processing and analysis; control systems; cryogenic equipment; adaptive optics; image resolution; infrared detector materials; and focal plane arrays.

Mclean, Ian S.↗

Electronic photography at NASA Langley Research Center

The field of photography began a metamorphosis several years ago which promises to fundamentally change how images are captured, transmitted, and output. At this time the metamorphosis is still in the early stages, but already new processes, hardware, and software are allowing many individuals and organizations to explore the entry of imaging into the information revolution. Exploration at this time is prerequisite to leading expertise in the future, and a number of branches at LaRC have ventured into electronic and digital imaging. Their progress until recently has been limited by two factors: the lack of an integrated approach and the lack of an electronic photographic capability. The purpose of the research conducted was to address these two items. In some respects, the lack of electronic photographs has prevented application of an integrated imaging approach. Since everything could not be electronic, the tendency was to work with hard copy. Over the summer, the Photographics Section has set up an Electronic Photography Laboratory. This laboratory now has the capability to scan film images, process the images, and output the images in a variety of forms. Future plans also include electronic capture capability. The current forms of image processing available include sharpening, noise reduction, dust removal, tone correction, color balancing, image editing, cropping, electronic separations, and halftoning. Output choices include customer specified electronic file formats which can be output on magnetic or optical disks or over the network, 4400 line photographic quality prints and transparencies to 8.5 by 11 inches, and 8000 line film negatives and transparencies to 4 by 5 inches. The problem of integrated imaging involves a number of branches at LaRC including Visual Imaging, Research Printing and Publishing, Data Visualization and Animation, Advanced Computing, and various research groups. These units must work together to develop common approaches to image processing and archiving. The ultimate goal is to be able to search for images using an on-line database and image catalog. These images could then be retrieved over the network as needed, along with information on the acquisition and processing prior to storage. For this goal to be realized, a number of standard processing protocols must be developed to allow the classification of images into categories. Standard series of processing algorithms can then be applied to each category (although many of these may be adaptive between images). Since the archived image files would be standardized, it should also be possible to develop standard output processing protocols for a number of output devices. If LaRC continues the research effort begun this summer, it may be one of the first organizations to develop an integrated approach to imaging. As such, it could serve as a model for other organizations in government and the private sector.

Holm, Jack M.↗

Distributed Tomographic Reconstruction with Quantization

Conventional tomographic reconstruction typically depends on centralized servers for both data storage and computation, leading to concerns about memory limitations and data privacy. Distributed reconstruction algorithms mitigate these issues by partitioning data across multiple nodes, reducing server load and enhancing privacy. However, these algorithms often encounter challenges related to memory constraints and communication overhead between nodes. In this paper, we introduce a decentralized Alternating Directions Method of Multipliers (ADMM) with configurable quantization. By distributing local objectives across nodes, our approach is highly scalable and can efficiently reconstruct images while adapting to available resources. To overcome communication bottlenecks, we propose two quantization techniques based on K-means clustering and JPEG compression. Numerical experiments with benchmark images illustrate the tradeoffs between communication efficiency, memory use, and reconstruction accuracy.

Miao, Runxuan↗

Constraints on the Progenitor System of the Type Ia Supernova 2014J from Pre-Explosion Hubble Space Telescope Imaging

We constrain the properties of the progenitor system of the highly reddened Type Ia supernova (SN Ia) 2014J in Messier 82 (M82; d (is) approx. 3.5 Mpc). We determine the supernova (SN) location using Keck-II K-band adaptive optics images, and we find no evidence for flux from a progenitor system in pre-explosion near-ultraviolet through near-infrared Hubble Space Telescope (HST) images. Our upper limits exclude systems having a bright red giant companion, including symbiotic novae with luminosities comparable to that of RS Ophiuchi. While the flux constraints are also inconsistent with predictions for comparatively cool He-donor systems (T (is) approximately 35,000 K), we cannot preclude a system similar to V445 Puppis. The progenitor constraints are robust across a wide range of RV and AV values, but significantly greater values than those inferred from the SN light curve and spectrum would yield proportionally brighter luminosity limits. The comparatively faint flux expected from a binary progenitor system consisting of white dwarf stars would not have been detected in the pre-explosion HST imaging. Infrared HST exposures yield more stringent constraints on the luminosities of very cool (T (is) less than 3000 K) companion stars than was possible in the case of SN Ia 2011fe.

RS Ophiuchi↗

Cleaning Images with Gaussian Process Regression

Many approaches to astronomical data reduction and analysis cannot tolerate missing data: corrupted pixels must first have their values imputed. This paper presents astrofix, a robust and flexible image imputation algorithm based on Gaussian process regression. Through an optimization process, astrofix chooses and applies a different interpolation kernel to each image, using a training set extracted automatically from that image. It naturally handles clusters of bad pixels and image edges and adapts to various instruments and image types. For bright pixels, the mean absolute error of astrofix is several times smaller than that of median replacement and interpolation by a Gaussian kernel. We demonstrate good performance on both imaging and spectroscopic data, including the SBIG 6303 0.4 m telescope and the FLOYDS spectrograph of Las Cumbres Observatory and the CHARIS integral-field spectrograph on the Subaru Telescope.

42 ENGINEERING↗

An Automatic Phase-Change Detection Technique for Colloidal Hard Sphere Suspensions

Colloidal suspensions of monodisperse spheres are used as physical models of thermodynamic phase transitions and as precursors to photonic band gap materials. However, current image analysis techniques are not able to distinguish between densely packed phases within conventional microscope images, which are mainly characterized by degrees of randomness or order with similar grayscale value properties. Current techniques for identifying the phase boundaries involve manually identifying the phase transitions, which is very tedious and time consuming. We have developed an intelligent machine vision technique that automatically identifies colloidal phase boundaries. The algorithm utilizes intelligent image processing techniques that accurately identify and track phase changes vertically or horizontally for a sequence of colloidal hard sphere suspension images. This technique is readily adaptable to any imaging application where regions of interest are distinguished from the background by differing patterns of motion over time.

McDowell, Mark↗

Hyperspectral Infrared Imaging of Flames Using a Spectrally Scanning Fabry-Perot Filter

The temperatures and compositions of gases in and around flames can be diagnosed using infrared emission spectroscopy to observe molecular band shapes and intensities. We have combined this approach with a low-order scanning Fabry-Perot filter and an infrared camera to obtain spectrally scanned infrared emission images of a laboratory flame and exhaust plume from 3.7 to 5.0 micrometers, at a spectral resolution of 0.043 micrometers, and a spatial resolution of 1 mm. The scanning filter or AIRIS (Adaptive Infrared Imaging Spectroradiometer) is a Fabry-Perot etalon operating in low order (mirror spacing = wavelength) such that the central spot, containing a monochromatic image of the scene, is viewed by the detector array. The detection system is a 128 x 128 liquid-nitrogen-cooled InSb focal plane array. The field of view is controlled by a 50 mm focal length multielement lens and an V4.8 aperture, resulting in an image 6.4 x 6.4 cm in extent at the flame and a depth of field of approximately 4 cm. Hyperspectral images above a laboratory CH4/air flame show primarily the strong emission from CO2 at 4.3 micrometers, and weaker emissions from CO and H2O. We discuss techniques to analyze the spectra, and plans to use this instrument in microgravity flame spread experiments.

Rawlins, W. T.↗

Toward implementing autonomous adaptive data acquisition for scanning hyperspectral imaging of biological systems

Autonomous experimentation is an emerging area of research, primarily related to autonomous vehicles, scientific combinatorial discovery approaches in materials science and drug discovery, and iterative research loops of planning, experimentation, and analysis. However, autonomous approaches developed in these contexts are difficult to apply to high-dimensional mapping technologies, such as scanning hyperspectral imaging of biological systems, due to sample complexity and heterogeneity. We briefly cover the history of adaptive sampling algorithms and surrogate modeling in order to define autonomous adaptive data acquisition as an objective-based, flexible building block for future biological imaging experimentation driven by intelligent infrastructure. We subsequently summarize the recent implementations of autonomous adaptive data acquisition (AADA) for scanning hyperspectral imaging, assess how these address the difficulties of autonomous approaches in hyperspectral imaging, and highlight the AADA design variation from a goal-oriented perspective. Finally, we present a modular AADA architecture that embeds AADA-driven flexible building blocks to address the challenge of time resolution for high-dimensional scanning hyperspectral imaging of nonequilibrium dynamical systems. In our example research-driven experimental design case, we propose an AADA infrastructure for time-resolved, noninvasive, and label-free scanning hyperspectral imaging of living biological systems. This AADA infrastructure can accurately target the correct state of the system for experimental workflows that utilize subsequent expensive, high-information-content analytical techniques.

59 BASIC BIOLOGICAL SCIENCES↗

A High Angular Resolution Survey of Massive Stars in Cygnus OB2: JHK Adaptive Optics Results from the Gemini Near-Infrared Imager

We present results of a high angular resolution survey of massive OB stars in the Cygnus OB2 association that we conducted with the Near-Infrared Imager camera and ALTAIR adaptive optics system of the Gemini North telescope. We observed 74 O- and early-B-type stars in Cyg OB2 in the JHK infrared bands in order to detect binary and multiple companions. The observations are sensitive to equal-brightness pairs at separations as small as [[Formula]], and progressively fainter companions are detectable out to △K=9 mag at a separation of 2″. This faint contrast limit due to read noise continues out to 10″ near the edge of the detector. We assigned a simple probability of chance alignment to each companion based upon its separation and magnitude difference from the central target star and upon areal star counts for the general star field of Cyg OB2. Companion stars with a field membership probability of less than 1% are assumed to be physical companions. This assessment indicates that 47% of the targets have at least one resolved companion that is probably gravitationally bound. Including known spectroscopic binaries, our sample includes 27 binary, 12 triple, and 9 systems with 4 or more components. These results confirm studies of high-mass stars in other environments that find that massive stars are born with a high-multiplicity fraction. The results are important for the placement of the stars in the Hertzsprung–Russell diagram, the interpretation of their spectroscopic analyses, and for future mass determinations through measurement of orbital motion.

79 ASTRONOMY AND ASTROPHYSICS↗