Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Image reconstruction”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 163 records · Page 9

Lossless compression of AVIRIS data: Comparison of methods and instrument constraints

A family of lossless compression methods, allowing exact image reconstruction, are evaluated for compressing Airborne Visible/Infrared Imaging Spectrometers (AVIRIS) image data. The methods are used on Differential Pulse Code Modulation (DPCM). The compressed data have an entropy of order 6 bits/pixel. A theoretical model indicates that significantly better lossless compression is unlikely to be achieved because of limits caused by the noise in the AVIRIS channels. AVIRIS data differ from data produced by other visible/near-infrared sensors, such as LANDSAT-TM or SPOT, in several ways. Firstly, the data are recorded at a greater resolution (12 bits, though packed into 16-bit words). Secondly, the spectral channels are relatively narrow and provide continuous coverage of the spectrum so that the data in adjacent channels are generally highly correlated. Thirdly, the noise characteristics of the AVIRIS are defined by the channels' Noise Equivalent Radiances (NER's), and these NER's show that, at some wavelengths, the least significant 5 or 6 bits of data are essentially noise.

Roger, R. E.↗

Machine learning for improved current-density reconstruction from two-dimensional vector magnetic images

The reconstruction of electrical current densities from magnetic field measurements is an important technique with applications in materials science, circuit design, quality control, plasma physics, and biology. Analytic reconstruction methods exist for planar currents, but break down in the presence of high-spatial-frequency noise or large standoff distance, restricting the types of systems that can be studied. Here, we demonstrate the use of a deep convolutional neural network for current density reconstruction from two-dimensional images of vector magnetic fields acquired by a quantum diamond microscope . Trained network performance significantly exceeds analytic reconstruction for data with high noise or large standoff distances. This machine learning technique can perform quality inversions on lower-signal-to-noise-ratio data, significantly reducing the data collection time and permitting reconstructions of weaker and three-dimensional current sources. Published by the American Physical Society 2025

Reed, Niko R. (ORCID:0009000305222403)↗

Automated piezoresponse force microscopy domain tracking during fast thermally stimulated phase transition in CuInP 2 S 6

Real-time tracking of dynamic nanoscale processes such as phase transitions by scanning probe microscopy is a challenging task, typically requiring extensive and laborious human supervision. Smart strategies to track specific regions of interest (ROI) in the system during such transformations in a fast and automated manner are necessary to study the evolution of the microscopic changes in such dynamic systems. In this work, we realize automated ROI tracking in piezoresponse force microscopy during a fast (≈0.8 °C s –1 ) thermally stimulated ferroelectric-to-paraelectric phase transition in CuInP 2 S 6 . We use a combination of fast (1 frame per second) sparse scanning with compressed sensing image reconstruction and real-time offset correction via phase cross correlation. The applied methodology enables in situ fast and automated functional nanoscale characterization of a certain ROI during external stimulation that generates sample drift and changes local functionality.

36 MATERIALS SCIENCE↗

An empirical method for geometric calibration of a photon counting detector-based cone beam CT system

BACKGROUND: Geometric calibration is essential in developing a reliable computed tomography (CT) system. It involves estimating the geometry under which the angular projections are acquired. Geometric calibration of cone beam CTs employing small area detectors, such as currently available photon counting detectors (PCDs), is challenging when using traditional-based methods due to detectors’ limited areas. OBJECTIVE: This study presented an empirical method for the geometric calibration of small area PCD-based cone beam CT systems. METHODS: Unlike the traditional methods, we developed an iterative optimization procedure to determine geometric parameters using the reconstructed images of small metal ball bearings (BBs) embedded in a custom-built phantom. An objective function incorporating the sphericities and symmetries of the embedded BBs was defined to assess performance of the reconstruction algorithm with the given initial estimated set of geometric parameters. The optimal parameter values were those which minimized the objective function. The TIGRE toolbox was employed for fast tomographic reconstruction. To evaluate the proposed method, computer simulations were carried out using various numbers of spheres placed in various locations. Furthermore, efficacy of the method was experimentally assessed using a custom-made benchtop PCD-based cone beam CT. RESULTS: Computer simulations validated the accuracy and reproducibility of the proposed method. The precise estimation of the geometric parameters of the benchtop revealed high-quality imaging in CT reconstruction of a breast phantom. Within the phantom, the cylindrical holes, fibers, and speck groups were imaged in high fidelity. The CNR analysis further revealed the quantitative improvements of the reconstruction performed with the estimated parameters using the proposed method. CONCLUSION: Apart from the computational cost, we concluded that the method was easy to implement and robust.

Instruments & Instrumentation↗

DOLCE: A Model-Based Probabilistic Diffusion Framework for Limited-Angle CT Reconstruction

Limited-Angle Computed Tomography (LACT) is a non-destructive evaluation technique used in a variety of applications ranging from security to medicine. The limited angle coverage in LACT is often a dominant source of severe artifacts in the reconstructed images, making it a challenging inverse problem. We present DOLCE, a new deep model-based framework for LACT that uses a conditional diffusion model as an image prior. Diffusion models are a recent class of deep generative models that are relatively easy to train due to their implementation as image denoisers. DOLCE can form high-quality images from severely under-sampled data by integrating data-consistency updates with the sampling updates of a diffusion model, which is conditioned on the transformed limited-angle data. We show through extensive experimentation on several challenging real LACT datasets that, the same pre-trained DOLCE model achieves the SOTA performance on drastically different types of images. Additionally, we show that, unlike standard LACT reconstruction methods, DOLCE naturally enables the quantification of the reconstruction uncertainty by generating multiple samples consistent with the measured data.

Kim, Hyojin↗

Four years experience in APMS star plate processing - Results and future plans

The present paper describes an automated system for measuring stellar proper motions on the basis of information contained in photographic plates. In this system, the images on a star plate are digitized by a scanning microdensitometer using light from a He-Ne gas laser, and a special-purpose computer arranges the measurements in computer-compatible form on magnetic tape. The scanning and image-reconstruction processes are briefly outlined, and the image-evaluation techniques are discussed. It is shown that the present system has been especially successful in measuring the proper motions of low-luminosity stars, including 119 stars with less than 1/10,000 of the solar bolometric luminosity. Plans for measurements of high-density Milky Way star plates are noted.

Newcomb, J. S.↗

Comparisons Between NO PLIF Imaging and CFD Simulations of Mixing Flowfields for High-Speed Fuel Injectors

The current work compares experimentally and computationally obtained nitric oxide (NO) planar laser induced fluorescence (PLIF) images of the mixing flowfields for three types of high-speed fuel injectors: a strut, a ramp, and a rectangular flushwall. These injection devices, which exhibited promising mixing performance at lower flight Mach numbers, are currently being studied as a part of the Enhanced Injection and Mixing Project (EIMP) at the NASA Langley Research Center. The EIMP aims to investigate scramjet fuel injection and mixing physics, and improve the understanding of underlying physical processes relevant to flight Mach numbers greater than eight. In the experiments, conducted in the NASA Langley Arc-Heated Scramjet Test Facility (AHSTF), the injectors are placed downstream of a Mach 6 facility nozzle, which simulates the high Mach number air flow at the entrance of a scramjet combustor. Helium is used as an inert substitute for hydrogen fuel. Both schlieren and PLIF techniques are applied to obtain mixing flowfield flow visualizations. The experimental PLIF is obtained by using a UV laser sheet to interrogate a plane of the flow by exciting fluorescence from the NO molecules, which are present in the AHSTF air. Consequently, the absence of signal in the resulting PLIF images is an indication of pure helium (fuel). The computational PLIF is obtained by applying a fluorescence model for NO to the results of the Reynolds-averaged simulations (RAS) of the mixing flow field carried out using the VULCAN-CFD solver. This approach is required because the PLIF signal is a nonlinear function of not only NO concentration, but also pressure, temperature, and the flow velocity. This complexity allows additional flow features to be identified and compared with those obtained from the computational fluid dynamics (CFD) simulations, however, such comparisons are only semiquantitative. Three-dimensional image reconstruction, similar to that used in magnetic resonance imaging, is also used to obtain images in the streamwise and spanwise planes from select cross-stream PLIF plane data. Synthetic schlieren is also computed from the RAS data. Good agreement between the experimental and computational results provides increased confidence in the CFD simulations for investigations of injector performance.

Drozda, Tomasz G.↗

Comparisons Between NO PLIF Imaging and CFD Simulations of Mixing Flowfields for High-Speed Fuel Injectors

The current work compares experimentally and computationally obtained nitric oxide (NO) planar laser-induced fluorescence (PLIF) images of the mixing flowfields for three types of high-speed fuel injectors: a strut, a ramp, and a rectangular flushwall. These injection devices, which exhibited promising mixing performance at lower flight Mach numbers, are currently being studied as a part of the Enhanced Injection and Mixing Project (EIMP) at the NASA Langley Research Center. The EIMP aims to investigate scramjet fuel injection and mixing physics, and improve the understanding of underlying physical processes relevant to flight Mach numbers greater than eight. In the experiments conducted in the NASA Langley Arc-Heated Scramjet Test Facility (AHSTF), the injectors are placed downstream of a Mach 6 facility nozzle, which simulates the high Mach number air flow at the entrance of a scramjet combustor. Helium is used as an inert substitute for hydrogen fuel. Both schlieren and PLIF techniques are applied to obtain mixing flowfield flow visualizations. The experimental PLIF is obtained by using a UV laser sheet to interrogate a plane of the flow by exciting fluorescence from the NO molecules that are present in the AHSTF air. Consequently, the absence of signal in the resulting PLIF images is an indication of pure helium (fuel). The computational PLIF is obtained by applying a fluorescence model for NO to the results of the Reynolds-averaged simulations (RAS) of the mixing flowfield carried out using the VULCAN-CFD solver. This approach is required because the PLIF signal is a nonlinear function of not only NO concentration, but also pressure, temperature, and the flow velocity. This complexity allows additional flow features to be identified and compared with those obtained from the computational fluid dynamics (CFD) simulations, however, such comparisons are only semiquantitative. Three-dimensional image reconstruction, similar to that used in magnetic resonance imaging, is also used to obtain images in the streamwise and spanwise planes from select cross-stream PLIF plane data. Synthetic schlieren is also computed from the RAS data. Good agreement between the experimental and computational results provides increased confidence in the CFD simulations for investigations of injector performance.

PLIF↗

Comparisons Between NO PLIF Imaging and CFD Simulations of Mixing Flowfields for High-Speed Fuel Injectors

The current work compares experimentally and computationally obtained nitric oxide (NO) planar laser-induced fluorescence (PLIF) images of the mixing flowfields for three types of high-speed fuel injectors: a strut, a ramp, and a rectangular flushwall. These injection devices, which exhibited promising mixing performance at lower flight Mach numbers, are currently being studied as a part of the Enhanced Injection and Mixing Project (EIMP) at the NASA Langley Research Center. The EIMP aims to investigate scramjet fuel injection and mixing physics, and improve the understanding of underlying physical processes relevant to flight Mach numbers greater than eight. In the experiments conducted in the NASA Langley Arc-Heated Scramjet Test Facility (AHSTF), the injectors are placed downstream of a Mach 6 facility nozzle, which simulates the high Mach number air flow at the entrance of a scramjet combustor. Helium is used as an inert substitute for hydrogen fuel. Both schlieren and PLIF techniques are applied to obtain mixing flowfield flow visualizations. The experimental PLIF is obtained by using a UV laser sheet to interrogate a plane of the flow by exciting fluorescence from the NO molecules that are present in the AHSTF air. Consequently, the absence of signal in the resulting PLIF images is an indication of pure helium (fuel). The computational PLIF is obtained by applying a fluorescence model for NO to the results of the Reynolds-averaged simulations (RAS) of the mixing flowfield carried out using the VULCAN-CFD solver. This approach is required because the PLIF signal is a nonlinear function of not only NO concentration, but also pressure, temperature, and the flow velocity. This complexity allows additional flow features to be identified and compared with those obtained from the computational fluid dynamics (CFD) simulations, however, such comparisons are only semiquantitative. Three-dimensional image reconstruction, similar to that used in magnetic resonance imaging, is also used to obtain images in the streamwise and spanwise planes from select cross-stream PLIF plane data. Synthetic schlieren is also computed from the RAS data. Good agreement between the experimental and computational results provides increased confidence in the CFD simulations for investigations of injector performance.

PLIF↗

The Dark Side of Pluto

During its departure from Pluto, New Horizons used its LORRI camera to image a portion of Pluto's southern hemisphere that was in a decades-long seasonal winter darkness, but still very faintly illuminated by sunlight reflected by Charon. Recovery of this faint signal was technically challenging. The bright ring of sunlight forward-scattered by haze in the Plutonian atmosphere encircling the nightside hemisphere was severely overexposed, defeating the standard smeared-charge removal required for LORRI images. Reconstruction of the overexposed portions of the raw images, however, allowed adequate corrections to be accomplished. The small solar elongation of Pluto during the departure phase also generated a complex scattered-sunlight background in the images that was three orders of magnitude stronger than the estimated Charon-light flux (the Charon-light flux is similar to the flux of moonlight on Earth a few days before first quarter). A model background image was constructed for each Pluto image based on principal component analysis applied to an ensemble of scattered-sunlight images taken at identical Sun−spacecraft geometry to the Pluto images. The recovered Charon-light image revealed a high-albedo region in the southern hemisphere. We argue that this may be a regional deposit of N2 or CH4 ice. The Charon-light image also shows that the south polar region currently has markedly lower albedo than the north polar region of Pluto, which may reflect the sublimation of N2 ice or the deposition of haze particulates during the recent southern summer.

Pluto↗

Characterizing and Mitigating Intraday Variability: Reconstructing Source Structure in Accreting Black Holes with mm-VLBI

The extraordinary physical resolution afforded by the Event Horizon Telescope has opened a window onto the astrophysical phenomena unfolding on horizon scales in two known black holes, M87* and Sgr A*. However, with this leap in resolution has come a new set of practical complications. Sgr A* exhibits intraday variability that violates the assumptions underlying Earth aperture synthesis, limiting traditional image reconstruction methods to short timescales and data sets with very sparse (u, v) coverage. We present a new set of tools to detect and mitigate this variability. We develop a data-driven, model-agnostic procedure to detect and characterize the spatial structure of intraday variability. This method is calibrated against a large set of mock data sets, producing an empirical estimator of the spatial power spectrum of the brightness fluctuations. We present a novel Bayesian noise modeling algorithm that simultaneously reconstructs an average image and statistical measure of the fluctuations about it using a parameterized form for the excess variance in the complex visibilities not otherwise explained by the statistical errors. These methods are validated using a variety of simulated data, including general relativistic magnetohydrodynamic simulations appropriate for Sgr A* and M87*. We find that the reconstructed source structure and variability are robust to changes in the underlying image model. We apply these methods to the 2017 EHT observations of M87*, finding evidence for variability across the EHT observing campaign. The variability mitigation strategies presented are widely applicable to very long baseline interferometry observations of variable sources generally, for which they provide a data-informed averaging procedure and natural characterization of inter-epoch image consistency.

79 ASTRONOMY AND ASTROPHYSICS↗

Resolution enhancement of spaceborne scatterometer data

Spaceborne wind scatterometers are designed principally to measure radar backscatter from the ocean's surface for the determination of the near-surface wind direction and speed. Although measurements of the radar backscatter are made over land, application of these measurements has been limited primarily to the calibration of the instrument. In this paper we present a method for generating enhanced resolution radar images of the earth's surface using spaceborne scatterometry. The technique is based on a new image reconstruction technique which takes advantage of the spatial overlap in scatterometer measurements made at different times to provide enhanced imaging resolution. We describe the reconstruction algorithm and demonstrate the technique using both simulated and actual Seasat-A Scatterometer (SASS) measurements. The SASS-derived images, which have approximately 4 km resolution, dramatically illustrate the resolution enhancement capability of the new technique. The technique permits utilization of both historic and contemporary scatterometer data for medium-scale monitoring of vegetation and polar ice. We discuss the tradeoff between imaging noise and resolution inherent in the technique.

Long, David G.↗

Imaging the sun in hard X-rays - Spatial and rotating modulation collimators

Several approaches to imaging hard X-rays emitted from solar flares have been proposed or are planned for the nineties including the spatial modulation collimator (SMC) and the rotating modulation collimator (RMC). A survey of current solar flare theoretical literature indicates the desirability of spatial resolutions down to 1 arcsecond, field of views greater than the full solar disk (i.e., 32 arcminutes), and temporal resolutions down to 1 second. Although the sun typically provides relatively high flux levels, the requirement for 1 second temporal resolution raises the question as to the viability of Fourier telescopes subject to the aforementioned constraints. A basic photon counting, Monte Carlo 'end-to-end' model telescope was employed using the Astronomical Image Processing System (AIPS) for image reconstruction. The resulting solar flare hard X-ray images compared against typical observations indicated that both telescopes show promise for the future.

Campbell, Jonathan W.↗

(Almost) Featureless Stereo: Calibration and Dense 3D Reconstruction Using Whole Image Operations

The conventional approach to shape from stereo is via feature extraction and correspondences. This results in estimates of the camera parameters and a typically spare estimate of the surface. Given a set of calibrated images, a dense surface reconstruction is possible by minimizing the error between the observed image and the image rendered from the estimated surface with respect to the surface model parameters. Given an uncalibrated image and an estimated surface, the camera parameters can be estimated by minimizing the error between the observed and rendered images a function of the camera parameters. We use a very small dense set of matched features to provide camera parameter estimates for the initial dense surface estimate. We then re-estimate the camera parameters as described above, and then re-estimate the surface. This process is iterated. Whilst it can not be proven to converge, we have found that around three iterations results in excellent surface and camera parameters estimates.

Smelyanskiy, V. N.↗

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↗

High-speed mapping of surface charge dynamics using sparse scanning Kelvin probe force microscopy

Unraveling local dynamic charge processes is vital for progress in diverse fields, from microelectronics to energy storage. This relies on the ability to map charge carrier motion across multiple length- and timescales and understanding how these processes interact with the inherent material heterogeneities. Towards addressing this challenge, we introduce high-speed sparse scanning Kelvin probe force microscopy, which combines sparse scanning and image reconstruction. This approach is shown to enable sub-second imaging (>3 frames per second) of nanoscale charge dynamics, representing several orders of magnitude improvement over traditional Kelvin probe force microscopy imaging rates. Bridging this improved spatiotemporal resolution with macroscale device measurements, we successfully visualize electrochemically mediated diffusion of mobile surface ions on a LaAlO 3 /SrTiO 3 planar device. Such processes are known to impact band-alignment and charge-transfer dynamics at these heterointerfaces. Furthermore, we monitor the diffusion of oxygen vacancies at the single grain level in polycrystalline TiO 2 . Through temperature-dependent measurements, we identify a charge diffusion activation energy of 0.18 eV, in good agreement with previously reported values and confirmed by DFT calculations. Together, these findings highlight the effectiveness and versatility of our method in understanding ionic charge carrier motion in microelectronics or nanoscale material systems.

25 ENERGY STORAGE↗

Observation of sea-ice dynamics using synthetic aperture radar images: Automated analysis

The European Space Agency's ERS-1 satellite, as well as others planned to follow, is expected to carry synthetic-aperture radars (SARs) over the polar regions beginning in 1989. A key component in utilization of these SAR data is an automated scheme for extracting the sea-ice velocity field from a time sequence of SAR images of the same geographical region. Two techniques for automated sea-ice tracking, image pyramid area correlation (hierarchical correlation) and feature tracking, are described. Each technique is applied to a pair of Seasat SAR sea-ice images. The results compare well with each other and with manually tracked estimates of the ice velocity. The advantages and disadvantages of these automated methods are pointed out. Using these ice velocity field estimates it is possible to construct one sea-ice image from the other member of the pair. Comparing the reconstructed image with the observed image, errors in the estimated velocity field can be recognized and a useful probable error display created automatically to accompany ice velocity estimates. It is suggested that this error display may be useful in segmenting the sea ice observed into regions that move as rigid plates of significant ice velocity shear and distortion.

Vesecky, John F.↗