Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “image sensor”

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 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
NASA NTRS1977

The robot's eyes - Stereo vision system for automated scene analysis

Attention is given to the robot stereo vision system which maintains the image produced by solid-state detector television cameras in a dynamic random access memory called RAPID. The imaging hardware consists of sensors (two solid-state image arrays using a charge injection technique), a video-rate analog-to-digital converter, the RAPID memory, and various types of computer-controlled displays, and preprocessing equipment (for reflexive actions, processing aids, and object detection). The software is aimed at locating objects and transversibility. An object-tracking algorithm is discussed and it is noted that tracking speed is in the 50-75 pixels/s range.

Williams, D. S.↗
NASA NTRS1986

Observations by the Halley multicolor camera

The first image of comet Halley was taken by the multicolor camera (HMC) on 9 March from a distance of 23.6 million km. During the encounter HMC was switched on at 4:12 hr before closest approach CA. It took its first image at 3:06 h before CA. Overall 2043 images were taken in single sensor mode. The inner coma was observed using all 11 filters and polarizers. The transmission curves of the filters (except polarizers) are shown together with the sensitivity of the camera. At 6 min before CA HMC switched to multiple sensor mode taking 4 images almost simultaneously through the clear, blue, and red wideband filters. Only 2% of all data taken could be transmitted in 69 image sets. The last image showing details of the nuclear surface was taken from a slant distance of 1740 km and has a nominal resolution of 39 m per pixel.

Keller, H. U.↗
NASA NTRS1998

Does the UVI on Polar Detect Cosmic Snowballs?

Frank and Sigwarth [1997a] claim that the dark pixels observed in dayglow images obtained by the Earth sensor of the Visible Imaging System (VIS) are due to bombardment of Earth by 20 to 40 ton cosmic snowballs. We have independently studied the same one hour of VIS data Frank and Sigwarth used and have performed detailed statistical analysis of the dark pixels. The characteristics of the dark pixels from the VIS images have been compared to those obtained from the overlapping images from the Ultraviolet Imager (UVI). We find the occurrence distributions of the dark pixels, single and multiple, from VIS and UVI are nearly identical. This result cannot be explained by a -eophysical source since the two cameras have different pixel resolutions: A search for evidence of of spacecraft "wobble" motion, whose presence would indicate that the source is external to the camera, has found that pairs of dark pixel clusters are uniformly distributed in an-le and no preference is observed in the wobble direction. Instrument artifacts as the source of the dark pixels is the most likely explanation for these results. Probability estimates for the occurrence of dark pixel clusters lead us to expect coincident events of instrumental origin to occur frequently in the two cameras. The conclusion of this study is that neither VIS nor UVI provide any scientific evidence that the origin of dark pixels is geophysical.

Parks, G. K.↗
NASA NTRS2023

Evaluation of Snowfall Retrieval Performance of Gpm Constellation Radiometers Relative to Spaceborne Radars

This study assesses the level-2 snowfall retrieval results from 11 passive microwave radiometers generated by the version 5 Goddard profiling algorithm (GPROF) relative to two spaceborne radars: CloudSat Cloud Profiling Radar (CPR) and Global Precipitation Measurement (GPM) Ku-band Precipitation Radar (KuPR). These 11 radiometers include six conical scanning radiometers [Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E), its successor sensor AMSR2, GPM Microwave Imager (GMI), and three Special Sensor Microwave Imager/Sounders (SSMIS)] and five cross-track scanning radiometers [Advanced Technology Microwave Sounder (ATMS) and four Microwave Humidity Sounders (MHS)]. Results show that over ocean conical scanning radiometers have better detection and intensity estimation skills than cross-track sensors, likely due to the availability and usage of the low-frequency channels (e.g., 19 and 37 GHz). Over land, AMSR-E and AMSR2 have noticeably worse performance than other sensors, primarily due to the lack of higher than 89-GHz channels (e.g., 150, 166, and 183 GHz). Over both land and ocean, all 11 sensors severely underestimate the snowfall intensity, which propagates to the widely used level 3 precipitation product [i.e., Integrated Multi-satelliteE Retrievals for GPM (IMERG)]. These conclusions hold regardless of using either KuPR or CPR as the reference, though the statistical metrics vary quantitatively. The conclusions drawn from these comparisons apply solely to the GPROF version 5 algorithm.

Yalei You↗
NASA NTRS2001

Determining Biosignatures by Complexity Analysis in Antarctic Cryptoendolithic Communities

One of the most difficult problems of life detection is that of identifying biosignatures across a wide range of scales using multiple co-registered probes. The technique should be of equal utility across a wide range of search spaces from remote sensors probing volumes of space or planetary surfaces, visual eye or camera searches across the surface of a rock in Antarctica, low resolution microscopic scanning of a rock or a space craft in situ, or high resolution electron microscope and computerized tomography scanning of geobiological samples. We describe here an approach to this problem which derives in large part from past work done in the area of astrophysics - namely the analysis of complexity in galactic signals by data compression methods. This approach is a radically new one for geobiology and astrobiology, and allows us to assess the complexity (and thus potential biogenicity) of an object being examined. This is done by considering the information within pixels of an image (regardless the sensor used to gather the information) as an energetic system capable of description in terms of classical thermodynamics. The image data space is searched by an algorithm that judges complexity via data compression (e.g., the more compressible it is, the less complex, and vice versa) and maximum entropy as originally outlined by Shannon. At present we are implementing methods to utilize images from multiple sensors gathering different kinds of information (e.g., visible gray-scale data, color analyses, UV fluorescence, chemical information, etc). We present here preliminary data from deep UV fluorescence and ESEM (Environmental Scanning Electron Microscope) images from a layered cryptoendolithic community of an Antarctic rock.

Storrie-Lombardi, M. C.↗
NASA NTRS1993

An evaluation of three-dimensional sensors for the extravehicular activity helper/retreiver

The Extravehicular Activity Retriever/Helper (EVAHR) is a robotic device currently under development at the NASA Johnson Space Center that is designed to fetch objects or to assist in retrieving an astronaut who may have become inadvertently de-tethered. The EVAHR will be required to exhibit a high degree of intelligent autonomous operation and will base much of its reasoning upon information obtained from one or more three-dimensional sensors that it will carry and control. At the highest level of visual cognition and reasoning, the EVAHR will be required to detect objects, recognize them, and estimate their spatial orientation and location. The recognition phase and estimation of spatial pose will depend on the ability of the vision system to reliably extract geometric features of the objects such as whether the surface topologies observed are planar or curved and the spatial relationships between the component surfaces. In order to achieve these tasks, accurate sensing of the operational environment and objects in the environment will therefore be critical. The qualitative and quantitative results of empirical studies of three sensors that are capable of providing three-dimensional information to the EVAHR, but using completely different hardware approaches are documented. The first of these devices is a phase shift laser with an effective operating range (ambiguity interval) of approximately 15 meters. The second sensor is a laser triangulation system designed to operate at much closer range and to provide higher resolution images. The third sensor is a dual camera stereo imaging system from which range images can also be obtained. The remainder of the report characterizes the strengths and weaknesses of each of these systems relative to quality of data extracted and how different object characteristics affect sensor operation.

Magee, Michael↗
NASA NTRS1982

Report of subpanel on feature extraction

The state of knowledge in feature extraction for Earth resource observation systems is reviewed and research tasks are proposed. Issues in the subpixel feature estimation problem are defined as: (1) the identification of image models which adequately describe the data and the sensor it is using; (2) the construction of local feature models based on those image models; and (3) the problem of trying to understand these effects of preprocessing on the entire process. The development of ground control point (GCP) libraries for automated selection presents two concerns. One is the organization of these GCP libraries for rectification problems, i.e., the problems of automatically selecting by computer the specific GCP's for particular registration tasks. Second is the importance of integrating ground control patterns in a data base management system, allowing interface to a large number of sensor image types with an automatic selection system. The development of data validation criteria for the comparison of different extraction techniques is also discussed.

Source record↗
NASA NTRS2002

Understanding the Global Water and Energy Cycle Through Assimilation of Precipitation-Related Observations: Lessons from TRMM and Prospects for GPM

Understanding the Earth's climate and how it responds to climate perturbations relies on what we know about how atmospheric moisture, clouds, latent heating, and the large-scale circulation vary with changing climatic conditions. The physical process that links these key climate elements is precipitation. Improving the fidelity of precipitation-related fields in global analyses is essential for gaining a better understanding of the global water and energy cycle. In recent years, research and operational use of precipitation observations derived from microwave sensors such as the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager and Special Sensor Microwave/Imager (SSM/I) have shown the tremendous potential of using these data to improve global modeling, data assimilation, and numerical weather prediction. We will give an overview of the benefits of assimilating TRMM and SSM/I rain rates and discuss developmental strategies for using space-based rainfall and rainfall-related observations to improve forecast models and climate datasets in preparation for the proposed multi-national Global Precipitation Mission (GPM).

Hou, Arthur↗
NASA NTRS2005

New Sensor Technology

The three instruments on the Orbiter Boom Sensor System (OBSS) will use a mix of U.S. and Canadian developed laser, television, infrared, and 3D imaging technologies. The sensors are the: 1) Laser Dynamic Range Imager (LDRI); 2) Intensified Television Camera (ITVC); 3) Laser Camera System (LCS).

Covault, Craig↗
NASA NTRS2011

The GOES-R GeoStationary Lightning Mapper (GLM)

The Geostationary Operational Environmental Satellite (GOES-R) is the next series to follow the existing GOES system currently operating over the Western Hemisphere. Superior spacecraft and instrument technology will support expanded detection of environmental phenomena, resulting in more timely and accurate forecasts and warnings. Advancements over current GOES capabilities include a new capability for total lightning detection (cloud and cloud-to-ground flashes) from the Geostationary Lightning Mapper (GLM), and improved capability for the Advanced Baseline Imager (ABI). The Geostationary Lighting Mapper (GLM) will map total lightning activity (in-cloud and cloud-to-ground lighting flashes) continuously day and night with near-uniform spatial resolution of 8 km with a product refresh rate of less than 20 sec over the Americas and adjacent oceanic regions. This will aid in forecasting severe storms and tornado activity, and convective weather impacts on aviation safety and efficiency among a number of potential applications. In parallel with the instrument development (a prototype and 4 flight models), a GOES-R Risk Reduction Team and Algorithm Working Group Lightning Applications Team have begun to develop the Level 2 algorithms (environmental data records), cal/val performance monitoring tools, and new applications using GLM alone, in combination with the ABI, merged with ground-based sensors, and decision aids augmented by numerical weather prediction model forecasts. Proxy total lightning data from the NASA Lightning Imaging Sensor on the Tropical Rainfall Measuring Mission (TRMM) satellite and regional test beds are being used to develop the pre-launch algorithms and applications, and also improve our knowledge of thunderstorm initiation and evolution. An international field campaign planned for 2011-2012 will produce concurrent observations from a VHF lightning mapping array, Meteosat multi-band imagery, Tropical Rainfall Measuring Mission (TRMM) Lightning Imaging Sensor (LIS) overpasses, and related ground and in-situ lightning and meteorological measurements in the vicinity of Sao Paulo. These data will provide a new comprehensive proxy data set for algorithm and application development.

Goodman, Steven J.↗
NASA NTRS1993

Proceedings of the Augmented VIsual Display (AVID) Research Workshop

The papers, abstracts, and presentations were presented at a three day workshop focused on sensor modeling and simulation, and image enhancement, processing, and fusion. The technical sessions emphasized how sensor technology can be used to create visual imagery adequate for aircraft control and operations. Participants from industry, government, and academic laboratories contributed to panels on Sensor Systems, Sensor Modeling, Sensor Fusion, Image Processing (Computer and Human Vision), and Image Evaluation and Metrics.

Kaiser, Mary K.↗
NASA NTRS1983

The use of multisensor images for Earth Science applications

The use of more than one remote sensing technique is particularly important for Earth Science applications because of the compositional and textural information derivable from the images. The ability to simultaneously analyze images acquired by different sensors requires coregistration of the multisensor image data sets. In order to insure pixel to pixel registration in areas of high relief, images must be rectified to eliminate topographic distortions. Coregistered images can be analyzed using a variety of multidimensional techniques and the acquired knowledge of topographic effects in the images can be used in photogeologic interpretations.

Evans, D.↗
NASA NTRS1989

Methods and decision making on a Mars rover for identification of fossils

A system for automated fusion and interpretation of image data from multiple sensors, including multispectral data from an imaging spectrometer is being developed. Classical artificial intelligence techniques and artificial neural networks are employed to make real time decision based on current input and known scientific goals. Emphasis is placed on identifying minerals which could indicate past life activity or an environment supportive of life. Multispectral data can be used for geological analysis because different minerals have characteristic spectral reflectance in the visible and near infrared range. Classification of each spectrum into a broad class, based on overall spectral shape and locations of absorption bands is possible in real time using artificial neural networks. The goal of the system is twofold: multisensor and multispectral data must be interpreted in real time so that potentially interesting sites can be flagged and investigated in more detail while the rover is near those sites; and the sensed data must be reduced to the most compact form possible without loss of crucial information. Autonomous decision making will allow a rover to achieve maximum scientific benefit from a mission. Both a classical rule based approach and a decision neural network for making real time choices are being considered. Neural nets may work well for adaptive decision making. A neural net can be trained to work in two steps. First, the actual input state is mapped to the closest of a number of memorized states. After weighing the importance of various input parameters, the net produces an output decision based on the matched memory state. Real time, autonomous image data analysis and decision making capabilities are required for achieving maximum scientific benefit from a rover mission. The system under development will enhance the chances of identifying fossils or environments capable of supporting life on Mars

Eberlein, Susan↗
NASA NTRS1995

Traffic Monitor

Intelligent Vision Systems, Inc. (InVision) needed image acquisition technology that was reliable in bad weather for its TDS-200 Traffic Detection System. InVision researchers used information from NASA Tech Briefs and assistance from Johnson Space Center to finish the system. The NASA technology used was developed for Earth-observing imaging satellites: charge coupled devices, in which silicon chips convert light directly into electronic or digital images. The TDS-200 consists of sensors mounted above traffic on poles or span wires, enabling two sensors to view an intersection; a "swing and sway" feature to compensate for movement of the sensors; a combination of electronic shutter and gain control; and sensor output to an image digital signal processor, still frame video and optionally live video.

Source record↗
NASA NTRS2003

Assimilation of Precipitation Information Retrieved from Passive Microwave Sensors

Estimates of surface precipitation and the associated vertical latent heating structure can be retrieved from space-borne passive microwave sensors such as the TRMM Microwave Imager (TMI) and Special Sensor Microwave/Imager (SSM/I). Studies have shown that assimilation of microwave rain rates can improve the quality of global analysis and forecast. Numerical weather prediction (NWP) centers are beginning to make operational use of these data. In the next few years, there will be a gradual increase in microwave rain products available from operational and research satellites, culminating to a target constellation of 9 satellites to provide global rain measurements every 3 hours with the proposed Global Precipitation Measurement (GPM) mission to be launched around 2007. Realizing the full potential of these observations in data assimilation will require continued advances in retrieval algorithms, assimilation techniques, and model physics. I present results from two research efforts at NASA GSFC. The first is on the assimilation of tropical precipitation using temperature/moisture tendency corrections within a continuous variational assimilation framework to improve analyses and forecasts produced by the Goddard Earth Observing System (GEOS) global data assimilation system. Results show that assimilation of TMI and SSM/I rain rates improves not only precipitation and moisture, but also the related clouds, radiation energy fluxes, and large-scale circulations in GEOS analyses. The improved analyses also yield better short-range forecasts, quantitative precipitation forecast (QPF) threat scores, and storm track predictions. The second part consists of results from exploratory experiments on variational assimilation of convective and stratiform latent heating profiles within the general framework of model parameter estimation as a way to identify systematic model errors and optimize physical paremeterization schemes in global forecast and climate models.

Hou, Arthur Y.↗
NASA NTRS2019

LANDSAT 9: Mission Status and Prelaunch Instrument Performance Characterization and Calibration

Landsat 9 is currently under development as a joint effort between NASA and the United States Geological Survey (USGS). Landsat 9 is largely a rebuild of Landsat 8 and has the same two sensors, an Operational Land Imager (OLI) and a Thermal InfraRed Sensor(TIRS). The OLI-2 on Landsat 9, being built by Ball Aerospace, has completed its pre-launch characterization and calibration and is scheduled to be delivered in the summer of 2019. The TIRS-2, with improved stray light performance and increased redundancy for improved reliability, is being built by Goddard Space Flight Center. TIRS-2is undergoing testing through Spring 2019 and is also scheduled for summer2019 delivery. Several improvements to the characterization of both instruments have been incorporated into the testing plan, including improved spectral and radiometric characterization. The instruments will then be integrated onto the spacecraft being built by Northrop Grumman Innovation Systems (NGIS). The mission is targeted to launch as early as December 2020 on an Atlas V.

Landsat↗