Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “registration”

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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

High registration particles-transferring system

Disclosed herein are implementations of a particles-transferring system, particle transferring unit, and method of transferring particles in a pattern. In one implementation, a particles-transferring system includes a first substrate including a first surface to support particles in a pattern, particle transferring unit including an outer surface to be offset from the first surface by a first gap, and second substrate including a second surface to be offset from the outer surface by a second gap. The particle transferring unit removes the particles from the first surface in response to the particles being within the first gap, secures the particles in the pattern to the outer surface, and transports the particles in the pattern. The second substrate removes the particles in the pattern from the particle transferring unit in response to the particles being within the second gap. The particles are to be secured in the pattern to the second surface.

36 MATERIALS SCIENCE↗
DOE OSTI2023

High registration particles-transferring system

Disclosed herein are implementations of a particles-transferring system, particle transferring unit, and method of transferring particles in a pattern. In one implementation, a particles-transferring system includes a first substrate including a first surface to support particles in a pattern, particle transferring unit including an outer surface to be offset from the first surface by a first gap, and second substrate including a second surface to be offset from the outer surface by a second gap. The particle transferring unit removes the particles from the first surface in response to the particles being within the first gap, secures the particles in the pattern to the outer surface, and transports the particles in the pattern. The second substrate removes the particles in the pattern from the particle transferring unit in response to the particles being within the second gap. The particles are to be secured in the pattern to the second surface.

Wang, Yunda↗
NASA NTRS1984

Geometric Accuracy Assessment of LANDSAT-4 Multispectral Scanner (MSS)

Standard LANDSAT-4 MSS digital image data were analyzed for geometric accuracy using two P-format (UTM projection) images of the Washington, D.C. area, scene day 109 (ID number 4010915140) and scene day 125 (ID number 4012515144). Both scenes were tested for geodetic registration accuracy (scene-to-map), temporal registration accuracy (scene-to-scene), and band-to-band registration accuracy (within a scene). The combined RMS error for geodetic registration accuracy was 0.43 pixel (25.51 meters), well within specifications. The comparison between the 2 scenes was made on a band-by-band basis. The 90 percent error figure for temporal registration was 0.68 (57x57) pixel (38.8 meters). Although this figure is larger than the specification, it can be considered excellent with respect to user application. The best case registration errors between bands 1 and 2, and 3 and 4 were 14.2m and 13.7m, respectively, both within specifications. The worst case registration error was 38.0 m between bands 2 and 3.

Imhoff, M. L.↗
DOE OSTI2026

SpaceNet 9—Cross-Sensor Alignment of Optical and SAR Imagery

Precise registration of high-resolution synthetic aperture radar (SAR) and optical imagery is necessary for realizing the full potential and benefits of multimodal image analysis. However, two significant challenges presently exist. First, there is a lack of annotated datasets and benchmarks available for high-resolution SAR–optical image registration. Second, an assessment of efficient and reliable image registration methods that can precisely align these modalities is lacking. Here, we present a holistic description of the SpaceNet 9 Challenge and its results. We present a description of the dataset and baseline algorithm along with the results of the challenge, including a description of the winning algorithms. We release the SpaceNet 9 dataset along with open-sourcing the winning algorithms and baseline. The objective of SpaceNet 9 was to compute a dense displacement map that indicates the shift needed to align pixels in an optical image to the pixels in a SAR image. The challenge launched in April 2025 and was active for approximately two months. The top five solutions reduced image alignment error from approximately 34 m to under 13 m for public and private test data, with the best results obtaining a registration error of only 8.5 and 6.7 m on the public testing and private testing dataset, respectively. Usage of pretrained image matching models, robust outlier rejection with RANSAC, and estimating local displacement were common among the top solutions. The results of this challenge provide insight into high-resolution SAR–optical image registration and offer opportunities for future benchmarking in this domain. The baseline algorithm, winning solutions, and datasets are available at https://spacenet.ai/sn9-challenge/.

benchmark datasets↗
NASA NTRS1976

Experimental study of digital image processing techniques for LANDSAT data

The author has identified the following significant results. Results are reported for: (1) subscene registration, (2) full scene rectification and registration, (3) resampling techniques, (4) and ground control point (GCP) extraction. Subscenes (354 pixels x 234 lines) were registered to approximately 1/4 pixel accuracy and evaluated by change detection imagery for three cases: (1) bulk data registration, (2) precision correction of a reference subscene using GCP data, and (3) independently precision processed subscenes. Full scene rectification and registration results were evaluated by using a correlation technique to measure registration errors of 0.3 pixel rms thoughout the full scene. Resampling evaluations of nearest neighbor and TRW cubic convolution processed data included change detection imagery and feature classification. Resampled data were also evaluated for an MSS scene containing specular solar reflections.

Rifman, S. S.↗
NASA NTRSDate not supplied

Joint Polar Satellite System (JPSS)-3 VIIRS Prelaunch Geometric Calibration and Characterization Status

The NASA/NOAA Visible Infrared Imaging Radiometer Suite (VIIRS) is a key instrument in the JPSS missions (SNPP, JPSS-1-4). Being part of the calibration and validation process, JPSS-3 VIIRS prelaunch geometric performance assessment focuses on the sensor’s spatial response, band-to-band co-registration (BBR), and pointing knowledge. In general, JPSS-3 VIIRS’ prelaunch geometric performance is very good, and consistent with SNPP and JPSS-1-2 VIIRS sensors. This paper highlights some specific key findings from the JPSS-3 VIIRS’ prelaunch tests. We first show that with timing adjustments, JPSS-3 VIIRS scan BBR error between VisNIR and S/M/LWIR bands has been reduced from 0.12/0.03 M sampling intervals to 0.005/0.002 M sampling intervals, respectively. Focal Plane Assembly (FPA) rotations have been changed from 0.1 degree to 0.04 degree in VisVIR, from 0.18 degree to 0.09 degree in S/MWIR, and 0.16 degree to 0.08 degree in LWIR. Another finding from the prelaunch test is that JPSS-3 VIIRS has relatively large band-to-band co-registration errors between VisNIR and S/M/LWIR bands in the track direction. This BBR mis-registration increases when aft‐optics assembly (AOA) temperature decreases. The BBR mis-registration is about 0.10 M sampling intervals between VisNIR and S/MWIR bands, and 0.08 M sampling intervals between VisNIR and LWIR bands. By comparison, the track BBR offset in JPSS-2 is less than 0.02 M sampling intervals between VisNIR and S/M/LWIR bands. We also notice that the unsymmetrical Day Night Band (DNB) scan-direction Line Spread Function (LSF) of JPSS-2 VIIRS at different gain stages and aggregation modes have been corrected in J3 VIIRS.

VIIRS↗
DOE OSTI2026

Terrestrial laser scanning data (Levels 0 and 1) for Pasoh, Malaysia, Sep 2024

This data package contains data from terrestrial laser scanning (TLS) at the Pasoh Forest Reserve, Malaysia. The Pasoh Forest Reserve is a facility of the Forest Research Institute Malaysia, and contains evergreen lowland dipterocarp forest. The Next-Generation Ecosystem Experiments Tropics (NGEE-Tropics) study areas at Pasoh were established to study how different species respond to climatic variation and soil water availability. Two study areas were chosen representing different topography and species. The TLS data archived here were collected to provide detailed, three-dimensional information about forest structure. Specifically, data were collected to allow tree-level characterization of woody structure and leaf area for 12 focal trees with FloraPulse and sap flux sensors, facilitating estimation of woody biomass and leaf area to allow upscaling of water content and transpiration data to the tree-level. Scan positions were not selected to provide consistent data for non-focal trees with the study areas. This data package contains the following data: - High-level files document further details of the campaign and data package: 1_CampaignSummary.csv provides details about the campaign and study site, 2_ScanAreasDetail.csv provides details about each separate scan area (groups of scans post-processed into a single point cloud), 3_TerrestrialLidarSensor.csv provides further technical details about the Riegl VZ-400i TLS sensor, TLS_CSV_dd.csv is a CSV Data Dictionary providing information about the fields in CSV files following the ESS-DIVE CSV File Formatting Guidelines Reporting Format, TLS_flmd.csv is a File Level Metadata file providing information about each file in the data package following the ESS-DIVE File Level Metadata Reporting Format, and README.txt is a text file describing the overall project and file structure. - Level 0 data are the raw data (.PROJ folders) as recorded by the Riegl VZ-400i TLS instrument before scan co-registration and post-processing with the Riegl's proprietary RiSCAN PRO software, which requires a license. - Level 1 data contain post-processed, co-registered data from each scan area. The "PointClouds" folder for each scan area contains a .las file with 1 cm resolution point cloud data exported from RiSCAN PRO. These are the main files likely to be of interest to most users and can be further processed with any software capable of manipulating .las files (e.g. Python, R CloudCompare). The "Project Information" folder contains log files from post-processing in RiSCAN PRO that may be of interest to users who want to see detailed records of post-processing, including all PDF reports generated by RiSCAN PRO. The "ScanPositions" folder contains information about the final position of all TLS scans, after post-processing, in multiple formats. The file ScanPositions_*.csv provides final geo-referenced scan positions, and the file SOP_backup_*.csv can be used in RiSCAN PRO to restore the co-registered scan positions if users wish to re-process raw data (Level 0 .PROJ folders) with RiSCAN PRO software (e.g., subsample to a different resolution, exclude a certain scan position, or apply different filters on reflectance or deviation values) without redoing time-consuming co-registration steps.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Terrestrial laser scanning data (Levels 0 and 1) from Urban Biogeochemistry Pilot Project sites, Knoxville, Tennessee, Jul 2024 - Jul 2025

This data package contains data from terrestrial laser scanning (TLS) at five urban park sites in Knoxville, Tennessee, USA. All parks include open-grown and/or closed-canopy trees and mixed nearby land use. These study sites were established as part of the Urban Biogeochemistry Pilot Project, which has an overall goal of better understanding how hydrobiogeochemical cycling is altered within the human environment. These five sites represent a gradient of urbanization, and were instrumented to understand hydrological and biogeochemical cycling (e.g., soil moisture, soil physical properties and biogeochemistry, tree transpiration, species type). The TLS data archived here were collected to provide detailed, three-dimensional information about forest structure. Specifically, data were collected to allow tree- and stand-level characterization of woody structure and leaf area. TLS scans were placed to capture the area around trees with sap flow sensors, and as much of a 50 m radius area around the meteorological station as possible given site property limits. Derived products will allow upscaling of water content and transpiration data. This data package contains the following data: - High-level files document further details of the campaign and data package: 1_CampaignSummary.csv provides details about the campaign and study site, 2_ScanAreasDetail.csv provides details about each separate scan area (groups of scans post-processed into a single point cloud), 3_TerrestrialLidarSensor.csv provides further technical details about the Riegl VZ-400i TLS sensor, TLS_CSV_dd.csv is a CSV Data Dictionary providing information about the fields in CSV files following the ESS-DIVE CSV File Formatting Guidelines Reporting Format, TLS_flmd.csv is a File Level Metadata file providing information about each file in the data package following the ESS-DIVE File Level Metadata Reporting Format, and README.txt is a text file describing the overall project and file structure. - Level 0 data are the raw data (.PROJ folders) as recorded by the Riegl VZ-400i TLS instrument before scan co-registration and post-processing with the Riegl's proprietary RiSCAN PRO software, which requires a license. - Level 1 data contain post-processed, co-registered data from each scan area. The "PointClouds" folder for each scan area contains a .las file with 1 cm resolution point cloud data exported from RiSCAN PRO. These are the main files likely to be of interest to most users and can be further processed with any software capable of manipulating .las files (e.g. Python, R CloudCompare). The "Project Information" folder contains log files from post-processing in RiSCAN PRO that may be of interest to users who want to see detailed records of post-processing, including all PDF reports generated by RiSCAN PRO. The "ScanPositions" folder contains information about the final position of all TLS scans, after post-processing, in multiple formats. The file ScanPositions_*.csv provides final geo-referenced scan positions, and the file SOP_backup_*.csv can be used in RiSCAN PRO to restore the co-registered scan positions if users wish to re-process raw data (Level 0 .PROJ folders) with RiSCAN PRO software (e.g., subsample to a different resolution, exclude a certain scan position, or apply different filters on reflectance or deviation values) without redoing time-consuming co-registration steps.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Student Support for the “Frontiers in Attosecond & Ultrafast X-ray Science” School

The new millennium witnessed two revolutionary breakthroughs in ultrafast x-ray science: table-top XUV sources based on high harmonic generation in gases ushered in the attosecond era while facility-based x-ray free-electron lasers opened the path for intense, femtosecond hard x-rays. This award requested scholarship funds for a 2019 and 2023 School whose prime objective was the training of young scientists in these emerging complementary areas both relevant to DOE BES mission. The school entitled the “Frontiers of Attosecond and Ultrafast X-ray Science (FAXS)” (http://www.erice-attosecond.it/) was the second and fourth in a series, which began in 2017. The two Schools were held during March 10-16, 2019 and March 26-31, 2023 at the Ettore Majorana Foundation and Centre for Scientific Culture (http://www.ccsem.infn.it/) in Erice, Sicily. The DOE funds supported the registration fee for young scientists (graduate students and postdocs) from US institutions. The registration fees included School participation, lodging and meals over the duration of the School. Note, the third addition of the School was held in 2022 as a virtual event due to the pandemic, DOE funds were not necessary for this event. The FAXS School is a course of the 62th and 63rd International School of Quantum Electronics under the directorship of Prof. Diederik Wiersma (University of Florence). The Directors for the FAXS School are Louis DiMauro (The Ohio State University, USA) and Mauro Nisoli (Politecnico di Milano, Italy). The FAXS School program consisted of approximately 10 lectures by leading experts in attosecond and x-ray science (see attached list). Most lecturers delivered a series of three 1-hour lectures. The lecturers were required to spend the full 5 days at the school so to promote interaction with the students. The Erice Majorana Center venue accommodated ~75 young scientists. The registration fee covered the cost of participating in the school, lodging and meals for the entire duration of the school. The schedule consisted of lectures every morning and afternoon except for one afternoon that was reserved for an archaeological excursion. Every evening had a student/postdoc poster session and social gatherings at the Majorana Center to encourage further interaction of all participants and lecturers. The two FAXS Schools attracted an international group of young scientists. The DOE funds supported the registration fee for 11 students/postdocs from US institutions (5 supported in 2019 and 6 supported in 2023). The management of the DOE fellowships were administered through the Research Foundation of The Ohio State University. FAXS scholarships for European students/postdocs were provided by European funding sources administered by co-Director, Prof. Nisoli. All students/postdocs were encouraged to present a poster. Travel expenses to the FAXS School were the responsibility of the student/postdoc home institution.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1982

Spaceborne scanner imaging system errors

The individual sensor system design elements which are the priori components in the registration and rectification process, and the potential impact of error budgets on multitemporal registration and side-lap registration are analyzed. The properties of scanner, MLA, and SAR imaging systems are reviewed. Each sensor displays internal distortion properties which to varying degrees make it difficult to generate on orthophoto projection of the data acceptable for multiple pass registration or meeting national map accuracy standards and is also affected to varying degrees by relief displacements in moderate to hilly terrain. Nonsensor related distortions, associated with the accuracy of ephemeris determination and platform stability, have a major impact on local geometric distortions. Platform stability improvements expected from the new multi mission spacecraft series and improved ephemeris and ground control point determination from the NAVSTAR/global positioning satellite systems are reviewed.

Prakash, A.↗
NASA NTRS1982

Geometric verification

Present LANDSAT data formats are reviewed to clarify how the geodetic location and registration capabilities were defined for P-tape products and RBV data. Since there is only one geometric model used in the master data processor, geometric location accuracy of P-tape products depends on the absolute accuracy of the model and registration accuracy is determined by the stability of the model. Due primarily to inaccuracies in data provided by the LANDSAT attitude management system, desired accuracies are obtained only by using ground control points and a correlation process. The verification of system performance with regards to geodetic location requires the capability to determine pixel positions of map points in a P-tape array. Verification of registration performance requires the capability to determine pixel positions of common points (not necessarily map points) in 2 or more P-tape arrays for a given world reference system scene. Techniques for registration verification can be more varied and automated since map data are not required. The verification of LACIE extractions is used as an example.

Grebowsky, G. J.↗
NASA NTRS1984

LANDSAT-4 MSS Geometric Correction: Methods and Results

An automated image registration system such as that developed for LANDSAT-4 can produce all of the information needed to verify and calibrate the software and to evaluate system performance. The on-line MSS archive generation process which upgrades systematic correction data to geodetic correction data is described as well as the control point library build subsystem which generates control point chips and support data for on-line upgrade of correction data. The system performance was evaluated for both temporal and geodetic registration. For temporal registration, 90% errors were computed to be .36 IFOV (instantaneous field of view) = 82.7 meters) cross track, and .29 IFOV along track. Also, for actual production runs monitored, the 90% errors were .29 IFOV cross track and .25 IFOV along track. The system specification is .3 IFOV, 90% of the time, both cross and along track. For geodetic registration performance, the model bias was measured by designating control points in the geodetically corrected imagery.

Brooks, J.↗
NASA NTRS1985

Measurement of Thematic Mapper data quality

Thematic Mapper data from Landsat-4 and Landsat-5 were examined for band-to-band registration, absolute geodetic registration, periodic noise and spatial resolution. Between focal planes, appreciable misregistrations existed in early data products but were corrected in later data products. The analysis of absolute geodetic registration used only system-corrected data because ground control point-corrected data were unavailable. Geodetic registration errors averaged only 9.7 pixels, less than expected for system-corrected data. Periodic noise at four spatial frequencies was observed in Landsat-5 Thematic Mapper data by using Fourier analysis on small areas over water. Magnitudes of periodic noise components were consistent within a scene. The modulation transfer function was determined for two Landsat-4 scenes. The effective instantaneous field of view was 40.8 meters in one case, and 48.6 meters in the other.

Wrigley, R. C.↗
NASA NTRS1985

Analysis and correction of Landsat 4 and 5 Thematic Mapper Sensor Data

Procedures for the correction and registration and registration of Landsat TM image data are examined. The registration of Landsat-4 TM images of San Francisco to Landsat-5 TM images of the San Francisco using the interactive geometric correction program and the cross-correlation technique is described. The geometric correction program and cross-correlation results are presented. The corrections of the TM data to a map reference and to a cartographic database are discussed; geometric and cartographic analyses are applied to the registration results.

Bernstein, R.↗
NASA NTRS1992

New approaches in interferometric SAR data processing

It is well established that interferometric synthetic aperture radar (SAR) images can be inverted to perform surface elevation mapping. Among the factors critical to the mapping accuracy are registration of the interfering SAR images and phase unwrapping. A novel registration algorithm is presented that determines the registration parameters through optimization. A new figure of merit is proposed that evaluates the registration result during the optimization. The phase unwrapping problem is approached through a new method involving fringe line detection. The algorithms are tested with two SEASAT SAR images of terrain near Yellowstone National Park. These images were collected on Seasat orbits 1334 and 1420, which were very close together in space, i.e., less than 100 m. The resultant elevation map is compared with the USGS digital terrain elevation model.

Lin, Qian↗
NASA NTRS1992

Registering and resampling images in STSDAS

Registering different images can be difficult, especially if the images to be registered are images at different wavelengths, where features in one image may look entirely different or be absent from the second image. Using two new packages soon to be added to the STSDAS package, REGISTER and RESAMPLE, this job is done automatically. The REGISTER package allows the user to determine the amount of translation, rotation, and/or magnification needed to make two images, spectra, or time series congruent. The methods implemented to compute the registration parameters use: a set of the pixel coordinates of the same features identified in two files, or the FITS coordinate transformation parameters in the headers of two data files, or a single feature identified as the peak of a cross-correlation between two vectors. The coefficients describing the registration are defined by the equations (for a two-dimensional image): x = a + bx + cy, y = d + ex + fy, where (X,Y) are the pixel coordinates of a feature in the reference image, (x,y) are the pixel coordinates of a feature in the secondary image, and the computed coefficients are a, b, c, d, e, and f. Results may be produced by linking the output of REGISTER to RESAMPLE in a command language procedure. The output from REGISTER and the input to RESAMPLE consists of a matrix of coefficients (a through f above) fully specifying the registration. The RESAMPLE package resamples simple vector or image data for a given amount of translation, rotation (images only), and magnification, or reflection of the science data. Specific options included are: image rotation about the FITS reference pixel; scale changes, i.e. magnification or demagnification (for images, independently on both axes); simple translation; reflection (for images, about one or both axes); and resampling and registration to a reference data set. Output from the RESAMPLE task is the resampled image which may then be displayed and compared with the reference image.

Williamson, R. L., II↗