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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.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS1979

Onboard image processing

The possibility of onboard geometric correction of Thematic Mapper type imagery to make possible image registration is considered. Typically, image registration is performed by processing raw image data on the ground. The geometric distortion (e.g., due to variation in spacecraft location and viewing angle) is estimated by using a Kalman filter updated by correlating the received data with a small reference subimage, which has known location. Onboard image processing dictates minimizing the complexity of the distortion estimation while offering the advantages of a real time environment. In keeping with this, the distortion estimation can be replaced by information obtained from the Global Positioning System and from advanced star trackers. Although not as accurate as the conventional ground control point technique, this approach is capable of achieving subpixel registration. Appropriate attitude commands can be used in conjunction with image processing to achieve exact overlap of image frames. The magnitude of the various distortion contributions, the accuracy with which they can be measured in real time, and approaches to onboard correction are investigated.

Martin, D. R.↗
DOE OSTI2026

CHESS 2025: Orthorectified airborne RGB imagery from NEON AOP surveys

This dataset provides Level 1 (L1) and Level 3 (L3) orthorectified Red-Green-Blue (RGB) imagery collected for the 2025 Colorado Headwaters Ecological Spectroscopy Study (CHESS). This high-resolution imagery is a photographic record of red, green, and blue visible light from sunlight reflected off of the Earth’s surface. The data comprise full-color images of the ground surface and are primarily intended to provide context to imaging spectroscopy and light detection and ranging (LiDAR) data. The data were acquired over three study domains in the Upper Gunnison river basin: the upper East River watershed (CRBU); Almont Triangle and Taylor Canyon (ALMO); and Upper Taylor River watershed (UPTA) between 2025-06-13 and 2025-07-15. RGB images were acquired using the PhaseOne IXM-RS150F high-resolution digital camera onboard the National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP). The package data include both an L1 product comprising one camera frame per file and an L3 mosaic aligned to the Universal Transverse Mercator (UTM) Zone 13N grid and the World Geodetic System (WGS) 84 projection. Both products are provided in geotif (.tif) format at 0.1 m ground resolution. The bulk of the imagery was collected during the main CHESS field campaign from June 13 to July 15, 2025. Additional images of a portion of the Upper Taylor (UPTA) domain were collected on September 18, 2025, to fill gaps in imagery identified after the main campaign was complete. RGB camera imagery is not radiometrically calibrated, and therefore pixel values should not be exploited for scientific analysis. Pixel values have undergone a manual adjustment to enhance feature identification. The imagery is rigorously geolocated which does allow for reliable geometric information to be retrieved. To generate the orthorectified imagery, the NEON AOP camera captured visible spectrum in red, green, and blue bands. The raw images were then processed using NEON’s camera orthorectification workflow. A boresight calibration flight was made to build a complete camera, distortion, and alignment model. Color balance/white balance and exposure correction were applied to the raw RGB images. The corrected images were orthorectified by ray-tracing image pixels to a lidar-derived digital surface model (DSM) mesh using the refined camera model, outputting orthorectified raster pixels on a regular grid. Flightline-level data were mosaicked by selecting per-pixel contributions from overlapping orthorectified images using line-of-sight (LOS) zenith angle minimization to reduce edge distortions. CHESS Project Description: The Colorado Headwaters Ecological Spectroscopy Study (CHESS) comprised a multi-week airborne remote sensing and field observation campaign in the Upper Gunnison Basin, Colorado, conducted in June and July of 2025. Airborne remote sensing was conducted by the National Ecological Observatory Network Airborne Observation Platform (NEON AOP), concurrent with a field campaign run by the Rocky Mountain Biological Laboratory (RMBL), the Lawrence Berkeley National Laboratory (LBNL) and SLAC National Accelerator Laboratory Watershed Function Science Focus Area (SFA), and NASA-JPL (Jet Propulsion Laboratory) Earth Surface Mineral Dust Source Investigation (EMIT) program. Between June 10 and July 18, 2025, the NEON AOP flight team collected high-resolution aerial imaging spectroscopy and Light Detection and Ranging (LiDAR) data over three domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). In coordination with the flights, a field campaign acquired ground-truth observations, including observations of vegetation composition, foliar traits, forest demography, and subsurface properties in 18 core sampling areas within the domains. Additional surface water observations were taken at over 380 point locations. All CHESS campaign datasets can be found within the CHESS ESS-DIVE data portal: https://data.ess-dive.lbl.gov/portals/chess. Funding Acknowledgement: Field and remote-sensing data acquisition was performed under a grant from the National Aeronautics and Space Administration (80NSSC24K1005). This work was also supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

2018 NEON and 2025 CHESS Campaigns↗
NASA NTRS1988

System Turns SAR Images Into Maps

Postprocessing system for synthetic-aperture radar (SAR) transforms raw images from natural rotated and distorted SAR reference frame into geocoded images. Images automatically corrected to remove slant-range nonlinearities and Doppler skew. Produces multiple-frame mosaics for large-scale mapping. Does not require tedious manual registration of representative "tie" points in raw SAR imagery with known locations on Earth.

Curlander, J. C.↗
NASA NTRS1997

International Ultraviolet Explorer Final Archive

CSC processed IUE images through the Final Archive Data Processing System. Raw images were obtained from both NDADS and the IUEGTC optical disk platters for processing on the Alpha cluster, and from the IUEGTC optical disk platters for DECstation processing. Input parameters were obtained from the IUE database. Backup tapes of data to send to VILSPA were routinely made on the Alpha cluster. IPC handled more than 263 requests for priority NEWSIPS processing during the contract. Staff members also answered various questions and requests for information and sent copies of IUE documents to requesters. CSC implemented new processing capabilities into the NEWSIPS processing systems as they became available. In addition, steps were taken to improve efficiency and throughput whenever possible. The node TORTE was reconfigured as the I/O server for Alpha processing in May. The number of Alpha nodes used for the NEWSIPS processing queue was increased to a maximum of six in measured fashion in order to understand the dependence of throughput on the number of nodes and to be able to recognize when a point of diminishing returns was reached. With Project approval, generation of the VD FITS files was dropped in July. This action not only saved processing time but, even more significantly, also reduced the archive storage media requirements, and the time required to perform the archiving, drastically. The throughput of images verified through CDIVS and processed through NEWSIPS for the contract period is summarized below. The number of images of a given dispersion type and camera that were processed in any given month reflects several factors, including the availability of the required NEWSIPS software system, the availability of the corresponding required calibrations (e.g., the LWR high-dispersion ripple correction and absolute calibration), and the occurrence of reprocessing efforts such as that conducted to incorporate the updated SWP sensitivity-degradation correction in May.

Source record↗
NASA NTRS2021

The Dark Side of Pluto

During its departure from Pluto, New Horizons used its LORRI camera to image a portion of Pluto's southern hemisphere that was in a decades-long seasonal winter darkness, but still very faintly illuminated by sunlight reflected by Charon. Recovery of this faint signal was technically challenging. The bright ring of sunlight forward-scattered by haze in the Plutonian atmosphere encircling the nightside hemisphere was severely overexposed, defeating the standard smeared-charge removal required for LORRI images. Reconstruction of the overexposed portions of the raw images, however, allowed adequate corrections to be accomplished. The small solar elongation of Pluto during the departure phase also generated a complex scattered-sunlight background in the images that was three orders of magnitude stronger than the estimated Charon-light flux (the Charon-light flux is similar to the flux of moonlight on Earth a few days before first quarter). A model background image was constructed for each Pluto image based on principal component analysis applied to an ensemble of scattered-sunlight images taken at identical Sun−spacecraft geometry to the Pluto images. The recovered Charon-light image revealed a high-albedo region in the southern hemisphere. We argue that this may be a regional deposit of N2 or CH4 ice. The Charon-light image also shows that the south polar region currently has markedly lower albedo than the north polar region of Pluto, which may reflect the sublimation of N2 ice or the deposition of haze particulates during the recent southern summer.

Pluto↗
NASA NTRS1987

Mining the IUE archive

The IUE archives are described as well as their applications and possible future developments. The data for each image is archived as a set usually containing a raw image, a processed image, and one or more extracted spectra. A cumulative plot of the number of images which have been retrieved from the IUE archives is provided, indicating that interest in the data continues to grow in all of the astronomical communities served.

Giaretta, David↗
NASA NTRS1994

A VLSI Processor Design of Real-Time Data Compression for High-Resolution Imaging Radar

For the high-resolution imaging radar systems, real-time data compression of raw imaging data is required to accomplish the science requirements and satisfy the given communication and storage constraints. The Block Adaptive Quantizer (BAQ) algorithm and its associated VLSI processor design have been developed to provide a real-time data compressor for high-resolution imaging radar systems.

data compression VLSI processor design imaging rad↗
NASA NTRS1985

Planetary image conversion task

The Planetary Image Conversion Task group processed 12,500 magnetic tapes containing raw imaging data from JPL planetary missions and produced an image data base in consistent format on 1200 fully packed 6250-bpi tapes. The output tapes will remain at JPL. A copy of the entire tape set was delivered to US Geological Survey, Flagstaff, Ariz. A secondary task converted computer datalogs, which had been stored in project specific MARK IV File Management System data types and structures, to flat-file, text format that is processable on any modern computer system. The conversion processing took place at JPL's Image Processing Laboratory on an IBM 370-158 with existing software modified slightly to meet the needs of the conversion task. More than 99% of the original digital image data was successfully recovered by the conversion task. However, processing data tapes recorded before 1975 was destructive. This discovery is of critical importance to facilities responsible for maintaining digital archives since normal periodic random sampling techniques would be unlikely to detect this phenomenon, and entire data sets could be wiped out in the act of generating seemingly positive sampling results. Reccomended follow-on activities are also included.

Martin, M. D.↗
DOE OSTI2024

Self-calibration strategies for reducing systematic slope measurement errors of autocollimators in deflectometric profilometry

Deflectometric profilometers are used to precisely measure the form of beam shaping optics of synchrotrons and X-ray free-electron lasers. They often utilize autocollimators which measure slope by evaluating the displacement of a reticle image on a detector. Based on our privileged access to the raw image data of an autocollimator, novel strategies to reduce the systematic measurement errors by using a set of overlapping images of the reticle obtained at different positions on the detector are discussed. It is demonstrated that imaging properties such as, for example, geometrical distortions and vignetting, can be extracted from this redundant set of images without recourse to external calibration facilities. This approach is based on the fact that the properties of the reticle itself do not change – all changes in the reticle image are due to the imaging process. Firstly, by combining interpolation and correlation, it is possible to determine the shift of a reticle image relative to a reference image with minimal error propagation. Secondly, the intensity of the reticle image is analysed as a function of its position on the CCD and a vignetting correction is calculated. Thirdly, the size of the reticle image is analysed as a function of its position and an imaging distortion correction is derived. It is demonstrated that, for different measurement ranges and aperture diameters of the autocollimator, reductions in the systematic errors of up to a factor of four to five can be achieved without recourse to external measurements.

47 OTHER INSTRUMENTATION↗
NASA NTRS1992

Image segmentation using fuzzy LVQ clustering networks

In this note we formulate image segmentation as a clustering problem. Feature vectors extracted from a raw image are clustered into subregions, thereby segmenting the image. A fuzzy generalization of a Kohonen learning vector quantization (LVQ) which integrates the Fuzzy c-Means (FCM) model with the learning rate and updating strategies of the LVQ is used for this task. This network, which segments images in an unsupervised manner, is thus related to the FCM optimization problem. Numerical examples on photographic and magnetic resonance images are given to illustrate this approach to image segmentation.

Tsao, Eric Chen-Kuo↗
NASA NTRS1998

A Photo Album of Earth Scheduling Landsat 7 Mission Daily Activities

Landsat7 is a member of a new generation of Earth observation satellites. Landsat7 will carry on the mission of the aging Landsat 5 spacecraft by acquiring high resolution, multi-spectral images of the Earth surface for strategic, environmental, commercial, agricultural and civil analysis and research. One of the primary mission goals of Landsat7 is to accumulate and seasonally refresh an archive of global images with full coverage of Earth's landmass, less the central portion of Antarctica. This archive will enable further research into seasonal, annual and long-range trending analysis in such diverse research areas as crop yields, deforestation, population growth, and pollution control, to name just a few. A secondary goal of Landsat7 is to fulfill imaging requests from our international partners in the mission. Landsat7 will transmit raw image data from the spacecraft to 25 ground stations in 20 subscribing countries. Whereas earlier Landsat missions were scheduled manually (as are the majority of current low-orbit satellite missions), the task of manually planning and scheduling Landsat7 mission activities would be overwhelmingly complex when considering the large volume of image requests, the limited resources available, spacecraft instrument limitations, and the limited ground image processing capacity, not to mention avoidance of foul weather systems. The Landsat7 Mission Operation Center (MOC) includes an image scheduler subsystem that is designed to automate the majority of mission planning and scheduling, including selection of the images to be acquired, managing the recording and playback of the images by the spacecraft, scheduling ground station contacts for downlink of images, and generating the spacecraft commands for controlling the imager, recorder, transmitters and antennas. The image scheduler subsystem autonomously generates 90% of the spacecraft commanding with minimal manual intervention. The image scheduler produces a conflict-free schedule for acquiring images of the "best" 250 scenes daily for refreshing the global archive. It then equitably distributes the remaining resources for acquiring up to 430 scenes to satisfy requests by international subscribers. The image scheduler selects candidate scenes based on priority and age of the requests, and predicted cloud cover and sun angle at each scene. It also selects these scenes to avoid instrument constraint violations and maximizes efficiency of resource usage by encouraging acquisition of scenes in clusters. Of particular interest to the mission planners, it produces the resulting schedule in a reasonable time, typically within 15 minutes.

Potter, William↗
NASA NTRS2005

Operation and Performance of the Mars Exploration Rover Imaging System on the Martian Surface

This slide presentation details the Mars Exploration Rover (MER) imaging system. Over 144,000 images have been gathered from all Mars Missions, with 83.5% of them being gathered by MER. Each Rover has 9 cameras (Navcam, front and rear Hazcam, Pancam, Microscopic Image, Descent Camera, Engineering Camera, Science Camera) and produces 1024 x 1024 (1 Megapixel) images in the same format. All onboard image processing code is implemented in flight software and includes extensive processing capabilities such as autoexposure, flat field correction, image orientation, thumbnail generation, subframing, and image compression. Ground image processing is done at the Jet Propulsion Laboratory's Multimission Image Processing Laboratory using Video Image Communication and Retrieval (VICAR) while stereo processing (left/right pairs) is provided for raw image, radiometric correction; solar energy maps,triangulation (Cartesian 3-spaces) and slope maps.

imaging↗
NASA NTRS1979

Low-level processing for real-time image analysis

A system that detects object outlines in television images in real time is described. A high-speed pipeline processor transforms the raw image into an edge map and a microprocessor, which is integrated into the system, clusters the edges, and represents them as chain codes. Image statistics, useful for higher level tasks such as pattern recognition, are computed by the microprocessor. Peak intensity and peak gradient values are extracted within a programmable window and are used for iris and focus control. The algorithms implemented in hardware and the pipeline processor architecture are described. The strategy for partitioning functions in the pipeline was chosen to make the implementation modular. The microprocessor interface allows flexible and adaptive control of the feature extraction process. The software algorithms for clustering edge segments, creating chain codes, and computing image statistics are also discussed. A strategy for real time image analysis that uses this system is given.

Eskenazi, R.↗
NASA NTRS1991

CD-ROM publication of the Mars digital cartographic data base

The recently completed Mars mosaicked digital image model (MDIM) and the soon-to-be-completed Mars digital terrain model (DTM) are being transcribed to optical disks to simplify distribution to planetary investigators. These models, completed in FY 1991, provide a cartographic base to which all existing Mars data can be registered. The digital image map of Mars is a cartographic extension of a set of compact disk read-only memory (CD-ROM) volumes containing individual Viking Orbiter images now being released. The data in these volumes are pristine in the sense that they were processed only to the extent required to view them as images. They contain the artifacts and the radiometric, geometric, and photometric characteristics of the raw data transmitted by the spacecraft. This new set of volumes, on the other hand, contains cartographic compilations made by processing the raw images to reduce radiometric and geometric distortions and to form geodetically controlled MDIM's. It also contains digitized versions of an airbrushed map of Mars as well as a listing of all feature names approved by the International Astronomical Union. In addition, special geodetic and photogrammetric processing has been performed to derive rasters of topographic data, or DTM's. The latter have a format similar to that of MDIM, except that elevation values are used in the array instead of image brightness values. The set consists of seven volumes: (1) Vastitas Borealis Region of Mars; (2) Xanthe Terra of Mars; (3) Amazonis Planitia Region of Mars; (4) Elysium Planitia Region of Mars; (5) Arabia Terra of Mars; (6) Planum Australe Region of Mars; and (7) a digital topographic map of Mars.

Batson, R. M.↗
NASA NTRS2013

Synthetic Foveal Imaging Technology

Apparatuses and methods are disclosed that create a synthetic fovea in order to identify and highlight interesting portions of an image for further processing and rapid response. Synthetic foveal imaging implements a parallel processing architecture that uses reprogrammable logic to implement embedded, distributed, real-time foveal image processing from different sensor types while simultaneously allowing for lossless storage and retrieval of raw image data. Real-time, distributed, adaptive processing of multi-tap image sensors with coordinated processing hardware used for each output tap is enabled. In mosaic focal planes, a parallel-processing network can be implemented that treats the mosaic focal plane as a single ensemble rather than a set of isolated sensors. Various applications are enabled for imaging and robotic vision where processing and responding to enormous amounts of data quickly and efficiently is important.

Monacos, Steve P.↗
NASA NTRS1994

Camera artifacts in IUE spectra

This study of emission line mimicking features in the IUE cameras has produced an atlas of artifiacts in high-dispersion images with an accompanying table of prominent artifacts and a table of prominent artifacts in the raw images along with a medium image of the sky background for each IUE camera.

Bruegman, O. W.↗
DOE OSTI2023

Application of unsupervised deep learning to image segmentation and in-situ contact angle measurements in a CO 2 -water-rock system

Rock surface wettability is a critical property that regulates multiphase flows in porous media, which can be quantified using the surface contact angle (CA). X-ray micro-computed tomography (μCT) provides an effective approach to in-situ measurements of surface CAs. However, the CA measurement accuracy depends significantly on the quality of CT image segmentation, which is the clustering of CT pixels into separate phases. Inspired by this, we developed a deep learning (DL)-based CA measurement workflow. Motivated by the recent tremendous progress in unsupervised learning techniques and aiming to avoid expensive manual data annotations, an unsupervised DL pipeline for CT image segmentation was proposed and implemented, which includes unsupervised model training and post-processing. The unsupervised model training was driven by a novel loss function constrained with feature similarity and spatial continuity and implemented by iterative forward and backward paths; the former clustered the pixel-wise feature vectors extracted by convolution neural networks, whereas the latter updated the parameters using gradient descent. An over-segmentation strategy was adopted for model training. The post-processing steps based on agglomerative hierarchical clustering (AHC) were implemented to further merge the over-segmented model output to the desired cluster number, which is intended to improve the efficiency of image segmentation. The developed unsupervised DL pipeline was compared with other commonly-used image segmentation methods using pixel-wise and physics-based evaluation metrics on a synthetic raw-image dataset, which had a known ground truth. The unsupervised DL pipeline showed the best performance. Next, the segmented images were input to an automatic CA measurement tool, and the results were validated by comparisons with manual measurements. The CA values from the manual and automatic measurements showed similar distributions and statistical properties. The automatic measurement demonstrated a wider spectrum because of the much larger number of measurement data points. The primary novelty of the unsupervised DL pipeline developed in this study lies in the novel loss function and the over-segmentation strategy associated with AHC post-processing. Finally, the workflow has been proven an efficient tool for pore-scale wettability characterization, which has a wide range of applications in fundamental studies of multiphase flows in natural porous media, which have critical implications to geological carbon sequestration, hydrocarbon energy recovery, and contaminant transport in groundwater.

42 ENGINEERING↗
NASA NTRS1995

Image Registration: A Necessary Evil

Registration of test and reference images is a key component of nearly all PSP data reduction techniques. This is done to ensure that a test image pixel viewing a particular point on the model is ratioed by the reference image pixel which views the same point. Typically registration is needed to account for model motion due to differing airloads when the wind-off and wind-on images are taken. Registration is also necessary when two cameras are used for simultaneous acquisition of data from a dual-frequency paint. This presentation will discuss the advantages and disadvantages of several different image registration techniques. In order to do so, it is necessary to propose both an accuracy requirement for image registration and a means for measuring the accuracy of a particular technique. High contrast regions in the unregistered images are most sensitive to registration errors, and it is proposed that these regions be used to establish the error limits for registration. Once this is done, the actual registration error can be determined by locating corresponding points on the test and reference images, and determining how well a particular registration technique matches them. An example of this procedure is shown for three transforms used to register images of a semispan model. Thirty control points were located on the model. A subset of the points were used to determine the coefficients of each registration transform, and the error with which each transform aligned the remaining points was determined. The results indicate the general superiority of a third-order polynomial over other candidate transforms, as well as showing how registration accuracy varies with number of control points. Finally, it is proposed that image registration may eventually be done away with completely. As more accurate image resection techniques and more detailed model surface grids become available, it will be possible to map raw image data onto the model surface accurately. Intensity ratio data can then be obtained by a "model surface ratio," rather than an image ratio. The problems and advantages of this technique will be discussed.

Bell, James↗