Data-Driven Artificial Intelligence for Calibration of Hyperspectral Big Data
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42 ENGINEERING↗
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Results for “image quality assessment”
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.
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Fresnel zone plate development for x-ray radiography of hydrodynamic instabilities at the National Ignition Facility
The study of Rayleigh–Taylor (RT) and Richtmyer–Meshkov (RM) instabilities in a planar geometry at high energy densities at the National Ignition Facility (NIF) requires high spatial resolution imaging. We demonstrate the potential of Fresnel zone plates (FZPs) to achieve resolution that would unlock such studies. FZPs are circular aperiodic gratings that use diffraction to focus x rays and produce an image with high spatial resolution. Taking into account the NIF’s challenging environment, we have designed a specific array of five FZPs for a zinc backlighter to take a radiograph of a target with 9 keV x rays. We measured a mean resolution for the FZP of 1.9µm±0.5µm and a ±1mm depth of focus at an x-ray calibration facility as well as a 2.3µm±0.4µm resolution on a resolution wire mesh shot on the NIF. We also performed an in-depth analysis of the image quality to assess the capability to resolve the small features present in RT and RM instabilities.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Study on spectral/radiometric characteristics of the Thematic Mapper for land use applications
Progress under the LANDSAT-4 and 5 Image Data Quality Assessment program for the Thematic Mapper is described. An initial screening of LANDSAT-5 data is performed. Tools are developed to allow access to TIPS-format data. Analysis of scan direction related signal droop is resumed with detailed analysis of nighttime data. A new mathematical model is developed to describe the effect. Coherent noise of a lower frequency than previously reported is discovered and analyzed. Coincident LANDSAT-4 TM and MSS data are analyzed to improve understanding of radiometric relationships between similar wavebands in the two sensors.
Malila, W. A.↗
Study of spectral/radiometric characteristics of the Thematic Mapper for land use applications
Progress during the Environmental Research Institute of Michigan-ERIM's and 5 image data quality assessment program for the thematic mapper is described. Analyses of LANDSAT 5 TM radiometric characteristics were performed. Effects which had earlier been found in LANDSAT 4 TM data were found to be present in LANDSAT 5 data as well, including: (1) scan direction related signal droop; (2) scan correlated level shifts; and (3) low frequency coherent noise. Coincident LANDSAT 4 and 5 raw TM data were analyzed, and band by band relationships between the two sensors were derived. Earlier efforts which developed an information theoretic measure of multispectral information content were continued, comparing TM and MSS information content.
Malila, W. A.↗
Study of spectral/radiometric characteristics of the Thematic Mapper for land use applications
Progress during ERIM's tenth quarter of effort under the LANDSAT-4 and 5 Image Data Quality Assessment program for the Thematic Mapper is described. Coincident LANDSAT-4 and 5 fully corrected (CCT-PT) TM data are analyzed in more detail and revised band-by-band relationships between the two sensors derived. An analysis technique employing the matching of cumulative distributions is developed and used and is believed to offer advantages over the histogram matching procedure currently used to produce LANDSAT data. Multiplicative factors ranging from 0.987 to 1.145 and offsets ranging from -2.7 to -6.2 video quantum levels are required to cause LANDSAT-5 data to match LANDSAT-4 data values. Evidence of low level clipping is found in TM Bands 5 and 7 of LANDSAT-5 but not LANDSAT-4. Analysis of the information content of LANDSAT TM and MSS data is continued. Components of information loss are identified and quantified and the effects of coarsened quantization are explored.
Malila, W. A.↗
Digital Beamforming Based RFI Mitigation for Synthetic Aperture Radar
An increasing challenge for P-band Synthetic Aperture Radar (SAR) is Radio Frequency Interference (RFI). RFI results in image distortions and degrades the derived science products. This makes it critical to apply RFI removal techniques to restore the image quality. New advanced techniques can be achieved with Digital Beamforming (DBF) radars such as EcoSAR. In this paper, we present a Range-Dependent Time Minimum Variance Distortionless Response (RDTMVDR) Beamformer and apply it to EcoSAR flight data during post-processing. The antenna pattern (AP) is adaptively changed for each range line which increases the RFI suppression compared to a fixed AP for each pulse. The interferometric image quality is assessed before and after RFI suppression.
Bollian, Tobias↗
Stereosat - A new astrodynamics challenge
The paper investigates the astrodynamics requirements for a spacecraft which produces stereo images of the land masses of the earth for use in geoscience investigations, cartography and earth resource exploration. It describes a candidate Stereosat imaging product, presents criteria for evaluating potential image quality and usability, and assesses the impact of various spacecraft and astrodynamic factors on image quality. Several challenges are identified and discussed, namely (1) securing adequate image quality for pixel level elevation measurements, (2) determining absolute location of imaged phenomena in remote regions, (3) satisfying the long-term orbit prediction requirements, and (4) transmitting accurate orbit data along with the image data stream. Meeting these challenges will greatly enhance operational facility.
Driver, J. M.↗
Quantum imaging with positronium-decay-emitted gamma rays
The use of entangled gamma rays from positronium decay for quantum-enhanced imaging of dense materials is demonstrated. Quantum ghost images, where only one of the entangled 511-keV photons interacts with the object, are obtained for tantalum samples of varying density using a 210-ps time-resolution dual detector system and a Na-22 positron source. An analysis comparing both classical and quantum imaging modalities is employed to isolate true 511-keV events from background noise. Image quality is quantitatively assessed using transmission ratios and the Michelson contrast. Quantum-correlated images are found to exhibit superior (up to approximately 1.7x, from 0.49 to 0.83 in the thickest sample measured) contrast compared to classical methods and align well with theoretical expectations. These results suggest that quantum ghost imaging with positronium-based entangled gamma rays could significantly enhance noninvasive imaging of high-density objects, with potential applications in areas such as cargo inspection and security screening.
36 MATERIALS SCIENCE↗
Smart Ultrasound Remote Guidance Experiment (SURGE)- Concept of Operations Evaluation for Using Remote Guidance Ultrasound for Planetary Space Flight
Introduction Use of remote guidance (RG) techniques aboard the International Space Station (ISS) has enabled astronauts to collect diagnostic-level ultrasound images. Exploration class missions will require this cohort of (typically) non-formally trained sonographers to operate with greater autonomy given the longer communication delays (2 seconds for ISS vs. >6 seconds for missions beyond the Moon) and communication blackouts. To determine the feasibility and training requirements for autonomous ultrasound image collection by non-expert ultrasound operators, ultrasound images were collected from a similar cohort using three different image collection protocols: RG only, RG with a computer-based learning tool (LT), and autonomous image collection with LT. The groups were assessed for both image quality and time to collect the images. Methods Subjects were randomized into three groups: RG only, RG with LT, and autonomous with LT. Each subject received 10 minutes of standardized training before the experiment. The subjects were tasked with making the following ultrasound assessments: 1) bone fracture and 2) focused assessment with sonography in trauma (FAST) to assess a patient s abdomen. Human factors-related questionnaire data were collected immediately after the assessments. Results The autonomous group did not out-perform the two groups that received RG. The mean time for the autonomous group to collect images was less than the RG groups, however the mean image quality for the autonomous group was less compared to both RG groups. Discussion Remote guidance continues to produce higher quality ultrasound images than autonomous ultrasound operation. This is likely due to near-instant feedback on image quality from the remote guider. Expansion in communication time delays, however, diminishes the capability to provide this feedback, thus requiring more autonomous ultrasound operation. The LT has the potential to be an excellent training and coaching component for autonomous ultrasound image collection during exploration missions.
Hurst, Victor, IV↗
Thematic Mapper image quality - Registration, noise, and resolution
The Landsat-4 satellite has two new imaging radiometers, including the redesigned Multispectral Scanner (MSS) and the Thematic Mapper (TM). The present investigation is concerned with an assessment of TM image quality on the basis of a study of band-to-band registration, periodic noise, and spatial resolution. In the TM images analyzed, the band-to-band registration accuracy of the instrument is very good. A few imperfections were found. Once a stable misregistration is removed, the TM should also meet its registration specifications between focal planes. Spatial resolution analyses in terms of MTF were performed in comparison modes. The forward and backward scans were shown to have virtually identical MTFs.
Wrigley, R. C.↗
Dynamic Differential Image Circle Diameter Measurement Precision Assessment: Application to Burning Droplets
Dynamic measurement precision assessment has been achieved for a differential circle measurement application. Differential circle diameter measurement, in image analysis, typically requires fitting a circle model that optimizes for image distortions, defects or occlusions. The differential task occurs when precise measurements of diameter change are required given object size variation with time. An automated system was designed to provide diameter measurements and associated measurement precision of images of a fuel droplet undergoing combustion in zero gravity for the FLEX-2 dataset. An image gradient-based, least-squares boundary point fitting method to a circle or ellipse model is used for diameter measurement. The presence of soot aggregates poses significant challenges for diameter measurements when it occludes part of the droplet boundary. The precision of the diameter measurements depends upon the image quality. Using synthetic image simulations that model the soot behavior, we developed a model based on image quality measures that assesses the measurement precision for each individual diameter measurement. Thus, diameter measurements with precision assessments were made available for follow-up scientific analysis. As a result, the algorithm's success rate for measurable runs was 98%. In cases of limited occlusion, a measurement precision of ±0.2 pixels for the FLEX-2 dataset was achieved.
42 ENGINEERING↗
A digital scene matching technique for geometric image correction and autonomous navigation
A technique is described for precise registration of two images of the same area, taken under different conditions. The technique, called AUTO-MATCH, involves digital preprocessing of the images to extract edge contours, followed by a correlation of corresponding edge end points. The availability of an array of endpoints makes possible subpixed registration accuracy. The technique is applied to a system for assessment of geometric image quality, to be installed at NASA-Goddard. This system measures the registration vectors over an array of window pairs from LANDSAT images, so as to determine the distortion between them. Similar measurements could be used to infer relative positioning of the spacecraft. The technique is considered for updating the inertial navigation systems of missiles or aircraft. Scene matching between an image obtained aboard the vehicle and a stored reference can eliminate the drift of an inertial platform in order to demonstrate this capability in real time. A laboratory demonstration of AUTO-MATCH is described.
Tisdale, G. E.↗
Quality Assessment of Preclassification Maps Generated From Spaceborne/Airborne Multispectral Images by the \textit{Satellite Image Automatic Mapper} and \textit{Atmospheric/Topographic Correction-Spectral Classification} Software Products: Part 1—Theory
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Andrea Baraldi↗
Automation of Geometric Accuracy Assessment Algorithm
When end-users are using multiple satellite images for a study the first step is often the assessment and rectification of geolocation offsets. We have developed an automated algorithm to calculate the geometric offsets between two satellite images. It splits both images into subset images (chips) and resamples them to a common resolution. Offsets are imposed on matching chips and the Pearson Cross Correlation (PCC) value calculated for each offset, where the best PCC gives the true offsets. With the true offsets corrected for, a quality of image registration is calculated, measurement uncertainty (MU). The MU threshold value is non-uniform across sensors because it depends on spectral characteristics of each sensor. Previously, the MU threshold was determined by manual inspection for each new sensor assessed. In this study, we automated MU threshold determination. 1/MU vs calculated offset approximates a Gaussian function in shape, see abstract image. A Gaussian function is fit to this dataset, and the root of the third derivative is calculated and applied as a quality threshold, removing the data of lower quality from the final assessment of image offsets. We apply this algorithm to commercial satellite data for proof of concept.
Alana Semple↗
Perceptual compression of magnitude-detected synthetic aperture radar imagery
A perceptually-based approach for compressing synthetic aperture radar (SAR) imagery is presented. Key components of the approach are a multiresolution wavelet transform, a bit allocation mask based on an empirical human visual system (HVS) model, and hybrid scalar/vector quantization. Specifically, wavelet shrinkage techniques are used to segregate wavelet transform coefficients into three components: local means, edges, and texture. Each of these three components is then quantized separately according to a perceptually-based bit allocation scheme. Wavelet coefficients associated with local means and edges are quantized using high-rate scalar quantization while texture information is quantized using low-rate vector quantization. The impact of the perceptually-based multiresolution compression algorithm on visual image quality, impulse response, and texture properties is assessed for fine-resolution magnitude-detected SAR imagery; excellent image quality is found at bit rates at or above 1 bpp along with graceful performance degradation at rates below 1 bpp.
Gorman, John D.↗
JACIE: A Model Partnership
The National Aeronautics and Space Administration (NASA), National Oceanic and Atmospheric Administration (NOAA), the United States Department of Agriculture (USDA), and the United States Geological Survey (USGS), and their associates and partners, are directly responsible for establishing and leading a unique interagency team of scientists and engineers who work together to evaluate and enhance the quality remote sensing data for commercial and government use. This team is called "the Joint Agency Commercial Imagery Evaluation (JACIE) team". The team works together to define, prioritize, assign, and assess civil and commercial image quality and jointly sponsors an annual JACIE Civil Commercial Imagery Evaluation workshop with participation support from the remote sensing calibration and validation science community.
Image Data↗
Evaluating Machine Learning-Based MRI Reconstruction Using Digital Image Quality Phantoms
Quantitative and objective evaluation tools are essential for assessing the performance of machine learning (ML)-based magnetic resonance imaging (MRI) reconstruction methods. However, the commonly used fidelity metrics, such as mean squared error (MSE), structural similarity (SSIM), and peak signal-to-noise ratio (PSNR), often fail to capture fundamental and clinically relevant MR image quality aspects. To address this, we propose evaluation of ML-based MRI reconstruction using digital image quality phantoms and automated evaluation methods. Our phantoms are based upon the American College of Radiology (ACR) large physical phantom but created in k-space to simulate their MR images, and they can vary in object size, signal-to-noise ratio, resolution, and image contrast. Our evaluation pipeline incorporates evaluation metrics of geometric accuracy, intensity uniformity, percentage ghosting, sharpness, signal-to-noise ratio, resolution, and low-contrast detectability. We demonstrate the utility of our proposed pipeline by assessing an example ML-based reconstruction model across various training and testing scenarios. The performance results indicate that training data acquired with a lower undersampling factor and coils of larger anatomical coverage yield a better performing model. The comprehensive and standardized pipeline introduced in this study can help to facilitate a better understanding of the performance and guide future development and advancement of ML-based reconstruction algorithms.
47 OTHER INSTRUMENTATION↗
Fully Balanced SSFP Without an Endorectal Coil for Postimplant QA of MRI-Assisted Radiosurgery (MARS) of Prostate Cancer: A Prospective Study
To investigate fully balanced steady-state free precession (bSSFP) with optimized acquisition protocols for magnetic resonance imaging (MRI)-based postimplant quality assessment of low-dose-rate (LDR) prostate brachytherapy without an endorectal coil (ERC).
62 RADIOLOGY AND NUCLEAR MEDICINE↗