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At least 289 records · Page 16

Image analysis used to count and measure etched tracks from ionizing radiation

We have developed techniques to use digitized scanning electron micrographs and computer image analysis programs to measure track densities in lunar soil grains and plastic dosimeters. Tracks in lunar samples are formed by highly ionizing solar energetic particles and cosmic rays during near surface exposure on the Moon. The track densities are related to the exposure conditions (depth and time). Distributions of the number of grains as a function of their track densities can reveal the modality of soil maturation. We worked on two samples identified for a consortium study of lunar weathering effects, 61221 and 67701. They were prepared by the lunar curator's staff as polished grain mounts that were etched in boiling 1 N NaOH for 6 h to reveal tracks. We determined that backscattered electron images taken at 10 percent contrast and approximately 50 percent brightness produced suitable high contrast images for analysis. We used the NIH Image program to cut out areas that were unsuitable for measurement such as edges, cracks, etc. We ascertained a gray-scale threshold of 25 to separate tracks from background. We used the computer to count everything that was two pixels or greater in size and to measure the area to obtain track densities. We found an excellent correlation with manual measurements for track densities below 1 x 10(exp 8) cm(exp -2). For track densities between 1 x 10(exp 8) cm(exp -2) to 1 x 10(exp 9) cm(exp -2) we found that a regression formula using the percentage area covered by tracks gave good agreement with manual measurements. We determined the track density distributions for 61221 and 67701. Sample 61221 is an immature sample, but not pristine. Sample 67701 is a submature sample that is very close to being fully mature. Because only 10 percent of the grains have track densities less than 10(exp 9) cm(exp -2), it is difficulty to determine whether the sample matured in situ or is a mixture of a mature and a submature soil. Although our analysis of plastic dosimeters is at an early stage of development, results are encouraging. The dosimeter was etched in 6.25 N NaOH at 70 deg C for 16 h. We took 200x secondary electron images of the sample and used the NIH Image software to count and measure major and minor diameters of the etched tracks. We calculated the relative track etch rate from a formula that relates it to the major and minor diameters. We made a histogram of the number of tracks versus their relative etch rate. The relative track etching rate is proportional to the linear energy transfer of the particle. With appropriate calibration experiments, the histogram could be used to calculate the radiation dose.

Blanford, George E.↗

Improved Speed and Functionality of a 580-GHz Imaging Radar

With this high-resolution imaging radar system, coherent illumination in the 576-to-589-GHz range and phase-sensitive detection are implemented in an all-solid-state design based on Schottky diode sensors and sources. By employing the frequency-modulated, continuous-wave (FMCW) radar technique, centimeter-scale range resolution has been achieved while using fractional bandwidths of less than 3 percent. The high operating frequencies also permit centimeter-scale cross-range resolution at several-meter standoff distances without large apertures. Scanning of a single-pixel transceiver enables targets to be rapidly mapped in three dimensions, so that the technology can be applied to the detection of concealed objects on persons.

Dengler, Robert↗

Rapid subsurface analysis of frequency-domain thermoreflectance images with K-means clustering

K-means clustering analysis is applied to frequency-domain thermoreflectance (FDTR) hyperspectral image data to rapidly screen the spatial distribution of thermophysical properties at material interfaces. Performing FDTR while raster scanning a sample consisting of 8.6 μm of doped-silicon (Si) bonded to a doped-Si substrate identifies spatial variation in the subsurface bond quality. Routine thermal analysis at select pixels quantifies this variation in bond quality and allows assignment of bonded, partially bonded, and unbonded regions. Performing this same routine thermal analysis across the entire map, however, becomes too computationally demanding for rapid screening of bond quality. To address this, K-means clustering was used to reduce the dimensionality of the dataset from more than 20 000 pixel spectra to just K = 3 component spectra. The three component spectra were then used to express every pixel in the image through a least-squares minimized linear combination providing continuous interpolation between the components across spatially varying features, e.g., bonded to unbonded transition regions. Fitting the component spectra to the thermal model, thermal properties for each K cluster are extracted and then distributed according to the weighting established by the regressed linear combination. Thermophysical property maps are then constructed and capture significant variation in bond quality over 25 μm length scales. The use of K-means clustering to achieve these thermal property maps results in a 74-fold speed improvement over explicit fitting of every pixel.

36 MATERIALS SCIENCE↗

Spatially Resolving Ocean Color and Sediment Dispersion in River Plumes, Coastal Systems, and Continental Shelf Waters

Satellite remote sensing of ocean color in dynamic coastal, inland, and nearshorewaters is impeded by high variability in optical constituents, demands specialized atmospheric correction, and is limited by instrument sensitivity. To accurately detect dispersion of bio-optical properties, remote sensors require ample signal-to-noise ratio (SNR) to sense small variations in ocean color without saturating over bright pixels, an atmospheric correction that can accommodate significantwater-leaving radiance in the near infrared (NIR), and spatial and temporal resolution that coincides with the scales of variability in the environment. Several current and historic space-borne sensors have met these requirements with success in the open ocean, but are not optimized for highly red-reflective and heterogeneous waters such as those found near river outflows or in the presence of sediment resuspension. Here we apply analytical approaches for determining optimal spatial resolution, dominant spatial scales of variability ("patches"), and proportions of patch variability that can be resolved from four river plumes around the world between 2008 and 2011. An offshore region in the Sargasso Sea is analyzed for comparison. A method is presented for processing Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua and Terra imagery including cloud detection, stray lightmasking, faulty detector avoidance, and dynamic aerosol correction using short-wave- and near-infrared wavebands in extremely turbid regions which pose distinct optical and technical challenges. Results showthat a pixel size of approx. 520 mor smaller is generally required to resolve spatial heterogeneity in ocean color and total suspended materials in river plumes. Optimal pixel size increases with distance from shore to approx. 630 m in nearshore regions, approx 750 m on the continental shelf, and approx. 1350 m in the open ocean. Greater than 90% of the optical variability within plume regions is resolvable with 500 m resolution, and small, but significant, differences were found between peak and nadir river flow periods in terms of optimal resolution and resolvable proportion of variability.

MODIS↗

Independent pixel and Monte Carlo estimates of stratocumulus albedo

Monte Carlo radiative transfer methods are employed here to estimate the plane-parallel albedo bias for marine stratocumulus clouds. This is the bias in estimates of the mesoscale-average albedo, which arises from the assumption that cloud liquid water is uniformly distributed. The authors compare such estimates with those based on a more realistic distribution generated from a fractal model of marine stratocumulus clouds belonging to the class of 'bounded cascade' models. In this model the cloud top and base are fixed, so that all variations in cloud shape are ignored. The model generates random variations in liquid water along a single horizontal direction, forming fractal cloud streets while conserving the total liquid water in the cloud field. The model reproduces the mean, variance, and skewness of the vertically integrated cloud liquid water, as well as its observed wavenumber spectrum, which is approximately a power law. The Monte Carlo method keeps track of the three-dimensional paths solar photons take through the cloud field, using a vectorized implementation of a direct technique. The simplifications in the cloud field studied here allow the computations to be accelerated. The Monte Carlo results are compared to those of the independent pixel approximation, which neglects net horizontal photon transport. Differences between the Monte Carlo and independent pixel estimates of the mesoscale-average albedo are on the order of 1% for conservative scattering, while the plane-parallel bias itself is an order of magnitude larger. As cloud absorption increases, the independent pixel approximation agrees even more closely with the Monte Carlo estimates. This result holds for a wide range of sun angles and aspect ratios. Thus, horizontal photon transport can be safely neglected in estimates of the area-average flux for such cloud models. This result relies on the rapid falloff of the wavenumber spectrum of stratocumulus, which ensures that the smaller-scale variability, where the radiative transfer is more three-dimensional, contributes less to the plane-parallel albedo bias than the larger scales, which are more variable. The lack of significant three-dimensional effects also relies on the assumption of a relatively simple geometry. Even with these assumptions, the independent pixel approximation is accurate only for fluxes averaged over large horizontal areas, many photon mean free paths in diameter, and not for local radiance values, which depend strongly on the interaction between neighboring cloud elements.

Cahalan, Robert F.↗

Optimal Binarization of Gray-Scaled Digital Images via Fuzzy Reasoning

A technique for finding an optimal threshold for binarization of a gray scale image employs fuzzy reasoning. A triangular membership function is employed which is dependent on the degree to which the pixels in the image belong to either the foreground class or the background class. Use of a simplified linear fuzzy entropy factor function facilitates short execution times and use of membership values between 0.0 and 1.0 for improved accuracy. To improve accuracy further, the membership function employs lower and upper bound gray level limits that can vary from image to image and are selected to be equal to the minimum and the maximum gray levels, respectively, that are present in the image to be converted. To identify the optimal binarization threshold, an iterative process is employed in which different possible thresholds are tested and the one providing the minimum fuzzy entropy measure is selected.

Dominguez, Jesus A.↗

Temporal Gain Correction for X-Ray Calorimeter Spectrometers

Calorimetric X-ray detectors are very sensitive to their environment. The boundary conditions can have a profound effect on the gain including heat sink temperature, the local radiation temperature, bias, and the temperature of the readout electronics. Any variation in the boundary conditions can cause temporal variations in the gain of the detector and compromise both the energy scale and the resolving power of the spectrometer. Most production X-ray calorimeter spectrometers, both on the ground and in space, have some means of tracking the gain as a function of time, often using a calibration spectral line. For small gain changes, a linear stretch correction is often sufficient. However, the detectors are intrinsically non-linear and often the event analysis, i.e., shaping, optimal filters etc., add additional non-linearity. Thus for large gain variations or when the best possible precision is required, a linear stretch correction is not sufficient. Here, we discuss a new correction technique based on non-linear interpolation of the energy-scale functions. Using Astro-HSXS calibration data, we demonstrate that the correction can recover the X-ray energy to better than 1 part in 104 over the entire spectral band to above 12 keV even for large-scale gain variations. This method will be used to correct any temporal drift of the on-orbit per-pixel gain using on-board calibration sources for the SXS instrument on the Astro-H observatory.

X-ray detector X-ray spectrometer X-ray calorimete↗

Recent History of Large-Scale Ecosystem Disturbances in North America Derived from the AVHRR Satellite Record

Ecosystem structure and function are strongly impacted by disturbance events, many of which in North America are associated with seasonal temperature extremes, wildfires, and tropical storms. This study was conducted to evaluate patterns in a 19-year record of global satellite observations of vegetation phenology from the Advanced Very High Resolution Radiometer (AVHRR) as a means to characterize major ecosystem disturbance events and regimes. The fraction absorbed of photosynthetically active radiation (FPAR) by vegetation canopies worldwide has been computed at a monthly time interval from 1982 to 2000 and gridded at a spatial resolution of 8-km globally. Potential disturbance events were identified in the FPAR time series by locating anomalously low values (FPAR-LO) that lasted longer than 12 consecutive months at any 8-km pixel. We can find verifiable evidence of numerous disturbance types across North America, including major regional patterns of cold and heat waves, forest fires, tropical storms, and large-scale forest logging. Summed over 19 years, areas potentially influenced by major ecosystem disturbances (one FPAR-LO event over the period 1982-2000) total to more than 766,000 km2. The periods of highest detection frequency were 1987-1989, 1995-1997, and 1999. Sub- continental regions of Alaska and Central Canada had the highest proportion (greater than 90%) of FPAR-LO pixels detected in forests, tundra shrublands, and wetland areas. The Great Lakes region showed the highest proportion (39%) of FPAR-LO pixels detected in cropland areas, whereas the western United States showed the highest proportion (16%) of FPAR-LO pixels detected in grassland areas. Based on this analysis, an historical picture is emerging of periodic droughts and heat waves, possibly coupled with herbivorous insect outbreaks, as among the most important causes of ecosystem disturbance in North America.

Potter, Christopher↗

MIP dQ/dx Calibration in DUNE ND-LAr Prototypes with Pixelated Charge Readout

The Deep Underground Neutrino Experiment (DUNE) will be a next-generation long baseline neutrino oscillation experiment that will employ LArTPC technology in a near detector placed at Fermilab and a far detector at the Sanford Underground Research Facility, at a baseline of 1300 km. The DUNE Liquid Argon Near Detector (ND-LAr) design takes into account the high neutrino intensity expected from the beam at the Long-Baseline Neutrino Facility (LBNF): 35 modules, each containing two optically separated time projection chambers, are instrumented with a pixel-based, true 3D charge readout alongside scintillation light traps to disentangle the O(100) interactions expected per 10us beam spill. A robust prototyping program supports ND-LAr’s design: the 2x2 Demonstrator consists of four scaled-down ND-LAr modules exposed to the NuMI beam at Fermilab, and the Full Scale Demonstrator (FSD) is a single ND-LAr module tested with cosmic rays at the University of Bern. We present here an analysis of minimum ionizing particle (MIP) tracks selected from 2x2 beam data and FSD cosmic ray data used to benchmark the pixel-based charge readout simulation and calibration in both detectors, with the ultimate goal of validating the design of DUNE ND-LAr as well as informing future calibration methods. This poster will showcase the dependence of the charge response on track inclination as well as a per-pixel dQ/dX extraction.

Mandujano, Roberto [UC, Irvine]↗

A comparative analysis of YOLOv8 and U-Net image segmentation approaches for transmission electron micrographs of polycrystalline thin films

Metallic thin films offer a platform to experimentally study the dynamics of microstructural evolution, but the required transmission electron microscopy (TEM)-based imaging generates complex images that are challenging to segment and quantify. This work provides a comparative analysis of a new YOLOv8 model and an established U-Net model for bright-field TEM images of polycrystals, employing a framework leveraging physical observables to evaluate performance against two hand-traced benchmark datasets. This methodology obviates the comparison of large, diversely structured, and manually labeled datasets that are required to assess performance on a per-image/per-pixel basis. It is found that the YOLOv8 model, adapted for real-time instance segmentation, has up to 43× faster inferencing (NVIDIA GeForce RTX 4090) compared to U-Net and reconstructs hand-traced grain size distributions (GSDs) with excellent fidelity, finding mean diameter within 3% for grains near an optimal magnification; for grains that deviate from the optimal pixel-diameter, the size of small- (large)-diameter grains is systematically over- (under)-estimated. This is partially mitigated by including scale-aware augmentations during training. Moreover, when the bias is corrected post-inference by a rigid shift in distribution, the YOLOv8 model reproduces ground truth GSDs with exceptional fidelity, with statistical tests indicating <5% probability that the distributions are distinct. Based on ground truth data, calibration curves pertaining to this shift can be constructed for a given model. This issue is not present in the U-Net model’s results, indicating that for quantitative measurements where the true size of objects is of interest, special procedures must be implemented for YOLO-based models.

36 MATERIALS SCIENCE↗

Thoughts on standardization of parameters for image evaluation

Images received for image processing and analysis are obtained from a wide variety of sources and with a wide variety of sensors. Because it is desirable to have image processing algorithms be as universally applicable as possible, they should be designed, where possible, to be insensitive to the parametric variations of the source material. Where this is not possible, these variations must be taken into account. Therefore, it is necessary to consider what parameters may be defined in common across a suite of image types. Objective parameters or measurements of images which, in the proper combinations, may serve as surrogates for real images may be pixel-specific, location dependent, or combinations thereof. Parameters which have proven useful in defining the characteristics of images include the gray scale linearity, granularity of the quantization, spectral content, geometrical fidelity, resolution of the system expressed as either the point spread function or the modulation transfer function, and the spatial frequency content and characteristics of the data itself.

Billingsley, F. C.↗

The bright knots at the tops of soft X-ray flare loops: Quantitative results from Yohkoh

Soft X-ray Telescope (SXT) observations from the Japanese Yohkoh spacecraft have shown that confined bright regions are common features at the tops of flare loops throughout most of the duration of the flares. In this paper we present quantitative results for these flare knots, in relation to other flare regions, for four relatively 'simple' flares. Emission measure distributions, electron temperatures, and electron densities are derived from SXT and Yohkoh Bragg Crystal Spectrometer (BCS) observations. The four flares selected are dominated by what appear to be single-loop structures, with bright knots at the loop tops. The flares are neither long-duration nor impulsive events. The spatial distributions of brightness and emission measure in the flares are found to be quite similar for all four events, even though there are significant differences in dynamical behavior between at least two of the events. Temperatures and densities calculated for these flares are consistent with previous results from many solar experiments. An investigation of intensity correlations between adjacent pixels at the tops of the loops suggests the existence of local disturbances in the magnetic loops that occur on spatial scales less than the radii of the loops.

Doschek, G. A.↗

VLSI Processor For Vector Quantization

Pixel intensities in each kernel compared simultaneously with all code vectors. Prototype high-performance, low-power, very-large-scale integrated (VLSI) circuit designed to perform compression of image data by vector-quantization method. Contains relatively simple analog computational cells operating on direct or buffered outputs of photodetectors grouped into blocks in imaging array, yielding vector-quantization code word for each such block in sequence. Scheme exploits parallel-processing nature of vector-quantization architecture, with consequent increase in speed.

Tawel, Raoul↗

Visible-Infrared Hyperspectral Image Projector

The VisIR HIP generates spatially-spectrally complex scenes. The generated scenes simulate real-world targets viewed by various remote sensing instruments. The VisIR HIP consists of two subsystems: a spectral engine and a spatial engine. The spectral engine generates spectrally complex uniform illumination that spans the wavelength range between 380 nm and 1,600 nm. The spatial engine generates two-dimensional gray-scale scenes. When combined, the two engines are capable of producing two-dimensional scenes with a unique spectrum at each pixel. The VisIR HIP can be used to calibrate any spectrally sensitive remote-sensing instrument. Tests were conducted on the Wide-field Imaging Interferometer Testbed at NASA s Goddard Space Flight Center. The device is a variation of the calibrated hyperspectral image projector developed by the National Institute of Standards and Technology in Gaithersburg, MD. It uses Gooch & Housego Visible and Infrared OL490 Agile Light Sources to generate arbitrary spectra. The two light sources are coupled to a digital light processing (DLP(TradeMark)) digital mirror device (DMD) that serves as the spatial engine. Scenes are displayed on the DMD synchronously with desired spectrum. Scene/spectrum combinations are displayed in rapid succession, over time intervals that are short compared to the integration time of the system under test.

Bolcar, Matthew↗

Deep Convective Cloud Calibration Sensitivity Studies in Support of Radiometrically Scaling GEO Imagers With VIIRS

The NASA CERES SYN1deg product provides the scientific community regional hourly TOA and surface broadband fluxes and clouds. For consistent geostationary (GEO) derived fluxes and clouds the GEO imagers are radiometrically scaled to the Aqua-MODIS calibration reference. The CERES project utilizes GEO and MODIS or VIIRS analogous channel coincident, collocated, and co-angled radiance pairs as the primary method to inter-calibrate the GEO imagers. Tropical deep convective clouds (DCC) are bright, near Lambertian, top of atmosphere pseudo invariant Earth targets that do not rely on coincident ray-matched radiance pairs to radiometrically scale sensors to a common calibration reference. The DCC invariant target (DCC-IT) methodology collectively analyzes all tropical DCC identified pixel radiances by way of probability density function (PDF) distributions. Perfectly inter-calibrated sensor pairs should reveal nearly identical PDF distributions given the same DCC identification criterion. The PDF median, mean, mode, and inflection point statistics were tested as a function of DCC identification criterion using SNPP-VIIRS and Himawari-8 AHI 0.65μm channel radiances during January 2019. It was found that the PDF inflection point provided inter-calibration factors within 0.25% that were nearly independent of DCC identification criterion. The PDF median provided inter-calibration factors within 0.25% for the coldest BT and most stringent homogeneity factors. The PDF mean and mode statistics were inadequate under any DCC conditions. It is critical for the DCC pixel radiances to be anisotropically corrected. The DCC-IT methodology will also be tested for other visible and SWIR bands.

DCC↗

Derivation of scaled surface reflectances from AVIRIS data

A method for retrieving 'scaled surface reflectances' assuming horizontal surfaces having Lambertian reflectances from spectral data collected by Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) is presented here. In this method, the integrated water vapor amount on a pixel by pixel basis is derived from the 0.94 micron and 1.14 micron water vapor absorption features. The transmission spectra of H2O, CO2, O3, N2O, CO, CH4, and O2 in the 0.4-2.5 micron region are simulated. The scattering effect due to atmospheric molecules and aerosols is modeled with the 5S computer code. The AVIRIS radiances are divided by solar irradiances above the atmosphere to obtain the apparent reflectances. The scaled surface reflectances are derived from the apparent reflectances using the simulated atmospheric gaseous transmittances and the simulated molecular and aerosol scattering data. The scaled surface reflectances differ from the real surface reflectances by a multiplicative factor. In order to convert the scaled surface reflectances into real surface reflectances, the slopes and aspects of the surfaces must be known.

Gao, Bo-Cai↗