SEARCH · Search NASA

Results for “imaging methods”

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.

SourceResearch connectionFrom yearThrough year

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

At least 847 records · Page 47

All sources NASA NTRS DOE OSTI

NASA NTRS2003

Jupiter Atmospheric Science with JIMO: Linking Science Objectives and Measurement Goals

Although the primary focus of the Jupiter Icy Moons Orbiter (JIMO) mission will be the characterization and study of Jupiter's icy moons, there will be opportunities throughout the mission for unprecendented observations of Jupiter. With an adaptable suite of payload instruments, the atmospheric data collected by JIMO can help to answer fundamental questions about the largest planet in our solar system that remain after (or were generated by) previous spacecraft reconnaissance (e.g. Voyager, Galileo, and Cassini). Near-IR (0.7-4 micron) spectral imaging will most likely be used to identify mineralogies and ices on the Jovian satellites by virtue of their spectral signatures. This same capability is very well tailored for studies of Jovian atmospheric dynamics and structure. Near-IR methane absorption bands allow 2-D mapping of the horizontal wind field at size scales to tens of kms, as well as the height dependence of this field above the ammonia cloud deck (700 to a few mbar), constraining current models of atmospheric vertical structure. Likewise, atmospheric ice aerosols with unique spectroscopic signatures (ammonia ice near 1.5, 2.0, and 2.8 microns and water ice between 3.0 - 3.5 microns) can be detected and mapped using spectral difference imaging or spectrally inclusive principal-component methods. Spectral imaging of the Jovian aurora via (3)H(+) emission lines between 3 - 4 microns can be used to spatially map the interplay between the satellites) Jupiter's magnetosphere, and Jupiter's atmosphere. Each of these measurements addresses one or more fundamental questions related to the energy balance in Jupiter's atmosphere. All of these tunable imaging objectives can be achieved using acousto-optic tunable filters (AOTF's), which have been used for years in ground-based observing instruments and which have been proposed for numerous planetary missions. The application of this technology to the science objectives of both the icy satellites and Jovian atmospheric components of the JIMO mission will be discussed.

Chanover, N. J.↗

NASA NTRS2009

Lossless Astronomical Image Compression and the Effects of Random Noise

In this paper we compare a variety of modern image compression methods on a large sample of astronomical images. We begin by demonstrating from first principles how the amount of noise in the image pixel values sets a theoretical upper limit on the lossless compression ratio of the image. We derive simple procedures for measuring the amount of noise in an image and for quantitatively predicting how much compression will be possible. We then compare the traditional technique of using the GZIP utility to externally compress the image, with a newer technique of dividing the image into tiles, and then compressing and storing each tile in a FITS binary table structure. This tiled-image compression technique offers a choice of other compression algorithms besides GZIP, some of which are much better suited to compressing astronomical images. Our tests on a large sample of images show that the Rice algorithm provides the best combination of speed and compression efficiency. In particular, Rice typically produces 1.5 times greater compression and provides much faster compression speed than GZIP. Floating point images generally contain too much noise to be effectively compressed with any lossless algorithm. We have developed a compression technique which discards some of the useless noise bits by quantizing the pixel values as scaled integers. The integer images can then be compressed by a factor of 4 or more. Our image compression and uncompression utilities (called fpack and funpack) that were used in this study are publicly available from the HEASARC web site.Users may run these stand-alone programs to compress and uncompress their own images.

Pence, William↗

NASA NTRS2016

Simultaneous Boundary-Layer Transition, Tip Vortex, and Blade Deformation Measurements of a Rotor in Hover

This paper describes simultaneous optical measurements of a sub-scale helicopter rotor in the U.S. Army Hover Chamber at NASA Ames Research Center. The measurements included thermal imaging of the rotor blades to detect boundary layer transition; retro-reflective background-oriented schlieren (RBOS) to visualize vortices; and stereo photogrammetry to measure displacements of the rotor blades, to compute spatial coordinates of the vortices from the RBOS data, and to map the thermal imaging data to a three-dimensional surface grid. The test also included an exploratory effort to measure flow near the rotor tip by tomographic particle image velocimetry (tomo PIV)an effort that yielded valuable experience but little data. The thermal imaging was accomplished using an image-derotation method that allowed long integration times without image blur. By mapping the thermal image data to a surface grid it was possible to accurately locate transition in spatial coordinates along the length of the rotor blade.

Rotorcraft↗

NASA NTRS2019

Denoising with Three Dimensional Fourier Transform for Three Dimensional Images, Including Image Sequences

A method of mitigating noise in source image data representing pixels of a 3-D image. The "3-D image" may be any type of 3-D image, regardless of whether the third dimension is spatial, temporal, or some other parameter. The 3-D image is divided into three-dimensional chunks of pixels. These chunks are apodized and a three-dimensional Fourier transform is performed on each chunk, thereby producing a three-dimensional spectrum of each chunk. The transformed chunks are processed to estimate a noise floor based on spectral values of the pixels within each chunk. A noise threshold is then determined, and the spectrum of each chunk is filtered with a denoising filter based on the noise threshold. The chunks are then inverse transformed, and recombined into a denoised 3-D image.

DeForest, Craig E.↗

DOE OSTI2018

Time reversal and phase coherent music techniques for super-resolution ultrasound imaging

Systems and methods for super-resolution ultrasound imaging using a windowed and generalized TR-MUSIC algorithm that divides the imaging region into overlapping sub-regions and applies the TR-MUSIC algorithm to the windowed backscattered ultrasound signals corresponding to each sub-region. The algorithm is also structured to account for the ultrasound attenuation in the medium and the finite-size effects of ultrasound transducer elements. A modified TR-MUSIC imaging algorithm is used to account for ultrasound scattering from both density and compressibility contrasts. The phase response of ultrasound transducer elements is accounted for in a PC-MUSIC system.

47 OTHER INSTRUMENTATION↗

DOE OSTI2018

Windowed time-reversal music technique for super-resolution ultrasound imaging

47 OTHER INSTRUMENTATION↗

NASA NTRS1992

Experiments with recursive estimation in astronomical image processing

Recursive estimation concepts were applied to image enhancement problems since the 70's. However, very few applications in the particular area of astronomical image processing are known. These concepts were derived, for 2-dimensional images, from the well-known theory of Kalman filtering in one dimension. The historic reasons for application of these techniques to digital images are related to the images' scanned nature, in which the temporal output of a scanner device can be processed on-line by techniques borrowed directly from 1-dimensional recursive signal analysis. However, recursive estimation has particular properties that make it attractive even in modern days, when big computer memories make the full scanned image available to the processor at any given time. One particularly important aspect is the ability of recursive techniques to deal with non-stationary phenomena, that is, phenomena which have their statistical properties variable in time (or position in a 2-D image). Many image processing methods make underlying stationary assumptions either for the stochastic field being imaged, for the imaging system properties, or both. They will underperform, or even fail, when applied to images that deviate significantly from stationarity. Recursive methods, on the contrary, make it feasible to perform adaptive processing, that is, to process the image by a processor with properties tuned to the image's local statistical properties. Recursive estimation can be used to build estimates of images degraded by such phenomena as noise and blur. We show examples of recursive adaptive processing of astronomical images, using several local statistical properties to drive the adaptive processor, as average signal intensity, signal-to-noise and autocorrelation function. Software was developed under IRAF, and as such will be made available to interested users.

Busko, I.↗

DOE OSTI2022

Deep-learning-guided high-resolution subsurface reflectivity imaging with application to ground-penetrating radar data

Subsurface reflectivity imaging is one of the most important geophysical characterization methods for revealing subsurface structures. In many cases, accurate subsurface reflectivity imaging is challenging because of, for example, random or coherent noise in the data and sparse source-receiver observation geometry. Here, we develop a deep-learning-guided iterative imaging method to improve subsurface structure imaging. Specifically, we train a supervised neural network to infer a noise-free, high-resolution image from a noisy, low-resolution image and use this estimated image as guidance to regularize least-squares imaging. We develop a systematic method to generate high-quality synthetic training data (data-label pairs) to train the guidance neural network. The trained neural network can provide high-fidelity predictions even for field-data images that are not in the training data. We validate our new imaging method using one synthetic and two field ground-penetrating radar data examples, and find that our method can produce clean, high-resolution subsurface reflectivity images where existing single-pass and least-squares imaging methods fail due to noise and insufficient data coverage.

58 GEOSCIENCES↗

NASA NTRS1989

Television monitor field shifter and an opto-electronic method for obtaining a stereo image of optimal depth resolution and reduced depth distortion on a single screen

A method and apparatus for obtaining a stereo image with reduced depth distortion and optimum depth resolution. Static and dynamic depth distortion and depth resolution trade-off is provided. Cameras obtaining the images for a stereo view are converged at a convergence point behind the object to be presented in the image, and (a) the collection-surface-to-object distance, (b) the camera separation distance, and (c) the focal lengths of zoom lenses for the camera are all increased. Doubling the distances cuts the static depth distortion in half while maintaining image size and depth resolution. Dynamic depth distortion is minimized by panning a stereo view-collecting camera system about a circle which passes through the convergence point and the cameras' first nodal points. Horizontal field shifting of the television fields on a television monitor brings both the monitor and the stereo views within the viewer's limit of binocular fusion.

Daniel B Diner↗

DOE OSTI2015

SU-E-J-137: Image Registration Tool for Patient Setup in Korea Heavy Ion Medical Accelerator Center

Purpose: A potential validation tool for compensating patient positioning error was developed using 2D/3D and 3D/3D image registration. Methods: For 2D/3D registration, digitally reconstructed radiography (DRR) and three-dimensional computed tomography (3D-CT) images were applied. The ray-casting algorithm is the most straightforward method for generating DRR. We adopted the traditional ray-casting method, which finds the intersections of a ray with all objects, voxels of the 3D-CT volume in the scene. The similarity between the extracted DRR and orthogonal image was measured by using a normalized mutual information method. Two orthogonal images were acquired from a Cyber-Knife system from the anterior-posterior (AP) and right lateral (RL) views. The 3D-CT and two orthogonal images of an anthropomorphic phantom and head and neck cancer patient were used in this study. For 3D/3D registration, planning CT and in-room CT image were applied. After registration, the translation and rotation factors were calculated to position a couch to be movable in six dimensions. Results: Registration accuracies and average errors of 2.12 mm ± 0.50 mm for transformations and 1.23° ± 0.40° for rotations were acquired by 2D/3D registration using an anthropomorphic Alderson-Rando phantom. In addition, registration accuracies and average errors of 0.90 mm ± 0.30 mm for transformations and 1.00° ± 0.2° for rotations were acquired using CT image sets. Conclusion: We demonstrated that this validation tool could compensate for patient positioning error. In addition, this research could be the fundamental step for compensating patient positioning error at the first Korea heavy-ion medical accelerator treatment center.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1993

Comparison of three methods for materials identification and mapping with imaging spectroscopy

We are comparing three methods of mapping analysis tools for imaging spectroscopy data. The purpose of this comparison is to understand the advantages and disadvantages of each algorithm so others would be better able to choose the best algorithm or combinations of algorithms for a particular problem. The three algorithms are: (1) the spectralfeature modified least squares mapping algorithm of Clark et al (1990, 1991): programs mbandmap and tricorder; (2) the Spectral Angle Mapper Algorithm(Boardman, 1993) found in the CU CSES SIPS package; and (3) the Expert System of Kruse et al. (1993). The comparison uses a ground-calibrated 1990 AVIRIS scene of 400 by 410 pixels over Cuprite, Nevada. Along with the test data set is a spectral library of 38 minerals. Each algorithm is tested with the same AVIRIS data set and spectral library. Field work has confirmed the presence of many of these minerals in the AVIRIS scene (Swayze et al. 1992).

Clark, Roger N.↗

NASA NTRS1985

Visualization of Coronary Arteries from Intravenous Angiograms

Under most circumstances, the coronary arteries are not satisfactorily visualized in intravenous angiograms. The objective of this study is to develop computer image enhancement methods that will improve the quality of the latent coronary images to a degree sufficient to detect an obstructive lesion. Such a technique, if successful, could be used as a first step alternative to conventional coronary angiography for individuals with ambiguous noninvasive cardiac tests. The determination of no lesion from the intravenous procedure would relieve the need for the conventional angiogram, while verification of an obstructive lesion could be followed by a conventional angiogram. The nature of the imaging problem and a description of the methods and initial processing results are described in this paper.

Selzer, Robert H.↗

NASA NTRS2019

Applicability of Spectral Decomposition by Varimax-Rotated, Principal Component Analysis to the Surface Biology and Geology (SBG) VNIR Mission Concept

Cyanobacterial and Harmful Algal Blooms (CyanoHABs) are a growing concern in coastal and inland waters. But, spectral interference from multiple constituents in optically complex waters can hamper application of remote sensing using traditional image processing methods. The Kent State University (KSU) spectral decomposition method can be applied to multispectral and hyperspectral remote sensing images (e.g. HICO and the NASA Glenn HSI2) to partition and identify signals related to cyanobacteria, algae, pigment degradation products and suspended sediment in each pixel. Fundamental to the use of remote sensing data is the ability to extract independent signals from correlated hyperspectral VNIR data cubes. The Kent State University varimax-rotated, principal component analysis method (VPCA) is important to integrate into the SBG VNIR mission concept because it provides greater specificity, a software-based SNR boost relative to hardware performance, and can assist with Cal/Val, Modeling and Applications. We present examples of the hyperspectral application of the KSU VPCA method with relevance to SBG. The information extracted by VPCA can be validated spectrally or spatially with laboratory and/or in situ sensors, which capture spatial or time series of information at discrete points within remote sensing images. Comparisons show hyperspectral sensors extract more components than multispectral ones, but more independent information can be extracted from multispectral sensors by VPCA than traditional band ratio approaches. The spectral decomposition method is capable of enhancing the signal to noise ratio (SNR) of the NASA Glenn, second-generation hyperspectral imager by a factor of 7x to 20x, with a spectral reproducibility of ±3%. The spectral decomposition method, when compared against existing remote sensing monitoring methods exhibits both greater specificity and a lower detection limit. The method has been validated with multispectral images in Lake Erie to quantify the Microcystis CyanoHAB and from the Indian River Lagoon, Florida to quantify the Brown Tide resulting from A. lagunesnsis. Field operations in the Western Basin of Lake Erie were conducted using a bbe Fluoroprobe to collect vertical profiles and horizontal tows along a transect from the Toledo to the Detroit Lighthouse during coincident satellite overpasses. Extraction of pixel values from the MODIS Aqua sensor yields agreement between in situ field and lab-based measures of cyanobacterial, cryptophyte, diatoms and green algae, suspended sediment and pigment degradation products with R2>0.8.

hyperspectral↗

DOE OSTI2022

Objective Phenotyping of Root System Architecture Using Image Augmentation and Machine Learning in Alfalfa (Medicago sativa L.)

Active breeding programs specifically for root system architecture (RSA) phenotypes remain rare; however, breeding for branch and taproot types in the perennial crop alfalfa is ongoing. Phenotyping in this and other crops for active RSA breeding has mostly used visual scoring of specific traits or subjective classification into different root types. While image-based methods have been developed, translation to applied breeding is limited. This research is aimed at developing and comparing image-based RSA phenotyping methods using machine and deep learning algorithms for objective classification of 617 root images from mature alfalfa plants collected from the field to support the ongoing breeding efforts. Our results show that unsupervised machine learning tends to incorrectly classify roots into a normal distribution with most lines predicted as the intermediate root type. Encouragingly, random forest and TensorFlow-based neural networks can classify the root types into branch-type, taproot-type, and an intermediate taproot-branch type with 86% accuracy. With image augmentation, the prediction accuracy was improved to 97%. Coupling the predicted root type with its prediction probability will give breeders a confidence level for better decisions to advance the best and exclude the worst lines from their breeding program. This machine and deep learning approach enables accurate classification of the RSA phenotypes for genomic breeding of climate-resilient alfalfa.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2015

Book Review: Reiner Salzer and Heinz W. Siesler (Eds.): Infrared and Raman spectroscopic imaging, 2nd ed.

This second edition of "Infrared and Raman Spectroscopic Imaging" propels practitioners in that wide-ranging field, as well as other readers, to the current state of the art in a well-produced and full-color, completely revised and updated, volume. This new edition chronicles the expanded application of vibrational spectroscopic imaging from yesterday's time-consuming point-by-point buildup of a hyperspectral image cube, through the improvements afforded by the addition of focal plane arrays and line scan imaging, to methods applicable beyond the diffraction limit, instructs the reader on the improved instrumentation and image and data analysis methods, and expounds on their application to fundamental biomedical knowledge, food and agricultural surveys, materials science, process and quality control, and many others.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2017

Conversion from film to image plates for transfer method neutron radiography of nuclear fuel

This paper summarizes efforts to characterize and qualify a computed radiography (CR) system for neutron radiography of irradiated nuclear fuel at Idaho National Laboratory (INL). INL has multiple programs that are actively developing, testing, and evaluating new nuclear fuels. Irradiated fuel experiments are subjected to a number of sequential post-irradiation examination techniques that provide insight into the overall behavior and performance of the fuel. One of the first and most important of these exams is neutron radiography, which provides more comprehensive information about the internal condition of irradiated nuclear fuel than any other non-destructive technique to date. Results from neutron radiography are often the driver for subsequent examinations of the PIE program. Features of interest that can be evaluated using neutron radiography include irradiation-induced swelling, isotopic and fuel-fragment redistribution, plate deformations, and fuel fracturing. The NRAD currently uses the foil-film transfer technique with film for imaging fuel. INL is pursuing multiple efforts to advance its neutron imaging capabilities for evaluating irradiated fuel and other applications, including conversion from film to CR image plates. Neutron CR is the current state-of-the-art for neutron imaging of highly-radioactive objects. Initial neutron radiographs of various types of nuclear fuel indicate that radiographs can be obtained of comparable image quality currently obtained using film. This paper provides neutron radiographs of representative irradiated fuel pins along with neutron radiographs of standards that informed the qualification of the neutron CR system for routine use. Additionally, this paper includes evaluations of some of the CR scanner parameters and their effects on image quality.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2015

SU-F-303-02: Achieving 4D MRI in Regular Breathing Cycle with Extended Acquisition Time of Dynamic MR Images

Purpose: The purpose of this study is to develop a technique to obtain four-dimensional (4D) magnetic resonance (MR) images that are more representative of a patient’s typical breathing cycle by utilizing an extended acquisition time while minimizing the image artifacts. Methods: The 4D MR data were acquired with the balanced steady state free precession in two-dimensional sagittal plane of view. Each slice was acquired repeatedly for about 15 s, thereby obtaining multiple images at each of the 10 phases in the respiratory cycle. This improves the probability that at least one of the images were acquired at the desired phase during a regular breathing cycle. To create optimal 4D MR images, an iterative approach was used to identify the set of images that yielded the highest slice-to-slice similarity. To assess the effectiveness of the approach, the data set was truncated into periods of 7 s (50 time points), 11 s (75 time points) and the full 15 s (100 time points). The 4D MR images were then sorted with data of the three different acquisition periods for comparison. Results: In general, the 4D MR images sorted using data from longer acquisition periods showed less mismatched artifacts. In addition, the normalized cross correlation (NCC) between slices of a 4D volume increases with increased acquisition period. The average NCC was 0.791 from the 7 s period, 0.794 from the 11 s period and 0.796 from the 15 s period. Conclusion: Our preliminary study showed that extending the acquisition time with the proposed sorting technique can improve image quality and reduce artifact presence in the 4D MR images. Data acquisition over two breathing cycles is a good trade-off between artifact reduction and scan time. This research was partially funded by the the Center for Radiation Oncology Research from UT MD Anderson Cancer Center.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1999

A Method to Solve Interior and Exterior Camera Calibration Parameters for Image Resection

An iterative method is presented to solve the internal and external camera calibration parameters, given model target points and their images from one or more camera locations. The direct linear transform formulation was used to obtain a guess for the iterative method, and herein lies one of the strengths of the present method. In all test cases, the method converged to the correct solution. In general, an overdetermined system of nonlinear equations is solved in the least-squares sense. The iterative method presented is based on Newton-Raphson for solving systems of nonlinear algebraic equations. The Jacobian is analytically derived and the pseudo-inverse of the Jacobian is obtained by singular value decomposition.

Samtaney, Ravi↗