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All sourcesNASA NTRSDOE OSTI
NASA NTRS1983

Improving our understanding of the remote sensing process

Plans for two fundamental research programs aimed at improving an understanding of the physics and mathematics of remote sensing are discussed. The first program, Scene Radiation and Atmospheric Research Program, is concerned with developing the capability to determine biophysical attributes of terrestrial scenes through an improved understanding of the relationships between those properties and remotely sensed radiation. The research issues in the second program, Mathematical Pattern Recognition and Image Analysis, are discussed with reference to the following five categories: preprocessing, digital image representation, object scene inference, computational structures, and continuing studies.

Calabrese, M. A.↗
NASA NTRS1992

Portable dynamic fundus instrument

A portable diagnostic image analysis instrument is disclosed for retinal funduscopy in which an eye fundus image is optically processed by a lens system to a charge coupled device (CCD) which produces recordable and viewable output data and is simultaneously viewable on an electronic view finder. The fundus image is processed to develop a representation of the vessel or vessels from the output data.

Taylor, Gerald R.↗
NASA NTRS1993

Determining the 3-D structure and motion of objects using a scanning laser range sensor

In order for the EVAHR robot to autonomously track and grasp objects, its vision system must be able to determine the 3-D structure and motion of an object from a sequence of sensory images. This task is accomplished by the use of a laser radar range sensor which provides dense range maps of the scene. Unfortunately, the currently available laser radar range cameras use a sequential scanning approach which complicates image analysis. Although many algorithms have been developed for recognizing objects from range images, none are suited for use with single beam, scanning, time-of-flight sensors because all previous algorithms assume instantaneous acquisition of the entire image. This assumption is invalid since the EVAHR robot is equipped with a sequential scanning laser range sensor. If an object is moving while being imaged by the device, the apparent structure of the object can be significantly distorted due to the significant non-zero delay time between sampling each image pixel. If an estimate of the motion of the object can be determined, this distortion can be eliminated; but, this leads to the motion-structure paradox - most existing algorithms for 3-D motion estimation use the structure of objects to parameterize their motions. The goal of this research is to design a rigid-body motion recovery technique which overcomes this limitation. The method being developed is an iterative, linear, feature-based approach which uses the non-zero image acquisition time constraint to accurately recover the motion parameters from the distorted structure of the 3-D range maps. Once the motion parameters are determined, the structural distortion in the range images is corrected.

Nandhakumar, N.↗
NASA NTRS2003

Investigation of Critical Heat Flux in Reduced Gravity Using Photomicrographic Techniques

Experiments were performed to examine the effects of body force on flow boiling critical heat flux (CHF). FC-72 was boiled along one wall of a transparent rectangular flow channel that permitted photographic study of the vapor-liquid interface just prior to CHF. High-speed video imaging techniques were used to identify dominant CHF mechanisms corresponding to different flow orientations and liquid velocities. Six different CHF regimes were identified: Wavy Vapor Layer, Pool Boiling, Stratification, Vapor Counterflow, Vapor Stagnation, and Separated Concurrent Vapor Flow. CHF showed significant sensitivity to orientation for flow velocities below 0.2 m/s, where extremely low CHF values where measured, especially with downward-facing heated wall and downflow orientations. High flow velocities dampened the effects of orientation considerably. The CHF data were used to assess the suitability of previous CHF models and correlations. It is shown the Interfacial Lift-off Model is very effective at predicting CHF for high velocities at all orientations. The flooding limit, on the other hand, is useful at estimating CHF at low velocities and for downflow orientations. A new method consisting of three dimensionless criteria is developed for determining the minimum flow velocity required to overcome body force effects on near-saturated flow boiling CHF. Vertical upflow boiling experiments were performed in pursuit of identifying the trigger mechanism for subcooled flow boiling CHF. While virtually all prior studies on flow boiling CHF concern the prediction or measurement of conditions that lead to CHF, this study was focused on events that take place during the CHF transient. High-speed video imaging and photomicrographic techniques were used to record the transient behavior of interfacial features from the last steady-state power level before CHF until the moment of power cut-off following CHF. The video records show the development of a wavy vapor layer which propagates along the heated wall, permitting cooling prior to CHF only in wetting fronts corresponding to the wave troughs. Image analysis software was developed to estimate void fraction from the individual video images. The void fraction records for subcooled flow boiling show the CHF transient is accompanied by gradual lift-off of wetting fronts culminating in some maximum vapor layer mean thickness, following which the vapor layer begins to thin down as the transition to film boiling ensues. This study proves the Interfacial Lift-off Model, which has been validated for near-saturated flow boiling CHF, is equally valid for subcooled conditions.

Mudawar, Issam↗
DOE OSTI2024

Double-walled containment cell

Double-walled containment cells are described as may be used for storage, transport, and examination of a sample held within the cell by use of optical analysis techniques. A double-walled containment cell can include multiple types of windows that can be located as desired on the containment cells and thereby provide for optical access to a sample for multiple optical analysis techniques. Disclosed containment cells can be sized and designed for use with existing optical analysis systems, e.g., laser ablation, X-ray diffraction, spectral analysis (e.g., Raman spectroscopy, infrared spectroscopy, laser-induced breakdown spectroscopy, etc.), imaging analysis, etc.

Villa-Aleman, Eliel↗
NASA NTRS1984

LANDSAT-4 Thematic Mapper Modulation Transfer Function (MTF) evaluation

Results of MTF analysis of imagery of the San Mateo Bridge are consistent on two TM image dates for bands 4,5, and 7. There are indications that bands 1, 2, and 3 suffer from low image contrast, and consequently low signal to noise in the derived MTFs. The two image analysis produced reasonable results along +45 deg and -45 deg azimuths in the 2-D MTF, but poor results along the 0 deg and 90 deg azimuths. The effective instantaneous field of view is given for each band, and the image contrast for water and the bridge are compared. Graphs show overall TM system MTFs.

Schowengerdt, R.↗
NASA NTRS1990

An analysis of CCD images of the coma of Comet Halley

The analysis of selected CCD images of the coma of comet P/Halley is presented. The images were taken using specially designed filters that isolate regions of a comet's spectrum such that only sunlight which has been scattered by the dust in the coma is recorded. The modeling analysis objective is to make use of the skills developed in the development of Monte Carlo particle trajectory models for the distributions of gas species in cometary comae and to use those models as a basis for a new dust coma model. This model will include a self-consistant picture of the time-dependent dusty-gas dynamics of the inner coma and the three-dimensional time-dependent trajectories of the dust particles under the influence of solar gravity and solar radiation pressure in the outer coma. The model is intended to be used as a tool to analyze selected images from the two sets of CCD images with the hope that it will help the understanding of the effects of a number of important processes on the spatial morphology of the observed dust coma. The processes of importance to the observed dust coma include: (1) the dust particle size distribution function; (2) the terminal velocities of various sized dust particles in the inner coma; (3) the radiation scattering properties of dust particles, which are important both in terms of the observe scattered radiation and the radiation pressure acceleration on dust particles; (4) the fragmentation and/or vaporization of dust particles; and (5) the relative importance of CHON and silicate dust particles as they contribute both to the dusty-gasdynamics in the inner coma (that produce the dust particle terminal velocities) and to the observed spatial morphology on the outer dust coma.

Combi, Michael↗
NASA NTRS1988

Automatic analysis of stereoscopic image pairs from GOES satellites

An algorithm for automatic analysis of stereoscopic images is applied to stereo pairs of severe local storms and hurricanes observed by two GOES satellites. The automatically derived height fields and manual analyses are compared. It is found that the automatic analysis produces a more detailed structure in less time than manual analysis, although the two methods have similar quality. In areas where the features are very small, however, it is suggested that manual analysis is superior.

Hasler, A. F.↗
DOE OSTI2023

Wave Detection and Tracking Within a Rotating Detonation Engine Through Object Detection

As the operational time window of experimental rotating detonation engines (RDEs) is expanded and the technology matures toward integration within gas turbines, monitoring techniques must evolve to offer computationally efficient and highly time-resolved diagnostics. In this study, computer vision object detection methodology that seeks to reduce data processing time and calculate wave velocity within drastically reduced time intervals as compared to traditional high-frame-rate RDE images analysis techniques is proposed. The adapted you-only-look-once object detection network is trained to detect individual detonation waves within single down-axis RDE images. The wave location and rotational direction detected within a frame are tracked through a series of high-speed images to calculate the frame-to-frame wave velocity with the time-step resolution of $\mathrm{20 μs}$ across a series of frames. The analysis of the annotation box size and image linearization effects is presented, demonstrating the lowest frame-to-frame velocity total uncertainty of $\mathrm{±3.8\%}$ and the highest classification speed of 9.5 frames per second using linearized images. Linearized images “unwrap” the RDE annulus pixel region to a reduced image size. Here, this new method offers great reductions in data processing times and unsteady detonation behavior insight at intervals more comparable to the timescales of detonation wave interactions via the application of machine learning to experimental RDE data.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS2001

Early X-Ray Imaging Spectroscopy Results from HESSI

First results from HESSI will be presented. Several flares will be selected for analysis. Images with the finest possible resolution up to 2 arcseconds will be displayed as a function of time in different energy bands from below 10 keV to above 100 keV. The relation between the soft and hard X-ray time profiles will be investigated with the objective of searching for the spatial Neupert effect, where the hard X-ray profile for any region of the source is similar to the time differential of the soft X-ray profile.

Dennis, Brian R.↗
NASA NTRS2014

Hindlimb Suspension as a Model to Study Ophthalmic Complications in Microgravity Status Report: Optimization of Rat Retina Flat Mounts Staining to Study Vascular Remodeling

Preliminary data from a prior tissue‐sharing experiment has suggested that early growth response protein‐1 (Egr1), a transcription factor involved in various stress responses in the vasculature, is induced in the rat retina after 14 days of hindlimb suspension (HS) and may be evidence that mechanical stress is occurring secondary to the cephalad fluid shift. This mechanical stress could cause changes in oxygenation of the retina, and the subsequent ischemia‐ or inflammation‐driven hypoxia may lead to microvascular remodeling. This microvascular remodeling process can be studied using image analysis of retinal vessels and can be then be quantified by the VESsel GENeration Analysis (VESGEN) software, a computational tool that quantifies remodeling patterns of branching vascular trees and capillary or vasculogenic networks. Our project investigates whether rodent HS is a valid model to study the effects of simulated‐weightlessness on ocular structures and their relationship with intracranial pressure (ICP). One of the hypotheses to be tested is that HS‐induced cephalad fluid shift is accompanied by vascular engorgement that produces changes in retinal oxygenation, leading to oxidative stress, hypoxia, microvascular remodeling, and cellular degeneration. We have optimized the procedure to obtain flat mounts of rat retina, staining of the endothelial lining in vasculature and acquisition of high quality images suitable for VESGEN analysis. Briefly, eyes were fixed in 4% paraformaldehyde for 24 hours and retinas were detached and then mounted flat on microscope slides. The microvascular staining was done with endothelial cell‐specific isolectin binding, coupled to Alexa‐488 fluorophore. Image acquisition at low magnification and high resolution was performed using a new Leica SP8 confocal microscope in a tile pattern across the X,Y plane and multiple sections along the Z‐axis. This new confocal microscope has the added capability of dye separation using the Linear Unmixing method and allows us to remove the autofluorescence originating from the photoreceptor layer. In summary, we have an improved method for studying the retinal microvasculature that will provide an increase in the quality of images captured and will be applied throughout the various animal cohorts of the recentlyinitiated study that will evaluate rodent HS as a model to study ophthalmic complications in microgravity.

Theriot, Corey A.↗
NASA NTRS2013

Fuzzy Reasoning to More Accurately Determine Void Areas on Optical Micrographs of Composite Structures

Accomplishing the best-performing composite matrix (resin) requires that not only the processing method but also the cure cycle generate low-void-content structures. If voids are present, the performance of the composite matrix will be significantly reduced. This is usually noticed by significant reductions in matrix-dominated properties, such as compression and shear strength. Voids in composite materials are areas that are absent of the composite components: matrix and fibers. The characteristics of the voids and their accurate estimation are critical to determine for high performance composite structures. One widely used method of performing void analysis on a composite structure sample is acquiring optical micrographs or Scanning Electron Microscope (SEM) images of lateral sides of the sample and retrieving the void areas within the micrographs/images using an image analysis technique. Segmentation for the retrieval and subsequent computation of void areas within the micrographs/images is challenging as the gray-scaled values of the void areas are close to the gray-scaled values of the matrix leading to the need of manually performing the segmentation based on the histogram of the micrographs/images to retrieve the void areas. The use of an algorithm developed by NASA and based on Fuzzy Reasoning (FR) proved to overcome the difficulty of suitably differentiate void and matrix image areas with similar gray-scaled values leading not only to a more accurate estimation of void areas on composite matrix micrographs but also to a faster void analysis process as the algorithm is fully autonomous.

Dominquez, Jesus A.↗
NASA NTRS1987

Optical and digital pattern recognition; Proceedings of the Meeting, Los Angeles, CA, Jan. 13-15, 1987

The papers presented in this volume provide an overview of current research in both optical and digital pattern recognition, with a theme of identifying overlapping research problems and methodologies. Topics discussed include image analysis and low-level vision, optical system design, object analysis and recognition, real-time hybrid architectures and algorithms, high-level image understanding, and optical matched filter design. Papers are presented on synthetic estimation filters for a control system; white-light correlator character recognition; optical AI architectures for intelligent sensors; interpreting aerial photographs by segmentation and search; and optical information processing using a new photopolymer.

Liu, Hua-Kuang↗
NASA NTRS1998

Automated Track Recognition and Event Reconstruction in Nuclear Emulsion

The major advantages of nuclear emulsion for detecting charged particles are its submicron position resolution and sensitivity to minimum ionizing particles. These must be balanced, however, against the difficult manual microscope measurement by skilled observers required for the analysis. We have developed an automated system to acquire and analyze the microscope images from emulsion chambers. Each emulsion plate is analyzed independently, allowing coincidence techniques to be used in order to reject back- ground and estimate error rates. The system has been used to analyze a sample of high-multiplicity Pb-Pb interactions (charged particle multiplicities approx. 1100) produced by the 158 GeV/c per nucleon Pb-208 beam at CERN. Automatically reconstructed track lists agree with our best manual measurements to 3%. We describe the image analysis and track reconstruction techniques, and discuss the measurement and reconstruction uncertainties.

Deines-Jones, P.↗
NASA NTRS2008

3D Position and Velocity Vector Computations of Objects Jettisoned from the International Space Station Using Close-Range Photogrammetry Approach

Measurement of the jettisoned object departure trajectory and velocity vector in the International Space Station (ISS) reference frame is vitally important for prompt evaluation of the object s imminent orbit. We report on the first successful application of photogrammetric analysis of the ISS imagery for the prompt computation of the jettisoned object s position and velocity vectors. As post-EVA analyses examples, we present the Floating Potential Probe (FPP) and the Russian "Orlan" Space Suit jettisons, as well as the near-real-time (provided in several hours after the separation) computations of the Video Stanchion Support Assembly Flight Support Assembly (VSSA-FSA) and Early Ammonia Servicer (EAS) jettisons during the US astronauts space-walk. Standard close-range photogrammetry analysis was used during this EVA to analyze two on-board camera image sequences down-linked from the ISS. In this approach the ISS camera orientations were computed from known coordinates of several reference points on the ISS hardware. Then the position of the jettisoned object for each time-frame was computed from its image in each frame of the video-clips. In another, "quick-look" approach used in near-real time, orientation of the cameras was computed from their position (from the ISS CAD model) and operational data (pan and tilt) then location of the jettisoned object was calculated only for several frames of the two synchronized movies. Keywords: Photogrammetry, International Space Station, jettisons, image analysis.

Papanyan, Valeri↗
NASA NTRS1981

Applications notice for participation in the LANDSAT-D image data quality analysis program

The applications notice for the LANDSAT 4 image data quality analysis program is presented. The objectives of the program are to qualify LANDSAT 4 sensor and systems performance from a user applications point of view, and to identify any malfunctions that may impact data applications. Guidelines for preparing proposals and background information are provided.

Source record↗
DOE OSTI2025

Spectral kernel machines with electrically tunable photodetectors

Spectral machine vision collects spectral and spatial information as three-dimensional hypercubes and digitally processes them, which causes a data bottleneck, limiting power efficiency, frame rate, and spectral-spatial resolution. This work introduces spectral kernel machines (SKMs) to overcome these bottlenecks. SKM directly compresses spectral analysis through the output photocurrent and learns from example objects to identify and classify new samples in a "sniff-and-seek" mode. We experimentally demonstrated SKMs with electrically tunable bipolar black phosphorus-molybdenum disulfide (bP-MoS2) photodiodes in the near- and mid-infrared band and silicon photoconductors in the visible band, performing versatile intelligent tasks from chemometrics to semiconductor metrology. This architecture consumed substantially less power and was more than an order of magnitude faster than existing solutions for hyperspectral image analysis, defining an intelligent imaging and sensing paradigm with intriguing possibilities.

Zhang, Dehui↗
DOE OSTI2021

Instance Segmentation for Direct Measurements of Satellites in Metal Powders and Automated Microstructural Characterization from Image Data

In this work, we propose instance segmentation as a useful tool for image analysis in materials science. Instance segmentation is an advanced technique in computer vision which generates individual segmentation masks for every object of interest that is recognized in an image. Using an out-of-the-box implementation of Mask R-CNN, instance segmentation is applied to images of metal powder particles produced through gas atomization. Leveraging transfer learning allows for the analysis to be conducted with a very small training set of labeled images. As well as providing another method for measuring the particle size distribution, we demonstrate the first direct measurements of the satellite content in powder samples. After analyzing the results for the labeled data dataset, the trained model was used to generate measurements for a much larger set of unlabeled images. The resulting particle size measurements showed reasonable agreement with laser scattering measurements. The satellite measurements were self-consistent and showed good agreement with the expected trends for different samples. Finally, we present a small case study showing how instance segmentation can be used to measure spheroidite content in the UltraHigh Carbon Steel DataBase, demonstrating the flexibility of the technique.

36 MATERIALS SCIENCE↗