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Most of the subject matter of a full training course in applying remote sensing is presented in a self-teaching mode in this how-to manual which combines a review of basics, a survey of systems, and a treatment of the principles and mechanics of image analysis by computers, with a laboratory approach for learning to utilize the data through practical experiences. All relevant image products are included.
Various papers on human and machine strategies in sensor fusion are presented. The general topics addressed include: active vision, measurement and analysis of visual motion, decision models for sensor fusion, implementation of sensor fusion algorithms, applying sensor fusion to image analysis, perceptual modules and their fusion, perceptual organization and object recognition, planning and the integration of high-level knowledge with perception, using prior knowledge and context in sensor fusion.
This work was aimed at exploring means for utilizing computer technology in quality inspection and evaluation. Inspection of metallic welds was selected as the main application for this development and primary emphasis was placed on visual inspection, as opposed to other inspection methods, such as radiographic techniques. Emphasis was placed on methodologies with the potential for use in real-time quality control systems. Because quality evaluation is somewhat subjective, despite various efforts to classify discontinuities and standardize inspection methods, the task of using a computer for both inspection and evaluation was not trivial. The work started out with a review of the various inspection techniques that are used for quality control in welding. Among other observations from this review was the finding that most weld defects result in abnormalities that may be seen by visual inspection. This supports the approach of emphasizing visual inspection for this work. Quality control consists of two phases: (1) identification of weld discontinuities (some of which may be severe enough to be classified as defects), and (2) assessment or evaluation of the weld based on the observed discontinuities. Usually the latter phase results in a pass/fail judgement for the inspected piece. It is the conclusion of this work that the first of the above tasks, identification of discontinuities, is the most challenging one. It calls for sophisticated image processing and image analysis techniques, and frequently ad hoc methods have to be developed to identify specific features in the weld image. The difficulty of this task is generally not due to limited computing power. In most cases it was found that a modest personal computer or workstation could carry out most computations in a reasonably short time period. Rather, the algorithms and methods necessary for identifying weld discontinuities were in some cases limited. The fact that specific techniques were finally developed and successfully demosntrated to work illustrates that the general approach taken here appears to be promising for commercial development of computerized quality inspection systems. Inspection based on these techniques may be used to supplement or substitute more elaborate inspection methods, such as x-ray inspections.
Naturalistic driving studies consist of drivers using their personal vehicles and provide valuable real-world data, but privacy issues must be handled very carefully. Drivers sign a consent form when they elect to participate, but passengers do not for a variety of practical reasons. However, their privacy must still be protected. One large study includes a blurred image of the entire cabin which allows reviewers to find passengers in the vehicle; this protects the privacy but still allows a means of answering questions regarding the impact of passengers on driver behavior. A method for automatically counting the passengers would have scientific value for transportation researchers. We investigated different image analysis methods for automatically locating and counting the non-drivers including simple face detection and fine-tuned methods for image classification and a published object detection method. We also compared the image classification using convolutional neural network and vision transformer backbones. Our studies show the image classification method appears to work the best in terms of absolute performance, although we note the closed nature of our dataset and nature of the imagery makes the application somewhat niche and object detection methods also have advantages. We perform some analysis to support our conclusion.
A major issue in optical astronomical image analysis is the combined effect of the instrument’s point spread function (PSF) and the atmospheric seeing that blurs images and changes their shape in a way that is band and time-of-observation dependent. In this work we present a very simple neural network based approach to nonblind image deconvolution that relies on feeding a convolutional autoencoder (CAE) input images that have been preprocessed by convolution with the corresponding PSF and its regularized inverse, a method which is both conceptually simple and computationally less intensive. We also present here, a new approach for dealing with limited input dynamic range of neural networks compared to the dynamic range present in astronomical images.
Image analysis area and volume metrics A 80 and V 80 , used by others, are studied as a function of image morphology, a 3D feature, and Monte Carlo noise in simulated images. The A 80 area metric is found to be stable, with consistent results (and meaning) obtainable without a detailed understanding of 3D features and/or simulation noise levels. However, the V 80 volume metric varies significantly with image morphology, 3D features, and simulation noise. If an experimental image set gives A 80 area inferences that are consistent with 2D image simulations, but V 80 volume inferences that are significantly larger than those corresponding to simulated images, then issues related to 3D features and simulation noise should be explored before conclusions are drawn related to a possible mismatch in the real physical size of experimental and simulated source volumes.
An efficient image processing system is described for the automatic analysis of particle image velocimetry (PIV) fringe patterns. Each interrogation point takes 1 second to analyze; a complete specklegram can be interrogated at 1000 points in approximately 15 minutes. Incorporated in the analysis is a means for automatic replacement of spurious velocity vectors without either re-interrogation of the specklegram or interpolation between neighboring data points. The sucess of the above system is demonstrated by application of the PIV technique to the study of the sink-driven cavity flow. This flow is studied as part of a larger program to investigate trapped vortex flows as a means of lift enhancement on swept wings.
This study investigates the alteration of felsic sandstone-type rock, which is used as a coarse aggregate in concrete, subject to the effects of gamma-ray and neutron irradiation. The effects of three gamma-ray doses (27, 55, and 108 MGy) and four neutron fluence levels (1.22, 2.19, 6.99, and 14.30 × 10 19 n/cm 2 , $E$ ≥ 0.01 MeV) were investigated. Quartz and albite were found to be the major rock-forming minerals, with microcline intermediates, chlorite, and muscovite as the minors. Gamma rays caused no significant changes to the physical properties of the sandstone aggregates, even at high doses (108 MGy). In contrast, neutron irradiation caused alterations that became more pronounced at higher neutron fluences. The solid was confirmed to expand through metamictization of the rock-forming minerals. Quartz and muscovite were the most affected phases, whereas albite and microcline intermediates were only slightly affected, and chlorite was almost unaffected. The decrease in density was measured by He and water pycnometry, and this value was almost reproduced by calculations using the rock-forming mineral composition of the pristine sample measured using X-ray powder diffraction/Rietveld analysis and the cell volume change of the major forming minerals. In addition, light optical microscopy and scanning electron microscopy images confirmed the presence of intergranular and intragranular cracks. Intergranular cracks appeared to have initiated from the quartz grains, which expanded significantly. The intragranular cracks were frequently observed in the albite and microcline intermediates. These cracks can be described as radial cracks starting from the expanding quartz, caused by enforced displacement for deformation consistency with quartz expansion. The crack area ratio quantified by SEM image analysis corresponds to the discrepancy of the volume expansion difference calculated by He or water pycnometry and dimensional change measurements. In conclusion, an evaluation of solid expansion and crack openings in aggregates is important to estimate concrete degradation.
A new fuzzy set based technique that was developed for decision making is discussed. It is a method to generate fuzzy decision rules automatically for image analysis. This paper proposes a method to generate rule-based approaches to solve problems such as autonomous navigation and image understanding automatically from training data. The proposed method is also capable of filtering out irrelevant features and criteria from the rules.
Abstract We present an urban science framework to characterize phone users’ exposure to different street context types based on network science, geographical information systems (GIS), daily individual trajectories, and street imagery. We consider street context as the inferred usage of the street, based on its buildings and construction, categorized in nine possible labels. The labels define whether the street is residential, commercial or downtown, throughway or not, and other special categories. We apply the analysis to the City of Boston, considering daily trajectories synthetically generated with a model based on call detail records (CDR) and images from Google Street View. Images are categorized both manually and using artificial intelligence (AI). We focus on the city’s four main racial/ethnic demographic groups (White, Black, Hispanic and Asian), aiming to characterize the differences in what these groups of people see during their daily activities. Based on daily trajectories, we reconstruct most common paths over the street network. We use street demand (number of times a street is included in a trajectory) to detect each group’s most relevant streets and regions. Based on their street demand, we measure the street context distribution for each group. The inclusion of images allows us to quantitatively measure the prevalence of each context and points to qualitative differences on where that context takes place. Other AI methodologies can further exploit these differences. This approach presents the building blocks to further studies that relate mobile devices’ dynamic records with the differences in urban exposure by demographic groups. The addition of AI-based image analysis to street demand can power up the capabilities of urban planning methodologies, compare multiple cities under a unified framework, and reduce the crudeness of GIS-only mobility analysis. Shortening the gap between big data-driven analysis and traditional human classification analysis can help build smarter and more equal cities while reducing the efforts necessary to study a city’s characteristics.
This research was initiated as a part of the Advanced Sensor and Imaging System Technology (ASSIST) program at NASA Langley Research Center. The primary goal of this research is the development of image analysis algorithms for the detection of runways and other objects using an on-board camera. Initial effort was concentrated on images acquired using a passive millimeter wave (PMMW) sensor. The images obtained using PMMW sensors under poor visibility conditions due to atmospheric fog are characterized by very low spatial resolution but good image contrast compared to those images obtained using sensors operating in the visible spectrum. Algorithms developed for analyzing these images using a model of the runway and other objects are described in Part 1 of this report. Experimental verification of these algorithms was limited to a sequence of images simulated from a single frame of PMMW image. Subsequent development and evaluation of algorithms was done using video image sequences. These images have better spatial and temporal resolution compared to PMMW images. Algorithms for reliable recognition of runways and accurate estimation of spatial position of stationary objects on the ground have been developed and evaluated using several image sequences. These algorithms are described in Part 2 of this report. A list of all publications resulting from this work is also included.
Preliminary analysis of CRISM imaging of the Mars Pathfinder landing site is consistent with previously reported results from landed imaging. At tens of meters scale, the surface is largely dust-covered. Lee portions of topographic knobs are reddest and show most evidence for ferric mineralogy. The nearby 1.5-km diameter "Big Crater" exposes olivine, which is atypical of the northern plains. Big Crater may have penetrated northern plains material to expose buried basaltic highlands.
Topics covered include: Cryogenic Chamber for Servo-Hydraulic Materials Testing; Apparatus Measures Thermal Conductance Through a Thin Sample from Cryogenic to Room Temperature; Rover Attitude and Pointing System Simulation Testbed; Desktop Application Program to Simulate Cargo-Air-Drop Tests; Multimodal Friction Ignition Tester; Small-Bolt Torque-Tension Tester; Integrated Spacesuit Audio System Enhances Speech Quality and Reduces Noise; Hardware Implementation of a Bilateral Subtraction Filter; Simple Optoelectronic Feedback in Microwave Oscillators; Small X-Band Oscillator Antennas; Free-Space Optical Interconnect Employing VCSEL Diodes; Discrete Fourier Transform Analysis in a Complex Vector Space; Miniature Scroll Pumps Fabricated by LIGA; Self-Assembling, Flexible, Pre-Ceramic Composite Preforms; Flight-speed Integral Image Analysis Toolkit; Work Coordination Engine; Multi-Mission Automated Task Invocation Subsystem; Autonomously Calibrating a Quadrupole Mass Spectrometer; Determining Spacecraft Reaction Wheel Friction Parameters; Composite Silica Aerogels Opacified with Titania; Multiplexed Colorimetric Solid-Phase Extraction; Detecting Airborne Mercury by Use of Polymer/Carbon Films; Lattice-Matched Semiconductor Layers on Single Crystalline Sapphire Substrate; Pressure-Energized Seal Rings to Better Withstand Flows; Rollerjaw Rock Crusher; Microwave Sterilization and Depyrogenation System; Quantifying Therapeutic and Diagnostic Efficacy in 2D Microvascular Images; NiF2/NaF:CaF2/Ca Solid-State High-Temperature Battery Cells; Critical Coupling Between Optical Fibers and WGM Resonators; Microwave Temperature Profiler Mounted in a Standard Airborne Research Canister; Alternative Determination of Density of the Titan Atmosphere; Solar Rejection Filter for Large Telescopes; Automated CFD for Generation of Airfoil Performance Tables; Progressive Classification Using Support Vector Machines; Active Learning with Irrelevant Examples; A Data Matrix Method for Improving the Quantification of Element Percentages of SEM/EDX Analysis; Deployable Shroud for the International X-Ray Observatory; Improved Model of a Mercury Ring Damper; Optoelectronic pH Meter: Further Details; X-38 Advanced Sublimator; and Solar Simulator Represents the Mars Surface Solar Environment.
Digitally processed Seasat synthetic aperture radar (SAR) imagery of the Denver, Colorado area was examined to assess its potential for mapping urban land cover and the compatibility of SAR derived classes with those described in the U.S. Geological Survey classification system. The entire scene was interpreted to generate a small-scale land cover map. In addition, six subscene enlargements representative of urban land cover categories extant in the area were used as test sites for detailed analysis of land cover types. Two distinct approaches were employed and compared in examining the imagery - a visual interpretation of black-and-white positive transparencies and an automated-machine/visual interpretation. The latter used the Image 100 interactive image analysis system to generate land cover classes by density level slicing of the image frequency histogram.
Proton imaging has become a key diagnostic for measuring electromagnetic fields in high-energy-density (HED) laboratory plasmas. Compared to other techniques for diagnosing fields, proton imaging is a measurement that can simultaneously offer high spatial and temporal resolution and the ability to distinguish between electric and magnetic fields without the protons perturbing the plasma of interest. Consequently, proton imaging has been used in a wide range of HED experiments, from inertial-confinement fusion to laboratory astrophysics. An overview is provided on the state of the art of proton imaging, including a discussion of experimental considerations like proton sources and detectors, the theory of proton-imaging analysis, and a survey of experimental results demonstrating the breadth of applications. As a result, topics at the frontiers of proton-imaging development are also described, along with an outlook on the future of the field.
The performance and design requirements for a Color Graphic Camera System are presented. The system is a functional part of the Earth Observation Department Laboratory System (EODLS) and will be interfaced with Image Analysis Stations. It will convert the output of a raster scan computer color terminal into permanent, high resolution photographic prints and transparencies. Images usually displayed will be remotely sensed LANDSAT imager scenes.
A minicomputer-based image processing facility provides a relatively low-cost entry point for education about image analysis applications in remote sensing. While a minicomputer has sufficient processing power to produce results quite rapidly for low volumes of small images, it does not have sufficient power to perform CPU- or 1/0-bound tasks on large images. A system equipped with a display terminal is ideally suited for interactive tasks. Software procurement is a limiting factor for most end users, and software availability may well be the overriding consideration in selecting a particular hardware configuration. The hardware chosen should be selected to be compatible with the software and with concern for future expansion.
The history of a 3-year effort in Idaho, Oregon, and Washington to establish operational capabilities to analyze LANDSAT digital data and apply the results to natural resources management programs is related. Currently a number of agencies are conduct operational applications projects utilizing the data analysis facilities available and LANDSAT-derived data are being used by these agencies in their day-to-day operations. The image analysis systems and software used in each state are described and the participating state and local agencies are listed.