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Techniques for using image processing in astronomy are identified and developed for the following: (1) geometric and radiometric decalibration of vidicon-acquired spectra, (2) automatic identification and segregation of stars from galaxies; and (3) display of multiband radio maps in compact and meaningful formats. Examples are presented of these techniques applied to a variety of objects.
Philosophy classes still ponder the question asked by Dr. George Berkely, an Anglican Bishop and philosopher in the 1600’s-- “If a tree falls in a forest and no one is around to hear it, does it make a sound?” With that in mind, I ask the following—If a still image or motion imagery from a space mission cannot be found during a search, does it exist? Since the beginning of spaceflight, imagery has been a key form of data collected. Whether for mere curiosity (what does Earth look like from Space?), or for operational reasons (did the solar panel deploy?), or for engineering purposes (what was that object that floated away from the spacecraft?), imagery has been included in space missions. To be useful, though, the image or motion imagery must be accessible and accessed when needed. During the analog era, that typically meant captions and numbers associated with the physical media. With “born digital” imagery, it is possible to add metadata to the image data file. This metadata might include the date and time of capture, mission, camera, exposure data, and similar data fields. Many modern cameras embed some basic metadata into the image file at the moment of capture. The reality, though, is even with today’s born-digital enhancements with embedded metadata at the time of capture, reviewing and cataloging still and motion imagery is very labor intensive. Humans review the imagery for sensitive content (privacy concerns, imagery containing proprietary data/subject matter), and to identify imagery containing crew members or imagery that should be reviewed for engineering or scientific reasons. All this review and manual data entry is very time-consuming. Many improvements in Artificial Intelligence (AI), Machine Learning, and processing power now make it possible to identify persons, objects, motion, color, audio with sensitive content, and other details after or while the imagery is captured.
A frequency-based performance identification approach was evaluated using flight data from the NASA F-15 Highly Integrated Digital Electronic Control aircraft. The approach used frequency separation to identify the effectiveness of multiple controls simultaneously as an alternative to independent control identification methods. Fourier transformations converted measured control and response data into frequency domain representations. Performance gradients were formed using multiterm frequency matching of control and response frequency domain models. An objective function was generated using these performance gradients. This function was formally optimized to produce a coordinated control trim set. This algorithm was applied to longitudinal acceleration and evaluated using two control effectors: nozzle throat area and inlet first ramp. Three criteria were investigated to validate the approach: simultaneous gradient identification, gradient frequency dependency, and repeatability. This report describes the flight test results. These data demonstrate that the approach can accurately identify performance gradients during simultaneous control excitation independent of excitation frequency.
Digital micromirror devices (DMDs) are commercial micro-electromechanical systems, consisting of millions of mirrors which can be individually addressed and tilted into one of two states (+/-12deg). These devices were developed to create binary patterns in video projectors, in the visible range. Commercially available DMDs are hermetically sealed and extremely reliable. Recently, DMDs have been identified as an alternative to microshutter arrays for space-based multi-object spectrometers (MOS). Specifically, the MOS at the heart of the proposed Galactic Evolution Spectroscopic Explorer (GESE) uses the DMD as a reprogrammable slit mask. Unfortunately, the protective borosilicate windows limit the use of DMDs in the UV and IR regimes, where the glass has insufficient throughput. In this work, we present our efforts to replace standard DMD windows with custom windows made from UV-grade fused silica, low-absorption optical sapphire (LAOS) and magnesium fluoride (MgF2). We present transmission measurements of the antireflection coated windows and the reflectance of bare (window removed) DMDs. Furthermore, we investigated the long-term stability of the DMD reflectance and experiments for coating DMD active area with a layer of pure aluminum (Al) to boost reflectance performance in the UV spectral range (200−400 nm).
We describe the application of machine classification techniques to the development of an automated tool for the reduction of a large scientific data set. The 2nd Palomar Observatory Sky Survey provides comprehensive photographic coverage of the northern celestial hemisphere. The photographic plates are being digitized into images containing on the order of 10(exp 7) galaxies and 10(exp 8) stars. Since the size of this data set precludes manual analysis and classification of objects, our approach is to develop a software system which integrates independently developed techniques for image processing and data classification. Image processing routines are applied to identify and measure features of sky objects. Selected features are used to determine the classification of each object. GID3* and O-BTree, two inductive learning techniques, are used to automatically learn classification decision trees from examples. We describe the techniques used, the details of our specific application, and the initial encouraging results which indicate that our approach is well-suited to the problem. The benefits of the approach are increased data reduction throughput, consistency of classification, and the automated derivation of classification rules that will form an objective, examinable basis for classifying sky objects. Furthermore, astronomers will be freed from the tedium of an intensely visual task to pursue more challenging analysis and interpretation problems given automatically cataloged data.
The object of the Control Preliminary Definition Program was to define a preliminary control system concept as a part of the Energy Efficient Engine program. The program was limited to a conceptual definition of a full authority digital electronic control system. System requirements were determined and a control system was conceptually defined to these requirements. Areas requiring technological development were identified and a plan was established for implementing the identified technological features, including a control technology demonstration. A significant element of this program was a study of the potential benefits of closed-loop active clearance control, along with laboratory tests of candidate clearance sensor elements for a closed loop system.
A study is described which was initiated to identify and quantify the interrelationships between and within the performance, safety, cost, and schedule parameters for unmanned, automated payload programs. The result of the investigation was a systems cost/performance model which was implemented as a digital computer program and could be used to perform initial program planning, cost/performance tradeoffs, and sensitivity analyses for mission model and advanced payload studies. Program objectives and results are described briefly.
Through Small Business Innovation Research (SBIR) funding from NASA's Stennis Space Center, Geophex devised a new design for broadband electromagnetic sensors. Geophex developed a patented sensing technology, capable not only of coastal monitoring, but also a variety of other functions, including environmental pollution characterization, groundwater contamination detection, archaeological study, and mineral detection. The new technology is offered in several of the company's products the GEM-2, GEM-2A, and the GEM-3. The Geophex products consist of two primary electromagnetic coils, which are stimulated by alternating currents that generate a magnetic field in the object targeted for investigation. GEM-2 is a handheld, lightweight, programmable, digital device. GEM-2A is an airborne version of the sensor. Suspended from a helicopter, the GEM-2A is used to search for mineral deposits and to survey large tracts of land. The GEM-3 is capable of detecting buried landmines and other active munitions. GEM-3 identifies landmines by their brand names. Because each landmine has its own unique electromagnetic response to the broad frequency band emitted by the GEM-3, bomb identification and disposal strategies are made easier.
The Exploration Medical Capability (ExMC) Element within the Human Research Program (HRP) applies systems engineering (SE) principles along with the use of Model-Based Systems Engineering (MBSE) tools to identify and communicate the requirements for medical and crew health and performance (CHP) systems. In the past fiscal year, the MBSE approach sought to advance the digital engineering toolset for medical and CHP system representation. These digital artifacts provide enhanced views of the relationships among requirements, standards, functions, and capabilities, to name a few, that is best suited for a user’s objectives. The MBSE tools and SE practices were applied to the development of the revised Earth Independent Medical Operations (EIMO) medical system and the Artemis III and IV CHP System models. In addition, a System of Systems concept was integrated into the EIMO model to facilitate the identification of system interfaces that interact with the medical system. Finally, the ExMC SE team has initiated several efforts to bring operationally relevant digital engineering practices to the Human Health and Performance Directorate (HHPD). This included the development of a pilot program within the directorate to help foster utilization of tools such as MagicDraw for system modeling and Power BI for visualizing extracted data in an easily accessible dashboard format. Additionally, with the increase in complexity of the integration effort for Artemis missions, ExMC has endeavored to bring digital engineering strategies to potentially increase efficiency in review processes. This talk will provide a high-level overview of the ExMC SE team accomplishments since the last Investigators’ Workshop, an introduction to upcoming SE talks, and the ongoing systems engineering work.
Utilizing a Compact Color Microscope Imaging System (CCMIS), a unique algorithm has been developed that combines human intelligence along with machine vision techniques to produce an autonomous microscope tool for biomedical, industrial, and space applications. This technique is based on an adaptive, morphological, feature-based mapping function comprising 24 mutually inclusive feature metrics that are used to determine the metrics for complex cell/objects derived from color image analysis. Some of the features include: Area (total numbers of non-background pixels inside and including the perimeter), Bounding Box (smallest rectangle that bounds and object), centerX (x-coordinate of intensity-weighted, center-of-mass of an entire object or multi-object blob), centerY (y-coordinate of intensity-weighted, center-of-mass, of an entire object or multi-object blob), Circumference (a measure of circumference that takes into account whether neighboring pixels are diagonal, which is a longer distance than horizontally or vertically joined pixels), . Elongation (measure of particle elongation given as a number between 0 and 1. If equal to 1, the particle bounding box is square. As the elongation decreases from 1, the particle becomes more elongated), . Ext_vector (extremal vector), . Major Axis (the length of a major axis of a smallest ellipse encompassing an object), . Minor Axis (the length of a minor axis of a smallest ellipse encompassing an object), . Partial (indicates if the particle extends beyond the field of view), . Perimeter Points (points that make up a particle perimeter), . Roundness [(4(pi) x area)/perimeter(squared)) the result is a measure of object roundness, or compactness, given as a value between 0 and 1. The greater the ratio, the rounder the object.], . Thin in center (determines if an object becomes thin in the center, (figure-eight-shaped), . Theta (orientation of the major axis), . Smoothness and color metrics for each component (red, green, blue) the minimum, maximum, average, and standard deviation within the particle are tracked. These metrics can be used for autonomous analysis of color images from a microscope, video camera, or digital, still image. It can also automatically identify tumor morphology of stained images and has been used to detect stained cell phenomena (see figure).
Issues related to digital-backend (DBE) systems can be difficult to evaluate in either local tests or actual VLBI experiments. The 2nd DBE intercomparison workshop at Haystack Observatory on 25-26 October 2012 provided a forum to explicitly address validation and interoperability issues among independent global developers of DBE equipment. This special report discusses the workshop. It identifies DBE systems that were tested at the workshop, describes the test objectives and procedures, and reports and discusses the results of the testing.
The main goal of the research project was to identify the geophysical signatures of fracture growth in natural rocks by utilizing novel geophysical techniques. The research objectives were to (a) investigate the potential for geophysical methods to determine when cracks initiate, the types and locations of propagated cracks, and the coalescence of networks of cracks in natural rocks at multiple scales, (b) determine how damage at the microscale evolved into damage at the macroscale and then link the microscopic and macroscopic observations, (c) quantify crack coalescence in rocks under realistic stress conditions using coupled mechanical-geophysical-optical visualization, and (d) identify the precursors in geophysical signals to crack coalescence. The following research thrusts were explored to achieve the research objectives: (1) uniaxial compression testing of rock specimens with and without a set of pre‐existing flaws and (2) triaxial compression testing of natural rock specimens. These thrusts allowed for exploring fracturing in rocks under realistic in situ environments and at multiple scales. This project provided educational opportunities for nine graduate and undergraduate students and resulted in 27 peer-reviewed publications. This first research thrust focused on investigating the micromechanics of fractures in rocks through uniaxial compression testing combined with advanced geophysical and imaging techniques, specifically acoustic emission (AE) monitoring, ultrasonic imaging, and 2-dimensional Digital Image Correlation (2D-DIC). By examining damage processes under time-independent and time-dependent loading conditions, insights into damage localization, crack initiation, and fracturing mechanisms were gained. It was observed that the AE signals and the strain-based measurements directly reflect the state of damage in the rock specimen and could be used to identify the cracking levels, such as the crack initiation (CI) and crack damage (CD), and the mode of deformation. A novel calibration apparatus was developed to enhance the accuracy of AE sensors, allowing for the estimation of key parameters such as magnitude, source dimension, stress drop, and radiated seismic energy associated with the fractures. The findings highlighted significant variations in the temporal evolution of AE source parameters during the primary, secondary, and tertiary stages of creep, identifying tensile cracking as the primary deformation mode. The second research thrust focused on enhancing the understanding of fracturing processes in natural rocks through triaxial compression testing, real-time AE monitoring, and ultrasonic monitoring. We investigated the impact of various factors such as fracture propagation regimes, injection parameters, rock types, and pre-existing conditions on the hydraulic fracture (HF) behavior using scaled true-triaxially loaded specimens of Barre granite and Lyons sandstone. Custom sensor housing facilitated concurrent active and passive monitoring to analyze hydro-mechanical responses and microseismicity associated with different HF scenarios. A coupled investigation of passive microseismicity and active signal attributes permitted a detailed comprehension of the various HF processes (aseismic deformation, fracture initiation and propagation, fluid permeation, and leak-off) and their dependence on the specific rock type. The findings of this research demonstrated the effectiveness of AE monitoring techniques in providing valuable insights into the impact of various factors on the behavior and dynamics of HF processes. The advancements in monitoring techniques, offering a more thorough and precise approach, represent a significant step towards optimizing HF practices and ensuring sustainable resource extraction.
Progress made in the development of a technique for identifying and delinating benthic and shoreline communities using multispectral imagery is described. Images were collected with a multispectral scanner system mounted in a C-47 aircraft. Concurrent with the overflight, ecological ground- and sea-truth information was collected at 19 sites in the bay and on the shore. Preliminary processing of the scanner imagery with a CDC 1604 digital computer provided the optimum channels for discernment among different underwater and coastal objects. Automatic mapping of the benthic plants by multiband imagery and the mapping of isotherms and hydrodynamic parameters by digital model can become an effective predictive ecological tool when coupled together. Using the two systems, it appears possible to predict conditions that could adversely affect the benthic communities. With the advent of the ERTS satellites and space platforms, imagery data could be obtained which, when used in conjunction with water-level and meteorological data, would provide for continuous ecological monitoring.
We present a 10-year X-ray light curve and the spectra of a peculiar X-ray transient in the spiral galaxy M81. The source was below the detection limit of ROSAT PSPC before 1993, but it brightened substantially in 1993, with luminosities exceeding the Eddington limit of a 1.5 solar mass compact accretor. It then faded and was not firmly detected in the ROSAT HRI and PSPC observations after 1994. The Chandra image obtained in 2000 May, however, shows an X-ray source at its position within the instrumental uncertainties. The Chandra source is coincident with a star-like object in the Digitized-Sky-Survey. A Hubble image suggests that the optical object may be extended. While these three observations could be of the same object, which may be an X-ray binary containing a black-hole candidate, the possibility that the ROSAT and Chandra sources are two different objects in a dense stellar environment cannot be ruled out. The Hubble data suggests that the optical object may be a globular cluster yet to be identified.
Several areas of applications of image processing to astronomy were identified and discussed. These areas include: (1) deconvolution for atmospheric seeing compensation; a comparison between maximum entropy and conventional Wiener algorithms; (2) polarization in galaxies from photographic plates; (3) time changes in M87 and methods of displaying these changes; (4) comparing emission line images in planetary nebulae; and (5) log intensity, hue saturation intensity, and principal component color enhancements of M82. Examples are presented of these techniques applied to a variety of objects.
The initial objectives of analyses of the MSS data are two-fold: (1) to evaluate the geodetic accuracy of CCT-P data of the test sites; and (2) to improve the geodetic accuracy by additional processing if the original data either do not meet pre-launch specifications or mapping requirements. The location of 45 ground control points (GCP) digitized from 35 U.S. Geological Survey 1:24,000 scale quadrangles (UTM coordinates) were identified in terms of pixel and scan line values. These 46 points are used to establish UTM position error vector distributions in the scene. As an initial check on the geometric reliability of the MSS data, 28 well-distributed GCPs were input to a program which compares the scaled image distances between all possible point pairs with the corresponding map distances and computes the distance differences; that is, the relative positional errors. The relative errors obtained from initial computations averaged about +/- 200 m. These errors could result from a number of sources, including misidentification of GCP locations, UTM coordinate errors introduced by the map digitizing process or errors resulting from data acquisition and geometric processing.
Pinyon-Juniper woodlands dominate approximately 24.3 million hectares (60 million acres) in the western United States. The overall objective was to test the sensitivity of the LANDSAT Thematic Mapper (TM) spectral data for detecting varying degrees of soil erosion within the Pinyon-Juniper woodlands. A second objective was to assess the potential of the spectral data for assigning the Universal Soil Loss Equation (USLE) crop management (C) factor values to varying cover types within the woodland. Thematic Mapper digital data for June 2, 1984 on channels 2, 3, 4, and 5 were used. Digital data analysis was performed using the ELAS software package. Best results were achieved using CLUS, an unsupervised clustering algorithm. Fifteen of the 40 Pinyon-Juniper signatures were identified as being relatively pure Pinyon-Juniper woodland. Final analysis resulted in the grouping of the 15 signatures into three major groups. Ten study sites were selected from each of the three groups and located on the ground. At each site the following field measurements were taken: percent tree canopy and percent understory cover, soil texture, total soil loss, and soil erosion rate estimates. A technique for measuring soil erosion within Pinyon-Juniper woodlands was developed. A theoretical model of site degradation after Pinyon-Juniper invasion is presented.
The study for which the results are presented had these objectives: (1) to use Landsat data and computer-implemented pattern recognition to classify the major crops from regions encompassing different climates, soils, and crops; (2) to estimate crop areas for counties and states by using crop identification data obtained from the Landsat identifications; and (3) to evaluate the accuracy, precision, and timeliness of crop area estimates obtained from Landsat data. The paper describes the method of developing the training statistics and evaluating the classification accuracy. Landsat MSS data were adequate to accurately identify wheat in Kansas; corn and soybean estimates for Indiana were less accurate. Systematic sampling of entire counties made possible by computer classification methods resulted in very precise area estimates at county, district, and state levels.