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At least 163 records · Page 9

Spatial vision processes: From the optical image to the symbolic structures of contour information

The significance of machine and natural vision is discussed together with the need for a general approach to image acquisition and processing aimed at recognition. An exploratory scheme is proposed which encompasses the definition of spatial primitives, intrinsic image properties and sampling, 2-D edge detection at the smallest scale, the construction of spatial primitives from edges, and the isolation of contour information from textural information. Concepts drawn from or suggested by natural vision at both perceptual and physiological levels are relied upon heavily to guide the development of the overall scheme. The scheme is intended to provide a larger context in which to place the emerging technology of detector array focal-plane processors. The approach differs from many recent efforts in edge detection and image coding by emphasizing smallest scale edge detection as a foundation for multi-scale symbolic processing while diminishing somewhat the importance of image convolutions with multi-scale edge operators. Cursory treatments of information theory illustrate that the direct application of this theory to structural information in images could not be realized.

Jobson, Daniel J.↗

Optical imaging of cloud-to-stratosphere/mesosphere lightning over the Amazon Basin (CS/LAB)

The purpose of the CS/LAB project was to obtain images of cloud to stratosphere lightning discharges from aboard NASA's DC-8 Airborne Laboratory while flying in the vicinity of thunderstorms over the Amazon Basin. We devised a low light level imaging package as an add-on experiment to an airborne Laboratory deployment to South America during May-June, 1993. We were not successful in obtaining the desired images during the South American deployment. However, in a follow up flight over the American Midwest during the night of July 8-9, 1993 we recorded nineteen examples of the events over intense thunderstorms. From the observations were estimated absolute brightness, terminal altitudes, flash duration, horizontal extents, emission volumes, and frequencies relative to negative and positive ground strokes.

Sentman, Davis D.↗

Classification of Magneto-Optic Images using Neural Networks

A real time imaging system with a neural network classifier has been incorporated on a Macintosh computer in conjunction with an MOI system. This system images rivets on aircraft aluminium structures using eddy currents and magnetic imaging. Moment invariant functions from the image of a rivet is used to train a multilayer perceptron neural network to classify the rivets as good or bad (rivets with cracks).

Nath, Shridhar↗

Hybrid-dual-fourier tomographic algorithm for a fast three-dimensionial optical image reconstruction in turbid media

A reconstruction technique for reducing computation burden in the 3D image processes, wherein the reconstruction procedure comprises an inverse and a forward model. The inverse model uses a hybrid dual Fourier algorithm that combines a 2D Fourier inversion with a 1D matrix inversion to thereby provide high-speed inverse computations. The inverse algorithm uses a hybrid transfer to provide fast Fourier inversion for data of multiple sources and multiple detectors. The forward model is based on an analytical cumulant solution of a radiative transfer equation. The accurate analytical form of the solution to the radiative transfer equation provides an efficient formalism for fast computation of the forward model.

Alfano, Robert R.↗

Combined optimization of image-gathering optics and image-processing algorithm for edge detection

This paper investigates the relationships between the image-gathering and image-processing systems for minimum mean-squared error estimation of scene characteristics. A stochastic optimization problem is formulated in which the objective is to determine a spatial characteristic of the scene rather than a feature of the already blurred, sampled, and noisy image data. The Wiener filter for the sampled image case is obtained as a special case, where the desired characteristics is scene restoration. Optimal edge detection is investigated. It is shown that the optimal edge detector compensates for the blurring introduced by the image-gathering optics, and, notably, that it is not circularly symmetric. The lack of circular symmetry is largely due to the geometric effects of the sampling lattice used in image acquisition.

Halyo, N.↗

Automated inspection of solder joints for surface mount technology

Researchers at NASA/GSFC evaluated various automated inspection systems (AIS) technologies using test boards with known defects in surface mount solder joints. These boards were complex and included almost every type of surface mount device typical of critical assemblies used for space flight applications: X-ray radiography; X-ray laminography; Ultrasonic Imaging; Optical Imaging; Laser Imaging; and Infrared Inspection. Vendors, representative of the different technologies, inspected the test boards with their particular machine. The results of the evaluation showed limitations of AIS. Furthermore, none of the AIS technologies evaluated proved to meet all of the inspection criteria for use in high-reliability applications. It was found that certain inspection systems could supplement but not replace manual inspection for low-volume, high-reliability, surface mount solder joints.

Savage, Robert M.↗

Concept of Operations for OSIRIS-REx Optical Navigation Image Planning

Optical navigation (OpNav) is a critical subsystem of the OSIRIS-REx asteroid sample return mission, which operated in the vicinity of near-Earth asteroid (101955) Bennu from August 2018 through April 2021. A substantial amount of mission resources across multiple subsystems and institutions is required to ensure that the OpNav data are successfully acquired. The KinetX OpNav team, part of the Flight Dynamics System (FDS), is responsible for performing required analysis to develop the OpNav operations plans; requesting, reviewing and verifying the plans; and ultimately using the image data for critical navigation operations. The FDS team, responsible for the mission navigation, is operated by KinetX Aerospace with management and operations support from NASA’s Goddard Space Flight Center. The Science Processing and Operations Center (SPOC), located at the University of Arizona’s Lunar and Planetary Laboratory, is responsible for generating the planning products for all science and most OpNav data. These plans are integrated into the spacecraft sequences, tested, and commanded by the Mission Support Area (MSA) at Lockheed Martin Space. To ensure mission-critical navigation image data are successfully acquired, the plan is developed through a waterfall of planning cycles over the course of 3 months prior to onboard plan execution. During the initial strategic planning for a mission phase, detailed analysis is performed by the OpNav team to conceptualize the concept of operations (ConOps) for image data collection. This phase OpNav Narrative is included along with other strategic planning documents for the key ground segment stakeholders to review and provide feedback. The detailed OpNav plans get defined in the tactical planning cycle, which spans 8 to 3 weeks before the week-long integrated sequence is executed on-board the spacecraft. During the tactical cycle, the initial OpNav Request is submitted along with the science requests, kicking off development of the science and OpNav plans. Once the initial plan is drafted, interfaces are exercised so that the plan can be reviewed and iterated, if necessary. A rigorous schedule is followed by the planning teams during the implementation cycle, spanning the last 18 days before uplink, to ensure all the necessary integration, testing, and reviewing can occur on time. The development of the OpNav planning ConOps, including responsibilities, interfaces, timelines, and procedures, took extensive collaboration across mission elements and institutions. The process was robust throughout the 137 weeks of continuous Optical Navigation Operations at Bennu, which concluded on April 9th, 2021.

Coralie D. Adam↗

Adaptive Optics For Imaging Bright Objects Next To Dim Ones

Adaptive optics used in imaging optical systems, according to proposal, to enhance high-dynamic-range images (images of bright objects next to dim objects). Designed to alter wavefronts to correct for effects of scattering of light from small bumps on imaging optics. Original intended application of concept in advanced camera installed on Hubble Space Telescope for imaging of such phenomena as large planets near stars other than Sun. Also applicable to other high-quality telescopes and cameras.

Shao, Michael↗

Introduction to Special Section: Machine Learning for Image-based Geologic Interpretation

Image-based geological interpretation has been a labor-intensive and time-consuming process because it requires well-trained geoscientists to identify geological structures, features, and textures from various types of images. These images include scanning electron microscopic images, optical microscopic images, optical photos, resistivity images, seismic volumes, remote-sensing images, etc. With fast-evolving machine learning (ML) technology and computing power in recent decades, computers can achieve nearhuman-level to super-human-level performance with scalable high efficiency in the computer vision field. These technological revolutions facilitated image-based geological interpretation in petroleum exploration and production. For example, a fault picking method applied to 3-D seismic volume data using deep learning can achieve superior performance in comparison to conventional auto-picking methods. In addition, under the new normal of low oil prices, the petroleum industry seeks cost-effective strategies such as automating traditionally labor-intensive processes. Nevertheless, the potential of applying ML to geological image interpretation is still facing a few key challenges including data scarcity, data distribution, poor data and/or label quality, data leakage, learning algorithms, model architecture, training methodologies, testing and evaluation metrics, hyper-parameters optimization, model drift, production deployment, and the like.

58 GEOSCIENCES↗

An Evaluation of Grazing-Incidence Optics for Neutron Imaging

The refractive index for most materials is slightly less than unity, which opens an opportunity to develop the grazing incidence neutron imaging optics. The ideal material for the optics would be natural nickel and its isotopes. Marshall Space Flight Center (MSFC) has active development program on the nickel replicated optics for use in x-ray astronomy. Brief status report on the program is presented. The results of the neutron focusing optic test carried by the MSFC team at National Institute of Standards and Technology (NIST) are also presented. Possible applications of the optics are briefly discussed.

Gubarev, M. V.↗

An Evaluation of Grazing-Incidence Optics for Neutron Imaging

The focusing capabilities of neutron imaging optic based on the Wolter-1 geometry have been successfully demonstrated with a beam of long wavelength neutrons with low angular divergence.. A test mirror was fabricated using an electroformed nickel replication process at Marshall Space Flight Center. The neutron current density gain at the focal spot of the mirror is found to be at least 8 for neutron wavelengths in the range from 6 to 20 A. Possible applications of the optics are briefly discussed.

Gubarev, M. V.↗

Optical Pseudocolor Encoding Of Gray-Scale Image

Optical encoding much faster than digital electronic encoding. In optical pseudocolor-encoding apparatus brightness modulation in image from television camera transformed into polarization modulation in LCTV, and then into pseudocolor modulation in image on projection screen. Advantageous for such purposes as thermography, inspection of circuit boards, mammography, and mapping.

Chao, Tien-Hsin↗

Elimination of coherent noise in a coherent light imaging system

Optical imaging systems using coherent light introduce objectionable noise into the output image plane. Dust and bubbles on and in lenses cause most of the noise in the output image. This noise usually appears as bull's-eye diffraction patterns in the image. By rotating the lens about the optical axis these diffraction patterns can be essentially eliminated. The technique does not destroy the spatial coherence of the light and permits spatial filtering of the input plane.

Grebowsky, G. J.↗