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NASA NTRS1989

Image processing using Gallium Arsenide (GaAs) technology

The need to increase the information return from space-borne imaging systems has increased in the past decade. The use of multi-spectral data has resulted in the need for finer spatial resolution and greater spectral coverage. Onboard signal processing will be necessary in order to utilize the available Tracking and Data Relay Satellite System (TDRSS) communication channel at high efficiency. A generally recognized approach to the increased efficiency of channel usage is through data compression techniques. The compression technique implemented is a differential pulse code modulation (DPCM) scheme with a non-uniform quantizer. The need to advance the state-of-the-art of onboard processing was recognized and a GaAs integrated circuit technology was chosen. An Adaptive Programmable Processor (APP) chip set was developed which is based on an 8-bit slice general processor. The reason for choosing the compression technique for the Multi-spectral Linear Array (MLA) instrument is described. Also a description is given of the GaAs integrated circuit chip set which will demonstrate that data compression can be performed onboard in real time at data rate in the order of 500 Mb/s.

Miller, Warner H.↗

DOE OSTI2023

CASPI: collaborative photon processing for active single-photon imaging

Image sensors capable of capturing individual photons have made tremendous progress in recent years. However, this technology faces a major limitation. Because they capture scene information at the individual photon level, the raw data is sparse and noisy. Here we propose CASPI: Collaborative Photon Processing for Active Single-Photon Imaging, a technology-agnostic, application-agnostic, and training-free photon processing pipeline for emerging high-resolution single-photon cameras. By collaboratively exploiting both local and non-local correlations in the spatio-temporal photon data cubes, CASPI estimates scene properties reliably even under very challenging lighting conditions. We demonstrate the versatility of CASPI with two applications: LiDAR imaging over a wide range of photon flux levels, from a sub-photon to high ambient regimes, and live-cell autofluorescence FLIM in low photon count regimes. We envision CASPI as a basic building block of general-purpose photon processing units that will be implemented on-chip in future single-photon cameras.

47 OTHER INSTRUMENTATION↗

DOE OSTI2024

O-GlcNAc transferase regulates collagen deposition and fibrosis resolution in idiopathic pulmonary fibrosis

Idiopathic pulmonary fibrosis (IPF) is a chronic pulmonary disease that is characterized by an excessive accumulation of extracellular matrix (ECM) proteins (e.g. collagens) in the parenchyma, which ultimately leads to respiratory failure and death. While current therapies exist to slow the progression, no therapies are available to resolve fibrosis. We characterized the O-linked N-Acetylglucosamine (O-GlcNAc) transferase (OGT)/O-GlcNAc axis in IPF using single-cell RNA-sequencing (scRNA-seq) data and human lung sections and isolated fibroblasts from IPF and non-IPF donors. The underlying mechanism(s) of IPF were further investigated using multiple experimental models to modulate collagen expression and accumulation by genetically and pharmacologically targeting OGT. Furthermore, we hone in on the transforming growth factor-beta (TGF-β) effector molecule, Smad3, by co-expressing it with OGT to determine if it is modified and its subsequent effect on Smad3 activation. We found that OGT and O-GlcNAc levels are upregulated in patients with IPF compared to non-IPF. We report that the OGT regulates collagen deposition and fibrosis resolution, which is an evolutionarily conserved process demonstrated across multiple species. Co-expression of OGT and Smad3 showed that Smad3 is O-GlcNAc modified. Blocking OGT activity resulted in decreased phosphorylation at Ser-423/425 of Smad3 attenuating the effects of TGF-β1 induced collagen expression/deposition. OGT inhibition or knockdown successfully blocked and reversed collagen expression and accumulation, respectively. Smad3 is discovered to be a substrate of OGT and its O-GlcNAc modification(s) directly affects its phosphorylation state. These data identify OGT as a potential target in pulmonary fibrosis resolution, as well as other diseases that might have aberrant ECM/collagen accumulation.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2001

In-Flight Edge Response Measurements for High Spatial Resolution Remote Sensing Systems

In-flight measurement of spatial resolution were conducted as part of the ASA Scientific Data Purchase (SDP) Validation and Verification (V&V) process. Characterization included remote sensing systems with ground sample distance (GSD) of 1 meter or less, such as the panchromatic imager on-board the ICONOS satellite and the airborne ADAR System 5500 multispectral instrument. Final image products were used to evaluate the effect of both the image acquisition system (e.g., optics, electronics, motion, jitter, atmosphere) and image post-processing (e.g., resampling, modulation trasfer function (MTF) compensator). Spatial resolution was characterized by full width at half maximum (FWHM) of an edge response-derived line spread function. This was found to be a more robust measure of spatial resolution than the value of NTF at Nyquist frequency The edge responses were analysed using the tilted-edge technique that ovecomes the spatial sampling limitations of the digital imaging systems. As an enhancement to existing algorithms, the slope of the edge response and the orientation of the edge target were determined by a single computational process. Adjacent black and white square panels, either painted on a flat surface or deployed as traps, formed the ground-based edge targets used in the tests. Orientation of the deployable tarps was optimized beforehand, based on simulations of the imaging system. Numerous edge target images were analyzed for each of the tested sensors. The effect of such factors as acquisition geometry, temporal variability, MTF compensation, and GSD on spatial resolution were investigated.

Blonski, Slawomir↗

NASA NTRS1992

Cyclops - The JPL AIRSAR synoptic processor

Capability for synoptic, or wide-area, SAR processing has been added to the JPL Aircraft Synthetic Aperture Radar System (AIRSAR) by means of the CYCLOPS synoptic processor. Polarimetric requirements have been relaxed so that a single node in the system can process SAR data with a throughput of three channels in 3.75 hours. Each channel consists of five minutes of full-range-swath data chosen from the twelve available AIRSAR polarization channels. Processed data consists of 16-look, 16-meter resolution imagery with a swath size of 60 km. The processor fully utilizes the available Doppler bandwidth and provides processing options for range migration correction, zero-Doppler deskew, frequency registration, and radiometric correction. The detected-power output product is scaled so as to provide sigma zero radiometric calibration.

Taylor, Victor B.↗

NASA NTRS1996

The EOS CERES Global Cloud Mask

To detect long-term climate trends, it is essential to produce long-term and consistent data sets from a variety of different satellite platforms. With current global cloud climatology data sets, such as the International Satellite Cloud Climatology Experiment (ISCCP) or CLAVR (Clouds from Advanced Very High Resolution Radiometer), one of the first processing steps is to determine whether an imager pixel is obstructed between the satellite and the surface, i.e., determine a cloud 'mask.' A cloud mask is essential to studies monitoring changes over ocean, land, or snow-covered surfaces. As part of the Earth Observing System (EOS) program, a series of platforms will be flown beginning in 1997 with the Tropical Rainfall Measurement Mission (TRMM) and subsequently the EOS-AM and EOS-PM platforms in following years. The cloud imager on TRMM is the Visible/Infrared Sensor (VIRS), while the Moderate Resolution Imaging Spectroradiometer (MODIS) is the imager on the EOS platforms. To be useful for long term studies, a cloud masking algorithm should produce consistent results between existing (AVHRR) data, and future VIRS and MODIS data. The present work outlines both existing and proposed approaches to detecting cloud using multispectral narrowband radiance data. Clouds generally are characterized by higher albedos and lower temperatures than the underlying surface. However, there are numerous conditions when this characterization is inappropriate, most notably over snow and ice of the cloud types, cirrus, stratocumulus and cumulus are the most difficult to detect. Other problems arise when analyzing data from sun-glint areas over oceans or lakes over deserts or over regions containing numerous fires and smoke. The cloud mask effort builds upon operational experience of several groups that will now be discussed.

Berendes, T. A.↗

DOE OSTI2026

Using 2.5D super-resolution to improve flaw detection in metal additive manufacturing parts

Industrial X-ray computed tomography (XCT) enables non-destructive inspection of additively manufactured (AM) parts, but high-resolution scanning requires long acquisition times and significant computational resources, limiting throughput in production environments. Super-resolution techniques can recover high-resolution information from low-resolution scans, but existing methods face a trade-off between 2D approaches that ignore inter-slice information and 3D methods that are computationally prohibitive for practical deployment. To address this trade-off, we propose a 2.5D deep learning-based super-resolution approach that uses seven neighbouring low-resolution slices to super-resolve the centre slice. This work evaluates the method on real XCT scans of steel AM parts, comparing reconstruction quality and flaw detection performance of 2D, 2.5D, and 3D ESRGAN-based super-resolution methods. Results demonstrate that 2.5D super-resolution significantly improves detection of small, process-induced flaws (e.g. porosity) compared to 2D methods, while avoiding the prohibitive computational burden of full 3D approaches. These findings provide initial evidence of 2.5D super-resolution as a practical, deployable solution for improving flaw detection in high-throughput industrial XCT inspection.

X-ray CT↗

NASA NTRS1983

Initialization of mesoscale models - The possible impact of remotely sensed data

Little or no improvement appears to have been achieved in mesoscale numerical prediction. This has been blamed on inherent unpredictability, insufficient spatial resolution, inadequate parameterization of important physical processes, and errors in the numerical discretization of the governing hydrodynamic equations. Attention is presently given to the more fundamental difficulty of forecasting when present conditions are not known with sufficient accuracy, and to the matching of remotely sensed sounding-capability satellite and all-weather Doppler radar data with mesoscale numerical models. This matching is not straightforward; simple and variational forms of four-dimensional assimilation, and Kalman filtering, are suggested approaches but their practical testing remains to be accomplished. The most severe problem faced is that of the temperature and humidity profiles' vertical resolution.

Gal-Chen, T.↗

DOE OSTI2024

Development of the tangent linear and adjoint models of the global online chemical transport model MPAS-CO 2 v7.3

We describe the development of the tangent linear (TL) and adjoint models of the Model for Prediction Across Scales (MPAS)-CO 2 transport model, which is a global online chemical transport model developed upon the non-hydrostatic Model for Prediction Across Scales – Atmosphere (MPAS-A). The primary goal is to make the model system a valuable research tool for investigating atmospheric carbon transport and inverse modeling. First, we develop the TL code, encompassing all CO 2 transport processes within the MPAS-CO 2 forward model. Then, we construct the adjoint model using a combined strategy involving re-calculation and storage of the essential meteorological variables needed for CO 2 transport. This strategy allows the adjoint model to undertake a long-period integration with moderate memory demands. To ensure accuracy, the TL and adjoint models undergo vigorous verifications through a series of standard tests. The adjoint model, through backward-in-time integration, calculates the sensitivity of atmospheric CO 2 observations to surface CO 2 fluxes and the initial atmospheric CO 2 mixing ratio. To demonstrate the utility of the newly developed adjoint model, we conduct simulations for two types of atmospheric CO 2 observations, namely the tower-based in situ CO 2 mixing ratio and satellite-derived column-averaged CO 2 mixing ratio (X CO 2 ). A comparison between the sensitivity to surface flux calculated by the MPAS-CO 2 adjoint model with its counterpart from CarbonTracker–Lagrange (CT-L) reveals a spatial agreement but notable magnitude differences. These differences, particularly evident for X CO 2 , might be attributed to the two model systems' differences in the simulation configuration, spatial resolution, and treatment of vertical mixing processes. Moreover, this comparison highlights the substantial loss of information in the atmospheric CO 2 observations due to CT-L's spatial domain limitation. Furthermore, the adjoint sensitivity analysis demonstrates that the sensitivities to both surface flux and initial CO 2 conditions spread out throughout the entire Northern Hemisphere within a month. MPAS-CO 2 forward, TL, and adjoint models stand out for their calculation efficiency and variable-resolution capability, making them competitive in computational cost. In conclusion, the successful development of the MPAS-CO 2 TL and adjoint models, and their integration into the MPAS-CO 2 system, establish the possibility of using MPAS's unique features in atmospheric CO 2 transport sensitivity studies and in inverse modeling with advanced methods such as variational data assimilation.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Characterization Techniques Investigated for Characterization of Anomalous Materials in Plutonium Oxide – 25666

The DOE has adopted a Dilute and Dispose approach for processing surplus plutonium which consists of blending plutonium oxide with adulterants and packaging it in a form which is acceptable for disposal at the Waste Isolation Pilot Plant. The feed material for the downblend process is intended to be pure plutonium oxide powder, however other objects are occasionally encountered within the oxide, particularly with legacy material. Potential technologies which could assist in the resolution of incidents where such anomalies are encountered have been investigated. Resolution of these incidents requires characterization of the anomalous object so that plutonium oxide processing can resume and so that a disposition pathway can be determined for the anomalous material. Technologies including gamma ray spectroscopy, alpha-gamma coincidence, LiDAR volumetric measurements, and surface conductivity measurements were investigated for this purpose, with a focus on systems which can be easily introduced into the processing environment when an anomaly is encountered, then removed from the environment after resolution to avoid impeding normal processing activities. This places an emphasis on small and portable measurement systems and systems that can operate in a high-background, oxide-processing environment. Gamma ray systems investigated include the GR1™a CZT detector and the MicroGe™a germanium detector, with a focus on detecting characteristic gamma rays from Pu-239 and other actinides. A gamma ray and alpha particle coincidence method was investigated with the goal of identifying actinides in the presence of a gamma ray background produced by adjacent plutonium oxide material. Leica™b BLK360 G1 and Keyence™c LJ-X8300 LiDAR systems were investigated for use in conjunction with mass measurements to gain accurate material density values, and a Foerster Sigmatest™d 2.070 was tested to determine surface conductivity. The combination of these properties would allow improved identification and characterization of a wide variety of potential anomalous material.

Munson, Justin M.↗

NASA NTRS1991

NASA-SETI microwave observing project: Targeted Search Element (TSE)

The Targeted Search Element (TSE) performs one of two complimentary search strategies of the NASA-SETI Microwave Observing Project (MOP): the targeted search. The principle objective of the targeted search strategy is to scan the microwave window between the frequencies of one and three gigahertz for narrowband microwave emissions eminating from the direction of 773 specifically targeted stars. The scanning process is accomplished at a minimum resolution of one or two Hertz at very high sensitivity. Detectable signals will be of a continuous wave or pulsed form and may also drift in frequency. The TSE will possess extensive radio frequency interference (RFI) mitigation and verification capability as the majority of signals detected by the TSE will be of local origin. Any signal passing through RFI classification and classifiable as an extraterrestrial intelligence (ETI) candidate will be further validated at non-MOP observatories using established protocol. The targeted search will be conducted using the capability provided by the TSE. The TSE provides six Targeted Search Systems (TSS) which independently or cooperatively perform automated collection, analysis, storage, and archive of signal data. Data is collected in 10 megahertz chunks and signal processing is performed at a rate of 160 megabits per second. Signal data is obtained utilizing the largest radio telescopes available for the Targeted Search such as those at Arecibo and Nancay or at the dedicated NASA-SETI facility. This latter facility will allow continuous collection of data. The TSE also provides for TSS utilization planning, logistics, remote operation, and for off-line data analysis and permanent archive of both the Targeted Search and Sky Survey data.

Webster, L. D.↗

DOE OSTI2023

Enabling rapid X-ray CT characterisation for additive manufacturing using CAD models and deep learning-based reconstruction

Metal additive manufacturing (AM) offers flexibility and cost-effectiveness for printing complex parts but is limited to few alloys. Qualifying new alloys requires process parameter optimisation to produce consistent, high-quality components. High-resolution X-ray computed tomography (XCT) has not been effective for this task due to artifacts, slow scan speed, and costs. We propose a deep learning-based approach for rapid XCT acquisition and reconstruction of metal AM parts, leveraging computer-aided design models and physics-based simulations of nonlinear interactions between X-ray radiation and metals. This significantly reduces beam hardening and common XCT artifacts. We demonstrate high-throughput characterisation of over a hundred AlCe alloy components, quantifying improvements in characterisation time and quality compared to high-resolution microscopy and pycnometry. Our approach facilitates investigating the impact of process parameters and their geometry dependence in metal AM.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Altered ß-cell Prohormone Processing and Secretion in Type 1 Diabetes

Analysis of data from clinical cohorts and more recently from human pancreatic tissue, indicate that defects in prohormone processing are an early and persistent component of type 1 diabetes pathogenesis. In this Perspectives article, we review the current state of knowledge of alterations in islet prohormone expression and processing in type 1 diabetes, and consider the clinical impact of these findings. Lingering questions, including pathologic etiologies and consequences of altered prohormone expression and secretion in type 1 diabetes, and the natural history of circulating prohormone production in health and disease are considered. Finally, key steps required to move forward in this area are outlined, including longitudinal testing of relevant clinical populations, studies that probe the genetics of altered prohormone processing, the need for combined functional and histologic testing of human pancreatic tissues, continued interrogation of the intersection between prohormone processing and autoimmunity, and optimal assays or approaches for analysis. Successful resolution of these questions may offer the potential to use altered prohormone processing as a pathogenic anchor that can be used to cluster different endotypes enveloping a large set of variables, and inform therapeutic strategies aimed at personalized intervention in the natural history of type 1 diabetes.

Islets, Insulin, Proinsulin, Islet Amyloid Polypep↗

NASA NTRS1993

A data distributed parallel algorithm for ray-traced volume rendering

This paper presents a divide-and-conquer ray-traced volume rendering algorithm and a parallel image compositing method, along with their implementation and performance on the Connection Machine CM-5, and networked workstations. This algorithm distributes both the data and the computations to individual processing units to achieve fast, high-quality rendering of high-resolution data. The volume data, once distributed, is left intact. The processing nodes perform local ray tracing of their subvolume concurrently. No communication between processing units is needed during this locally ray-tracing process. A subimage is generated by each processing unit and the final image is obtained by compositing subimages in the proper order, which can be determined a priori. Test results on both the CM-5 and a group of networked workstations demonstrate the practicality of our rendering algorithm and compositing method.

Ma, Kwan-Liu↗

NASA NTRS1996

Active-Pixel Image Sensors With Programmable Resolution

Active-pixel image sensors with programmable resolution proposed for use in applications in which speed and efficiency of processing of image data enhanced by providing those data at varying resolutions. Such applications include modeling of biological vision, stereoscopic range-finding, recognition of patterns, tracking targets, and progressive transmission of compressed images. In target-tracking application, sensor initially forms low-resolution image from which area of interest identified, then sensor set at high resolution for examination of identified area. Outputs of contiguous pixels combined. Sensor of this type made to act as though it comprised fewer and larger pixels.

Kemeny, Sabrina E.↗

NASA NTRS2011

Online Time Series Analysis of Land Products over Asia Monsoon Region via Giovanni

Time series analysis is critical to the study of land cover/land use changes and climate. Time series studies at local-to-regional scales require higher spatial resolution, such as 1km or less, data. MODIS land products of 250m to 1km resolution enable such studies. However, such MODIS land data files are distributed in 10ox10o tiles, due to large data volumes. Conducting a time series study requires downloading all tiles that include the study area for the time period of interest, and mosaicking the tiles spatially. This can be an extremely time-consuming process. In support of the Monsoon Asia Integrated Regional Study (MAIRS) program, NASA GES DISC (Goddard Earth Sciences Data and Information Services Center) has processed MODIS land products at 1 km resolution over the Asia monsoon region (0o-60oN, 60o-150oE) with a common data structure and format. The processed data have been integrated into the Giovanni system (Goddard Interactive Online Visualization ANd aNalysis Infrastructure) that enables users to explore, analyze, and download data over an area and time period of interest easily. Currently, the following regional MODIS land products are available in Giovanni: 8-day 1km land surface temperature and active fire, monthly 1km vegetation index, and yearly 0.05o, 500m land cover types. More data will be added in the near future. By combining atmospheric and oceanic data products in the Giovanni system, it is possible to do further analyses of environmental and climate changes associated with the land, ocean, and atmosphere. This presentation demonstrates exploring land products in the Giovanni system with sample case scenarios.

Shen, Suhung↗

DOE OSTI2020

Representation of Modes of Variability in Six U.S. Climate Models

We compare the performance of several modes of variability across six U.S. climate modeling groups, with a focus on identifying robust improvements in recent models [including those participating in phase 6 of the Coupled Model Intercomparison Project (CMIP)] compared to previous versions. In particular, we examine the representation of the Madden–Julian oscillation (MJO), El Niño–Southern Oscillation (ENSO), the Pacific decadal oscillation (PDO), the quasi-biennial oscillation (QBO) in the tropical stratosphere, and the dominant modes of extratropical variability, including the southern annular mode (SAM), the northern annular mode (NAM) [and the closely related North Atlantic Oscillation (NAO)], and the Pacific–North American pattern (PNA). Where feasible, we explore the processes driving these improvements through the use of “intermediary” experiments that utilize model versions between CMIP3/5 and CMIP6 as well as targeted sensitivity experiments in which individual modeling parameters are altered. We find clear and systematic improvements in the MJO and QBO and in the teleconnection patterns associated with the PDO and ENSO. Some gains arise from better process representation, while others (e.g., the QBO) from higher resolution that allows for a greater range of interactions. Our results demonstrate that the incremental development processes in multiple climate model groups lead to more realistic simulations over time.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2013

SMAP Radar Processing and Calibration

The Soil Moisture Active Passive (SMAP) mission is part of the NASA space-based Earth observation program, and consists of an L-band radar and radiometer scheduled for launch into sun synchronous orbit in late 2014. A joint effort of the Jet Propulsion Laboratory (JPL) and the Goddard Space Flight Center (GSFC), the SMAP mission draws heavily on the design and risk reduction heritage of the Hydrosphere State (Hydros) mission [1], [2]. The SMAP science and applications objectives are to: 1) understand processes that link the terrestrial water, energy and carbon cycles, 2) estimate global water and energy fluxes at the land surface, 3) quantify net carbon flux in boreal landscapes, 4) enhance weather and climate forecast skill, and 5) develop improved flood prediction and drought monitoring capability. To meet these science objectives, SMAP ground processing will combine the attributes of the radar and radiometer observations (in terms of their spatial resolution and sensitivity to soil moisture, surface roughness, and vegetation) to estimate soil moisture with 4% volumetric accuracy at a resolution of 10 km, and freeze-thaw state at a resolution of 1-3 km. Model sensitivities translate the soil moisture accuracy to a radar backscatter accuracy of 1 dB (1 sigma) at 3 km resolution and a brightness temperature accuracy of 1.3 K at 40 km resolution. This paper will describe the level 1 radar processing and calibration challenges and the choices made so far for the algorithms and software implementation.

Synthetic Aperture Radar (SAR),↗