Search NASA⌕ Search

SEARCH · Search NASA

Results for “pixel reliability”

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

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

At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

NASA Tech Briefs, July 2004

Topics: Optoelectronic Sensor System for Guidance in Docking; Hybrid Piezoelectric/Fiber-Optic Sensor Sheets; Multisensor Arrays for Greater Reliability and Accuracy; Integrated-Optic Oxygen Sensors; Ka-Band Autonomous Formation Flying Sensor; CMOS VLSI Active-Pixel Sensor for Tracking; Lightweight, Self-Deploying Foam Antenna Structures; Electrically Small Microstrip Quarter-Wave Monopole Antennas; A 2-to-28-MHz Phase-Locked Loop; Portable Electromyograph; Open-Source Software for Modeling of Nanoelectronic Devices; Software for Generating Strip Maps from SAR Data; Calibration Software for use with Jurassicprok; Software for Probabilistic Risk Reduction; Software Processes SAR Motion-Measurement Data; Improved Method of Purifying Carbon Nanotubes; Patterned Growth of Carbon Nanotubes or Nanofibers; Lightweight, Rack-Mountable Composite Cold Plate/Shelves; SiC-Based Miniature High-Temperature Cantilever Anemometer; Inlet Housing for a Partial-Admission Turbine; Lightweight Thermoformed Structural Components and Optics; Growing High-Quality InAs Quantum Dots for Infrared Lasers; Selected Papers on Protoplanetary Disks; Module for Oxygenating Water without Generating Bubbles; Coastal Research Imaging Spectrometer; Rapid Switching and Modulation by use of Coupled VCSELs; Laser-Induced-Fluorescence Photogrammetry and Videogrammetry; Laboratory Apparatus Generates Dual-Species Cold Atomic Beam; Laser Ablation of Materials for Propulsion of Spacecraft; Small Active Radiation Monitor; Hybrid Image-Plane/Stereo Manipulation; Partitioning a Gridded Rectangle into Smaller Rectangles; Digital Radar-Signal Processors Implemented in FPGAs; Part 1 of a Computational Study of a Drop-Laden Mixing Layer; and Some Improvements in Signal-Conditioning Circuits.

Source record↗
NASA NTRS2016

VIIRS Reflective Solar Band Radiometric and Stability Evaluation Using Deep Convective Clouds

This work takes advantage of the stable distribution of deep convective cloud (DCC) reflectance measurements to assess the calibration stability and detector difference in Visible Infrared Imaging Radiometer Suite (VIIRS) reflective bands. VIIRS Sensor Data Records (SDRs) from February 2012 to June 2015 are utilized to analyze the long-term trending, detector difference, and half angle mirror (HAM) side difference. VIIRS has two thermal emissive bands with coverage crossing 11 microns for DCC pixel identification. The comparison of the results of these two processing bands is one of the indicators of analysis reliability. The long-term stability analysis shows downward trends (up to approximately 0.4 per year) for the visible and near-infrared bands and upward trends (up to 0.5per year) for the short- and mid-wave infrared bands. The detector difference for each band is calculated as the difference relative to the average reflectance overall detectors. Except for the slightly greater than 1 difference in the two bands at 1610 nm, the detector difference is less than1 for other solar reflective bands. The detector differences show increasing trends for some short-wave bands with center wavelengths from 400 to 600 nm and remain unchanged for the bands with longer center wavelengths. The HAM side difference is insignificant and stable. Those short-wave bands from 400 to 600 nm also have relatively larger HAM side difference, up to 0.25.Comparing the striped images from SDR and the smooth images after the correction validates the analyses of detector difference and HAM side difference. These analyses are very helpful for VIIRS calibration improvement and thus enhance product quality

VIIRS↗
NASA NTRS2026

The Canadian Galactic Emission Mapper (CGEM) A Cosmic Microwave Foreground Experiment

The Canadian Galactic Emission Mapper (CGEM) is a 4-meter single-dish radio telescope located at the Dominion Radio Astrophysical Observatory (DRAO) in Penticton, Canada. CGEM is designed to map polarized Galactic synchrotron emission across the entire northern sky at 8-10 GHz with 1 MHz frequency resolution and ∼ 0.5 degree angular resolution. Its goal is to obtain high-fidelity, low-noise maps of polarized Galactic synchrotron radiation, at frequencies where synchrotron dominates, in order to provide a reliable template for CMB B−mode foreground cleaning. We will show on sky performance of CGEM’s single-pixel azimuthally-symmetric telescope, its coherent, dual-polarized radiometer, and show maps made from commissioning data from the first few months of operation.

Cosmic microwave background↗
NASA NTRS1986

The CCD/Transit Instrument (CTI) data-analysis system

An account is given of the Kitt Peak CCD/Transit Instrument's software for the automated archiving, analysis, and interrogation of each observation night's nearly 450 Mbytes of image data. The analysis phase is performed by a pair of linked algorithms, one of which operates on the absolute pixel-values and the other on the spatial derivative of the data, so that both isolated and merged images are reliably detected in a single pass. This is in due course followed by the automatic comparison of each new detection with a set of predefined templates in parameter space, in order to find such interesting objects as supernovae, quasars, and variable stars.

Cawson, M. G. M.↗
NASA NTRS2013

A Signal Detection Theory Approach to Evaluating Oculometer Data Quality

Currently, data quality is described in terms of spatial and temporal accuracy and precision [Holmqvist et al. in press]. While this approach provides precise errors in pixels, or visual angle, often experiments are more concerned with whether subjects'points of gaze can be said to be reliable with respect to experimentally-relevant areas of interest. This paper proposes a method to characterize oculometer data quality using Signal Detection Theory (SDT) [Marcum 1947]. SDT classification results in four cases: Hit (correct report of a signal), Miss (failure to report a ), False Alarm (a signal falsely reported), Correct Reject (absence of a signal correctly reported). A technique is proposed where subjects' are directed to look at points in and outside of an AOI, and the resulting Points of Gaze (POG) are classified as Hits (points known to be internal to an AOI are classified as such), Misses (AOI points are not indicated as such), False Alarms (points external to AOIs are indicated as in the AOI), or Correct Rejects (points external to the AOI are indicated as such). SDT metrics describe performance in terms of discriminability, sensitivity, and specificity. This paper presentation will provide the procedure for conducting this assessment and an example of data collected for AOIs in a simulated flightdeck environment.

Latorella, Kara↗
NASA NTRS1974

Monitoring the vernal advancement and retrogradation (green wave effect) of natural vegetation

The author has identified the following significant results. Primary emphasis during the period has been given to completing the resource and land use mask overlays for ultimate subsite MSS data extraction and analysis, refining the computer mask program, verifying resultant masks, and evaluating the initial subsite data. Standard deviations for the selected subsites were generally reduced significantly when compared to the values for the overall 7km x 7km test site areas. This indicates that the masking technique has been successful in reducing the variability of the ERTS-1 MSS data for ultimate subsite comparisons with ground data. The techniques used to locate the 7km x 7km test site areas and extract masked subsite data apparently limit the ability to reliably locate identical very small subsite areas for temporal comparisons. Current evidence indicates that areas which include less than about four pixel elements in either dimension are probably unreliable.

Rouse, J. W., Jr.↗
NASA NTRS2008

A Compact, Modular Package for Superconducting Bolometer Arrays

As bolometer arrays grow to ever-larger formats, packaging becomes a more critical engineering issue. We have designed a detector package to house a superconducting bolometer array, SQUID multiplexers, bias and filtering circuitry, and electrical connectors. The package includes an optical filter, magnetic shielding, and has well-defined thermal and mechanical interfaces. An early version of this package has been used successfully in the GISMO 2mm camera, a 128-pixel camera operating at a base temperature of 270mK. A more advanced package permits operation at lower temperatures by providing direct heat sinking to the SQUIDS and bias resistors, which generate the bulk of the dissipation in the package. Standard electrical connectors provide reliable contact while enabling quick installation and removal of the package. We describe how the design compensates for differing thermal expansions, allows heat sinking of the bolometer array, and features magnetic shielding in critical areas. We highlight the performance of this detector package and describe its scalability to 1280-pixel arrays in the near future.

Benford, D.↗
NASA NTRS2005

Satellite Calibration With LED Detectors at Mud Lake

Earth-monitoring instruments in orbit must be routinely calibrated in order to accurately analyze the data obtained. By comparing radiometric measurements taken on the ground in conjunction with a satellite overpass, calibration curves are derived for an orbiting instrument. A permanent, automated facility is planned for Mud Lake, Nevada (a large, homogeneous, dry lakebed) for this purpose. Because some orbiting instruments have low resolution (250 meters per pixel), inexpensive radiometers using LEDs as sensors are being developed to array widely over the lakebed. LEDs are ideal because they are inexpensive, reliable, and sense over a narrow bandwidth. By obtaining and averaging widespread data, errors are reduced and long-term surface changes can be more accurately observed.

Hiller, Jonathan D.↗
NASA NTRS2008

A Compact, Modular Superconducting Bolometer Array Package

We have designed a detector package to house a superconducting bolometer array, SQUID multiplexers, bias and integration circuitry, optical filtering, electrical connectors, and thermal/mechanical interfaces. This package has been used successfully in the GISMO 2mm camera, a 128-pixel camera operating at a base temperature of 270mK. Operation at lower temperatures is allowed by providing direct heat sinking to the SQUIDS and bias resistors, which generate the bulk of the dissipation in the package. Standard electrical connectors provide reliable contact while enabling quick installation and removal of the package. Careful design has gone into the compensation for differing thermal expansions, the need for heat sinking of the bolometer array, and the placement of magnetic shielding in critical areas. In this presentation, we detail the design and performance of this detector package and describe its scalability to 1280- pixel arrays in the near future.

Benford, Dominic J.↗
NASA NTRS1998

The AVIRIS Low Altitude Option-An Approach to Increase Geometric Resolution and Improve Operational Flexibility Simultaneously

From 1987 through 1997 the Airborne Visible-InfraRed Imaging Spectrometer has matured into a remote sensing instrument capable of producing prodigious amounts of high quality data. Using the NASA/Ames ER-2 high altitude aircraft platform, flight operations have become very reliable as well. Being exclusively dependent on the ER-2, however, has limitations: the ER-2 has a narrow cruise envelope which fixes the AVIRIS ground pixel at 20 meters; it requires a significant support infrastructure; and it has a very limited number of bases it can operate from. In the coming years, the ER-2 will also become less available for AVIRIS flights as NASA Earth Observing System satellite underflights increase. Adapting AVIRIS to lower altitude, less specialized aircraft will create a much broader envelope for data acquisition, i.e., higher ground geometric resolution while maintaining nearly the ideal spatial sampling. This approach will also greatly enhance flexibility while decreasing the overall cost of flight operations and field support. Successful adaptation is expected to culminate with a one-month period of demonstration flights.

Sarture, Charles M.↗
NASA NTRS1983

Comparative assessment of LANDSAT-4 MSS and TM data quality for mapping applications in the southeast

The initial objectives of analyses of the MSS data are two-fold: (1) to evaluate the geodetic accuracy of CCT-P data of the test sites; and (2) to improve the geodetic accuracy by additional processing if the original data either do not meet pre-launch specifications or mapping requirements. The location of 45 ground control points (GCP) digitized from 35 U.S. Geological Survey 1:24,000 scale quadrangles (UTM coordinates) were identified in terms of pixel and scan line values. These 46 points are used to establish UTM position error vector distributions in the scene. As an initial check on the geometric reliability of the MSS data, 28 well-distributed GCPs were input to a program which compares the scaled image distances between all possible point pairs with the corresponding map distances and computes the distance differences; that is, the relative positional errors. The relative errors obtained from initial computations averaged about +/- 200 m. These errors could result from a number of sources, including misidentification of GCP locations, UTM coordinate errors introduced by the map digitizing process or errors resulting from data acquisition and geometric processing.

Welch, R.↗
NASA NTRS2021

Improving the CERES SYN Cloud and Flux Products by Identifying GOES-17 Scan Anomalies Using a Convolutional Neural Network

The NASA Clouds and the Earth’s Radiant Energy System (CERES) project relies on top-of-atmosphere (TOA) broadband fluxes derived from geostationary (GEO) satellite imagery to account for the diurnal flux variations between the CERES observation intervals, and thereby produce a synoptic gridded (SYN1deg) product based on continuous temporal observations. Consistent broadband flux derivation depends on accurate radiative property measurements and cloud retrievals, which largely determine the radiance-to-flux conversion process. Therefore, it is important to ensure a high quality of cloud property input in order to maintain a reliable broadband flux record. In Edition 4 of the CERES SYN1deg product, a robust automated image anomaly detection algorithm based on inter-line and inter-pixel differences, spatial variance, and 2-D Fourier analysis has been successful in identifying imagery with linear artifacts, but the line-by-line inspection and cleaning process must still be performed by a human. Therefore, further automation of this quality assurance process is warranted, especially considering the excessive amount of additional cleaning necessitated by the GOES-17 Advance Baseline Imager (ABI) cooling system anomaly. As such, this article highlights advancement of the CERES GEO image artifact cleaning approach based on a convolutional neural network (CNN) for classification of bad scanlines. Once trained, the CNN approach is a computationally inexpensive means to ensure greater consistency in cloud retrievals, and therefore broadband flux derivation, based on GOES-17 measurements.

Benjamin Scarino↗
NASA NTRS1994

Image quality measures and their performance

A number of quality measures are evaluated for gray scale image compression. They are all bivariate exploiting the differences between corresponding pixels in the original and degraded images. It is shown that although some numerical measures correlate well with the observers' response for a given compression technique, they are not reliable for an evaluation across different techniques. The two graphical measures (histograms and Hosaka plots), however, can be used to appropriately specify not only the amount, but also the type of degradation in reconstructed images.

Eskicioglu, Ahmet M.↗
NASA NTRSDate not supplied

Comparing Low-Cost Sensors with Ground-Based and Airborne In-Situ and Column Observations of NO2 and HCHO during the FRAPPE Field Campaign in Colorado, USA

Even in the presence of more reliable air quality tools, low-cost sensors have the benefit of recording data on highly localized spatial and temporal scales, allowing for multiple measurements within a single satellite pixel and on pixel boundaries. However, they are less accurate than their regulatory-grade counterparts, requiring regular co-locations with accepted instruments to ensure their validity. Thus, the addition of low-cost sensors to a field campaign – where reference-grade air quality instruments are abundant – not only provides ample opportunities for low-cost sensor co-location and calibration, but also allows the low-cost instruments to be used for sub-pixel validation, covering more surface area than the regulatory instruments alone with a network of sensors. During the summer of 2014, our low-cost sensor network was deployed during the Front Range Air Pollution and Photochemistry Experiment (FRAPPÉ) campaign conducted to sample the composition of air at and above ground level in northeastern Colorado, USA. The low-cost sensor platform included a suite of gas-phase sensors, notably NO2 and two generalized volatile organic compound (VOC) sensors, which were leveraged together to quantify speciated hydrocarbons such as formaldehyde. These key pollutants were chosen for their impacts on human health and climate change, as well as their inclusion on the TEMPO satellite launching this year. Airborne campaign measurements included slant column optical observations of formaldehyde (HCHO), nitrogen dioxide (NO2), and ozone (O3). Myriad additional in-situ instruments described chemical composition up to approximately 5 km above surface level. Ground-based instrumentation included both stationary and mobile regulatory-grade instruments, which were used for sensor calibration. Machine learning techniques such as artificial neural networks (ANNs) were used to match the low-cost signals to that of the reference-grade instruments. Here, we compare calibrated low-cost sensor data collected at ground level in a variety of locations along Colorado’s Front Range to various data sources from the FRAPPÉ campaign to better understand how well airborne and regulatory ground-based measurements can be extrapolated to other locations. Further, as the slant column measurements act as satellite simulators, we explore how low-cost instruments can be used for satellite validation purposes. Comparisons among these different data types also have important implications in data fusion.

Kristen Okorn↗
NASA NTRS1982

Analysis of high altitude remotely sensed data collected in the Nantucket Shoals experiment 4-15 May, 1981

High altitude ocean color scanner ratios of band 2 (456 to 476 nanometers) to band 4 (539 to 559 nanometers) and band 1 (418 to 438 nanometers) to band 3 (498 to 518 nanometers) had high correlation coefficient values (-0.928 and 0.891 respectively) with seven boat sampled chlorophyll a measurements. The range of chlorophyll a concentrations was small (1.7-2.58 mg/cu m.). Each ratio was used to calculate chlorophyll a values for the center pixel of each scan line on flight lines 5 and 6. The two ratios produced dissimilar chlorophyll a trends. Due to the high noise level in the scanner data, no reliable synoptic chlorophyll a map could be generated with either ratio algorithm.

Ohlhorst, C. W.↗
NASA NTRS2004

Image-Based Computational Fluid Dynamics in Blood Vessel Models: Toward Developing a Prognostic Tool to Assess Cardiovascular Function Changes in Prolonged Space Flights

One of NASA's objectives is to be able to perform a complete, pre-flight, evaluation of cardiovascular changes in astronauts scheduled for prolonged space missions. Computational fluid dynamics (CFD) has shown promise as a method for estimating cardiovascular function during reduced gravity conditions. For this purpose, MRI can provide geometrical information, to reconstruct vessel geometries, and measure all spatial velocity components, providing location specific boundary conditions. The objective of this study was to investigate the reliability of MRI-based model reconstruction and measured boundary conditions for CFD simulations. An aortic arch model and a carotid bifurcation model were scanned in a 1.5T Siemens MRI scanner. Axial MRI acquisitions provided images for geometry reconstruction (slice thickness 3 and 5 mm; pixel size 1x1 and 0.5x0.5 square millimeters). Velocity acquisitions provided measured inlet boundary conditions and localized three-directional steady-flow velocity data (0.7-3.0 L/min). The vessel walls were isolated using NIH provided software (ImageJ) and lofted to form the geometric surface. Constructed and idealized geometries were imported into a commercial CFD code for meshing and simulation. Contour and vector plots of the velocity showed identical features between the MRI velocity data, the MRI-based CFD data, and the idealized-geometry CFD data, with less than 10% differences in the local velocity values. CFD results on models reconstructed from different MRI resolution settings showed insignificant differences (less than 5%). This study illustrated, quantitatively, that reliable CFD simulations can be performed with MRI reconstructed models and gives evidence that a future, subject-specific, computational evaluation of the cardiovascular system alteration during space travel is feasible.

Chatzimavroudis, George P.↗
NASA NTRS2022

Bayesian Deep Learning for Segmentation for Autonomous Safe Planetary Landing

Hazard detection is critical for enabling autonomous landing on planetary surfaces. Current state-of-the-art methods leverage traditional computer vision approaches to automate the identification of safe terrain from input digital elevation models (DEMs). However, performance for these methods can degrade for input DEMs with increased sensor noise. In the last decade, deep learning techniques have been developed for various applications. Nevertheless, their applicability to safety-critical space missions has often been limited due to concerns regarding their outputs’ reliability. In response to these limitations, this paper proposes an application of the Bayesian deep learning segmentation method for hazard detection. The developed approach enables reliable, safe landing site detection by i) generating simultaneously a safety prediction map and its uncertainty map via Bayesian deep learning and semantic segmentation, and ii) using the uncertainty map to filter out the uncertain pixels in the prediction map so that the safe site identification is performed only based on the certain pixels (i.e., pixels for which the model is certain about its safety prediction). Experiments are presented with simulated data based on a Mars HiRISE digital terrain model by varying uncertainty threshold and noise levels to demonstrate the performance of the proposed approach.

Kento Tomita↗
NASA NTRS2009

Comparison of GOES Cloud Classification Algorithms Employing Explicit and Implicit Physics

Cloud-type classification based on multispectral satellite imagery data has been widely researched and demonstrated to be useful for distinguishing a variety of classes using a wide range of methods. The research described here is a comparison of the classifier output from two very different algorithms applied to Geostationary Operational Environmental Satellite (GOES) data over the course of one year. The first algorithm employs spectral channel thresholding and additional physically based tests. The second algorithm was developed through a supervised learning method with characteristic features of expertly labeled image samples used as training data for a 1-nearest-neighbor classification. The latter's ability to identify classes is also based in physics, but those relationships are embedded implicitly within the algorithm. A pixel-to-pixel comparison analysis was done for hourly daytime scenes within a region in the northeastern Pacific Ocean. Considerable agreement was found in this analysis, with many of the mismatches or disagreements providing insight to the strengths and limitations of each classifier. Depending upon user needs, a rule-based or other postprocessing system that combines the output from the two algorithms could provide the most reliable cloud-type classification.

EXPLICIT PHYSICS ALGORITHMS↗