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At least 505 records · Page 28

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NASA NTRS1992

Clustering methods for removing outliers from vision-based range estimates

The present approach to the automation of helicopter low-altitude flight uses one or more passive imaging sensors to extract environmental obstacle information; this is then processed via computer-vision techniques to yield a time-varying map of range to obstacles in the sensor's field of view along the vehicle's flight path. Attention is given to two related techniques which can eliminate outliers from a sparse range map, clustering sparse range-map information into different spatial classes that rely on a segmented and labeled image to aid in spatial classification within the image plane.

Hussien, B.↗

NASA NTRS2001

High-Resolution Large-Field-of-View Three-Dimensional Hologram Display System and Method Thereof

A real-time, dynamic, free space-virtual reality, 3-D image display system is enabled by using a unique form of Aerogel as the primary display media. A preferred embodiment of this system comprises a 3-D mosaic topographic map which is displayed by fusing four projected hologram images. In this embodiment, four holographic images are projected from four separate holograms. Each holographic image subtends a quadrant of the 4(pi) solid angle. By fusing these four holographic images, a static 3-D image such as a featured terrain map would be visible for 360 deg in the horizontal plane and 180 deg in the vertical plane. An input, either acquired by 3-D image sensor or generated by computer animation, is first converted into a 2-D computer generated hologram (CGH). This CGH is then downloaded into large liquid crystal (LC) panel. A laser projector illuminates the CGH-filled LC panel and generates and displays a real 3-D image in the Aerogel matrix.

Chao, Tien-Hsin↗

NASA NTRS1987

Science synergism study for EOS on evolution of desert surfaces

The effectiveness of EOS data as a basis for the study of desert surfaces' evolution is presently evaluated for both long and short term geomorphic evolution. Attention is given to the usefulness of such sensor systems planned for EOS as MODIS for regional vegetation distribution/variability monitoring, HIRIS for visible-near IR observations, TIMS for lithological identification, HMMR and SSMI for soil characteristics, LASA for atmospheric profiles, SAR for surface roughness, ALT for two-dimensional topography, ACR for the calibration of imaging sensors, and ERBE for climate modeling and regional surface albedo variation determinations.

Farr, Tom G.↗

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 OSTI2025

End–to–End Metasurface Design for Temperature Imaging via Broadband Planck‐Radiation Regression

A theoretical framework is presented for temperature imaging from long-wavelength infrared (LWIR) thermal radiation (e.g., 8–12 µm) through the end-to-end design of a metasurface-optics frontend and a computational-reconstruction backend. A new nonlinear reconstruction algorithm, “Planck regression”, is introduced to reconstruct the temperature map from a gray scale sensor image, even in the presence of severe chromatic aberration, by exploiting black body and optical physics particular to thermal imaging. This algorithm is combined with an end-to-end approach that optimizes manufacturable, single-layer metasurfaces to yield the most accurate reconstruction. The designs demonstrate high-quality, noise-robust reconstructions of arbitrary temperature maps (including completely random images) in simulations of an ultra-compact thermal-imaging device. Here, it is also shown that Planck regression is much more generalizable to arbitrary images than a straightforward neural-network reconstruction, which requires a large training set of domain-specific images.

36 MATERIALS SCIENCE↗

NASA NTRS1981

Satellite detection of oil on the marine surface

The ability of two widely dissimilar spaceborne imaging sensors to detect surface oil accumulations in the marine environment has been evaluated using broadly different techniques. Digital Landsat multispectral scanner (MSS) data consisting of two visible and two near infrared channels has been processed to enhance contrast between areas of known oil coverage and background clean surface water. These enhanced images have then been compared to surface verification data gathered by aerial reconnaissance during the October 15, 1975, Landsat overpass. A similar evaluation of oil slick imaging potential has been made for digitally enhanced Seasat-A synthetic aperture radar (SAR) data from July 18, 1979. Due to the premature failure of this satellite, however, no concurrent surface verification data were collected. As a substitute, oil slick configuration information has been generated for the comparison using meteorological and oceanographic data. The test site utilized in both studies was the extensive area of natural seepage located off Coal Oil Point, adjacent to the University of California, Santa Barbara.

Wilson, M. J.↗

NASA NTRS2006

3D X-Ray Luggage-Screening System

A three-dimensional (3D) x-ray luggage- screening system has been proposed to reduce the fatigue experienced by human inspectors and increase their ability to detect weapons and other contraband. The system and variants thereof could supplant thousands of xray scanners now in use at hundreds of airports in the United States and other countries. The device would be applicable to any security checkpoint application where current two-dimensional scanners are in use. A conventional x-ray luggage scanner generates a single two-dimensional (2D) image that conveys no depth information. Therefore, a human inspector must scrutinize the image in an effort to understand ambiguous-appearing objects as they pass by at high speed on a conveyor belt. Such a high level of concentration can induce fatigue, causing the inspector to reduce concentration and vigilance. In addition, because of the lack of depth information, contraband objects could be made more difficult to detect by positioning them near other objects so as to create x-ray images that confuse inspectors. The proposed system would make it unnecessary for a human inspector to interpret 2D images, which show objects at different depths as superimposed. Instead, the system would take advantage of the natural human ability to infer 3D information from stereographic or stereoscopic images. The inspector would be able to perceive two objects at different depths, in a more nearly natural manner, as distinct 3D objects lying at different depths. Hence, the inspector could recognize objects with greater accuracy and less effort. The major components of the proposed system would be similar to those of x-ray luggage scanners now in use. As in a conventional x-ray scanner, there would be an x-ray source. Unlike in a conventional scanner, there would be two x-ray image sensors, denoted the left and right sensors, located at positions along the conveyor that are upstream and downstream, respectively (see figure). X-ray illumination may be provided by a single source or by two sources. The position of the conveyor would be detected to provide a means of matching the appropriate left- and right-eye images of an item under inspection. The appropriate right- and left-eye images of an item would be displayed simultaneously to the right and left eyes, respectively, of the human inspector, using commercially available stereo display screens. The human operator could adjust viewing parameters for maximum viewing comfort. The stereographic images thus generated would differ from true stereoscopic images by small distortions that are characteristic of radiographic images in general, but these distortions would not diminish the value of the images for identifying distinct objects at different depths.

Fernandez, Kenneth↗

NASA NTRS2008

Potential Use of a Bayesian Network for Discriminating Flash Type from Future GOES-R Geostationary Lightning Mapper (GLM) data

Continuous monitoring of the ratio of cloud flashes to ground flashes may provide a better understanding of thunderstorm dynamics, intensification, and evolution, and it may be useful in severe weather warning. The National Lighting Detection Network TM (NLDN) senses ground flashes with exceptional detection efficiency and accuracy over most of the continental United States. A proposed Geostationary Lightning Mapper (GLM) aboard the Geostationary Operational Environmental Satellite (GOES-R) will look at the western hemisphere, and among the lightning data products to be made available will be the fundamental optical flash parameters for both cloud and ground flashes: radiance, area, duration, number of optical groups, and number of optical events. Previous studies have demonstrated that the optical flash parameter statistics of ground and cloud lightning, which are observable from space, are significantly different. This study investigates a Bayesian network methodology for discriminating lightning flash type (ground or cloud) using the lightning optical data and ancillary GOES-R data. A Directed Acyclic Graph (DAG) is set up with lightning as a "root" and data observed by GLM as the "leaves." This allows for a direct calculation of the joint probability distribution function for the lighting type and radiance, area, etc. Initially, the conditional probabilities that will be required can be estimated from the Lightning Imaging Sensor (LIS) and the Optical Transient Detector (OTD) together with NLDN data. Directly manipulating the joint distribution will yield the conditional probability that a lightning flash is a ground flash given the evidence, which consists of the observed lightning optical data [and possibly cloud data retrieved from the GOES-R Advanced Baseline Imager (ABI) in a more mature Bayesian network configuration]. Later, actual GLM and NLDN data can be used to refine the estimates of the conditional probabilities used in the model; i.e., the Bayesian network is a learning network. Methods for efficient calculation of the conditional probabilities (e.g., an algorithm using junction trees), finding data conflicts, goodness of fit, and dealing with missing data will also be addressed.

Solakiewiz, Richard↗

NASA NTRS2016

Evaluation of GLAMR-Based Calibration for SI-Traceable Field Reflectance Retrievals

The reflected solar instrument that is part of the Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission is being formulated with a goal of providing SI-traceable measurement of radiance that is an order of magnitude more accurate than the current imaging sensors. The Goddard Laser for Absolute Measurement of Radiance (GLAMR) is a key element to reaching such accuracy along with transferring the laboratory calibration to on-orbit measurements. Results from field reflectance retrievals using three separate instruments all of which have been calibrated using GLAMR are shown. The instruments include a commercial field spectrometer and a portable version of CLARREO's calibration demonstration system. The third instrument is NASA Goddard's Lidar, Hyperspectral and Thermal Imager (G-LiHT) which is an airborne system. All three were operated during a March 2013 measurement campaign at Red Lake Playa, Arizona as part of the on-orbit commissioning phase of Landsat 8. Reflectance is derived from near-coincident measurements by the three sensors for a small area of the playa. The retrieved results are SI-traceable and demonstrate the ability to transfer the GLAMR calibration to the field. Use of the G-LiHT data in the calibration of Landsat-7 and -8 sensors permits them both to be placed on the GLAMR-scale as well.

Angal, Amit↗

DOE OSTI2021

Measurement of the ionization response of amorphous selenium with 122 keV γ rays

In this work, we performed a measurement of the ionization response of 200 μm-thick amorphous selenium (aSe) layers under drift electric fields of up to 50 V/μm. The aSe target was exposed to ionizing radiation from a 57 Co radioactive source and the ionization pulses were recorded with high resolution. Using the spectral line from the photoabsorption of 122 keV γ rays, we measured the charge yield in aSe and the line width as a function of drift electric field. From a detailed microphysics simulation of charge generation and recombination in aSe, we conclude that the strong dependence of recombination on the ionization track density provides the dominant contribution to the energy resolution in aSe. These results provide valuable input to estimate the sensitivity of a proposed next-generation search for the neutrinoless ββ decay of 82 Se that aims to employ imaging sensors with an active layer of aSe. We estimate the RMS line width of the integrated ionization signal from neutrinoless ββ decay events (of deposited energy 3 MeV) to be 2.0% for a drift field of 50 V/μm. The energy resolution can be improved to 1% by correcting for the charge yield as a function of ionization density along the imaged electron tracks.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS1977

Application of the high resolution return beam vidicon

The Return Beam Vidicon (RBV) is a high-performance electronic image sensor and electrical storage component. It can accept continuous or discrete exposures. Information can be read out with a single scan or with many repetitive scans for either signal processing or display. Resolution capability is 10,000 TV lines/height, and at 100 lp/mm, performance matches or exceeds that of film, particularly with low-contrast imagery. Electronic zoom can be employed effectively for image magnification and data compression. The high performance and flexibility of the RBV permit wide application in systems for reconnaissance, scan conversion, information storage and retrieval, and automatic inspection and test. This paper summarizes the characteristics and performance parameters of the RBV and cites examples of feasible applications.

Cantella, M. J.↗

NASA NTRS1999

Optical Detection of Lightning from Space

Two primary detection techniques (optical and RF) have a proven capability for detecting lightning from low earth orbit. However, the lightning processes that generate the optical and RF signals are vastly different providing significantly different information content from each sensor type. Because of the intervening ionosphere, low frequency RF components do not reach satellite altitudes. As a consequence, many of the processes associated with the major energy release of a lightning event (i.e. return strokes, k-changes, recoil streamers, etc), in all likelihood contribute little to the RF signal arriving at the satellite. The optical output from lighting, on the other hand, has been shown to be highly correlated with the energetic, charge-transferring processes mentioned above. On the down side, the optical energy, while essentially unaffected by the atmosphere once it emerges from the cloud, is heavily scattered within the cloud. While there is little absorption by the cloud, the great optical depth makes the total light energy emerging from the cloud to be dependent on where in the cloud the lightning occurred. Analyses suggest that when lightning is confined to the lowest regions of the cloud, the light is strongly attenuated and detection becomes problematic. Fortunately, the vast majority of lightning flashes are comprised of channels that propagate through the middle of the cloud and higher. These flashes produce bright signals at the top of a cloud and are readily detectable. Presently, we have two optical instruments in orbit. The Optical Transient Detector (OTD) has been orbiting the earth since April, 1995, while the Lightning Imaging Sensor (LIS) was launched on the Tropical Rainfall Measuring Mission (TRMM) in November of 1997. Both instruments are relatively small, solid state optical imagers, designed specifically to detect and locate lightning activity from low earth orbit with high detection efficiency and location accuracy.

Christian, H. J.↗

NASA NTRS2007

Great Lakes Hyperspectral Water Quality Instrument Suite for Airborne Monitoring of Algal Blooms

NASA Glenn Research Center and NOAA Great Lakes Environmental Research Lab are collaborating to utilize an airborne hyperspectral imaging sensor suite to monitor Harmful Algal Blooms (HABs) in the western basin of Lake Erie. The HABs are very dynamic events as they form, spread and then disappear within a 4 to 8 week time period in late summer. They are a concern for human health, fish and wildlife because they can contain blue green toxic algae. Because of this toxicity there is a need for the blooms to be continually monitored. This situation is well suited for aircraft based monitoring because the blooms are a very dynamic event and they can spread over a large area. High resolution satellite data is not suitable by itself because it will not give the temporal resolution due to the infrequent overpasses of the quickly changing blooms. A custom designed hyperspectral imager and a point spectrometer mounted on aT 34 aircraft have been used to obtain data on an algal bloom that formed in the western basin of Lake Erie during September 2006. The sensor suite and operations will be described and preliminary hyperspectral data of this event will be presented

Lekki, John↗

DOE OSTI2022

Evaluation of UAV-derived multimodal remote sensing data for biomass prediction and drought tolerance assessment in bioenergy sorghum

Screening for drought tolerance is critical to ensure high biomass production of bioenergy sorghum in arid or semi-arid environments. The bottleneck in drought tolerance selection is the challenge of accurately predicting biomass for a large number of genotypes. Although biomass prediction by low-altitude remote sensing has been widely investigated on various crops, the performance of the predictions are not consistent, especially when applied in a breeding context with hundreds of genotypes. In some cases, biomass prediction of a large group of genotypes benefited from multimodal remote sensing data; while in other cases, the benefits were not obvious. In this study, we evaluated the performance of single and multimodal data (thermal, RGB, and multispectral) derived from an unmanned aerial vehicle (UAV) for biomass prediction for drought tolerance assessments within a context of bioenergy sorghum breeding. The biomass of 360 sorghum genotypes grown under well-watered and water-stressed regimes was predicted with a series of UAV-derived canopy features, including canopy structure, spectral reflectance, and thermal radiation features. Biomass predictions using canopy features derived from the multimodal data showed comparable performance with the best results obtained with the single modal data with coefficients of determination (R 2 ) ranging from 0.40 to 0.53 under water-stressed environment and 0.11 to 0.35 under well-watered environment. The significance in biomass prediction was highest with multispectral followed by RGB and lowest with the thermal sensor. Finally, two well-recognized yield-based drought tolerance indices were calculated from ground truth biomass data and UAV predicted biomass, respectively. Results showed that the geometric mean productivity index outperformed the yield stability index in terms of the potential for reliable predictions by the remotely sensed data. Collectively, this study demonstrated a promising strategy for the use of different UAV-based imaging sensors to quantify yield-based drought tolerance.

09 BIOMASS FUELS↗

NASA NTRS1984

Summary of workshop on the application of VLSI for robotic sensing

It was one of the objectives of the considered workshop to identify near, mid, and far-term applications of VLSI for robotic sensing and sensor data preprocessing. The workshop was also to indicate areas in which VLSI technology can provide immediate and future payoffs. A third objective is related to the promotion of dialog and collaborative efforts between research communities, industry, and government. The workshop was held on March 24-25, 1983. Conclusions and recommendations are discussed. Attention is given to the need for a pixel correction chip, an image sensor with 10,000 dynamic range, VLSI enhanced architectures, the need for a high-density serpentine memory, an LSI-tactile sensing program, an analog-signal preprocessor chip, a smart strain gage, a protective proximity envelope, a VLSI-proximity sensor program, a robot-net chip, and aspects of silicon micromechanics.

Brooks, T.↗

NASA NTRS2018

A Monolithic 2k x 2k LWIR HgCdTe Detector Array for Passively Cooled Space Missions

A 2K x 2K 10 µm cutoﬀ HgCdTe array for background-limited space astronomy has been developed by Teledyne Imaging Sensors to speciﬁcations set by JPL, and demonstrated by University of Rochester at a focal plane temperature of 40K for the proposed JPL Near-Earth Object Camera (NEOCam) survey mission under the NASA Planetary Defense Coordination Oﬃce. We describe the detector performance for the ﬁrst large format monolithic HgCdTe detector array tested, including the dark current, well depth, dark current vs. temperature, quantum eﬃciency, latent image performance, and read noise.

Pan, Jianmei↗

NASA NTRS2018

A Monolithic 2k x 2k LWIR HgCdTe Detector Array for Passively Cooled Space Missions

Pan, Jianmei↗

NASA NTRS1980

Concepts for on-board satellite image registration, volume 1

The NASA-NEEDS program goals present a requirement for on-board signal processing to achieve user-compatible, information-adaptive data acquisition. One very specific area of interest is the preprocessing required to register imaging sensor data which have been distorted by anomalies in subsatellite-point position and/or attitude control. The concepts and considerations involved in using state-of-the-art positioning systems such as the Global Positioning System (GPS) in concert with state-of-the-art attitude stabilization and/or determination systems to provide the required registration accuracy are discussed with emphasis on assessing the accuracy to which a given image picture element can be located and identified, determining those algorithms required to augment the registration procedure and evaluating the technology impact on performing these procedures on-board the satellite.

Ruedger, W. H.↗