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NASA NTRS1995

Software For Tie-Point Registration Of SAR Data

SAR-REG software package registers synthetic-aperture-radar (SAR) image data to common reference frame based on manual tie-pointing. Image data can be in binary, integer, floating-point, or AIRSAR compressed format. For example, with map of soil characteristics, vegetation map, digital elevation map, or SPOT multispectral image, as long as user can generate binary image to be used by tie-pointing routine and data are available in one of the previously mentioned formats. Written in FORTRAN 77.

Rignot, Eric↗

NASA NTRS2021

Spatial Registration Assessments for the SNPP and N20 VIIRS Reflective Solar Bands Using Unscheduled Lunar Observations

The Visible Infrared Imaging Radiometer Suite (VIIRS) is a multi-spectral Earth-observing instrument on board the Suomi-NPP (SNPP) and NOAA-20 (N20) spacecraft, with spectral bands ranging in wavelength from 0.41 to 12.2 μm. For the reflective solar bands (RSB), the bands are calibrated on orbit using both solar diffuser (SD) and lunar observations. The lunar observations use near-monthly scheduled spacecraft maneuvers in order to view the Moon within a desired phase angle range. While the primary purpose of the maneuvers is for radiometric calibration, these observations can also be used to characterize the spatial performance of the instrument, including the band-to-band and detector-to-detector registration (BBR/DDR). The Moon can also be observed without spacecraft maneuvers. However, these observations are over a larger phase angle range. While the geometry of these unscheduled observations is more varied, they can still be used to assess the sensor performance. In this work, we will use unscheduled Moon data to analyze the BBR and DDR of the SNPP and N20 VIIRS RSB. For the BBR, we implemented an image cross-correlation approach, which removes the residual oscillations in the trending data when compared to previous methodologies. For the DDR, we developed an edge fitting approach that accounts for the lunar motion across the VIIRS focal plane array on a scan-by-scan basis using lunar and satellite ephemeris data. In our analysis, we find that the BBR and DDR for both VIIRS RSB are stable on orbit.

Band-to-band registration (BBR)↗

NASA NTRS1997

A scale space feature based registration technique for fusion of satellite imagery

Feature based registration is one of the most reliable methods to register multi-sensor images (both active and passive imagery) since features are often more reliable than intensity or radiometric values. The only situation where a feature based approach will fail is when the scene is completely homogenous or densely textural in which case a combination of feature and intensity based methods may yield better results. In this paper, we present some preliminary results of testing our scale space feature based registration technique, a modified version of feature based method developed earlier for classification of multi-sensor imagery. The proposed approach removes the sensitivity in parameter selection experienced in the earlier version as explained later.

Raghavan, Srini↗

NASA NTRS1997

Registration assisted mosaic generation

This paper presents a general strategy for assembling mosaics from numerous individual images where uncertainty exists in the position and orientation of those images. Both of the presented applications relate to remotely operated camera platforms, the first being the Galileo solid state imaging (SSI) camera presently in orbit around Jupiter, and the second being the Imager for Mars Pathfinder (IMP) stereo camera on Mars. A basic strategy in both applications is to determine the correct relative camera pointing followed by direct map projection of the images. It is assumed that approximate camera pointing exists sufficient to locate adjacent images and to place initial tiepoints within reach of the correlator. Spatial correlation is used to fix tiepoints whose initial locations are predicted by the camera pointing. We use either an fast fourier transform (fft) algorithm or a variant of Gruen's scheme permitting limited image rotation and skew. The Gruen correlator has three hierarchical modes: 1) A classical spatial least squares correlation on integral pixel boundaries used when rotation is small. 2) An annealing non-deterministic search used when rotations are unknown. A simplex deterministic search used for the end game. The correlation operation can be performed either interactively or autonomously. The final camera pointing solution relies upon a simplex downhill search in 2n or 3n dimensions where n is the number of images comprising the mosaic and the objective function to be minimized is the disagreement between tiepoint locations predicted from the camera pointing with those observed by the correlator. For Galileo the 3n unknowns are euler angles defining camera pointing in planet coordinates, and for Mars Pathfinder they are 2n unknowns representing commanded azimuth and elevation in the Lander coordinate system.

Lorre, Jean J.↗

NASA NTRS1986

Performance of the SIR-B digital image processing subsystem

A ground-based system to generate digital SAR image products has been developed and implemented in support of the SIR-B mission. This system is designed to achieve the maximum throughput while meeting strict image fidelity criteria. Its capabilities include: automated radiometric and geometric correction of the output imagery; high-precision absolute location without tiepoint registration; filtering of the raw data to remove spurious signals from alien radars; and automated catologing to maintain a full set of radar and image production facility in support of the SIR-B science investigators routinely produces over 80 image frames per week.

Curlander, J. C.↗

NASA NTRS1973

Digital processing of radiographic images

Some techniques are presented and the software documentation for the digital enhancement of radiographs. Both image handling and image processing operations are considered. The image handling operations dealt with are: (1) conversion of format of data from packed to unpacked and vice versa; (2) automatic extraction of image data arrays; (3) transposition and 90 deg rotations of large data arrays; (4) translation of data arrays for registration; and (5) reduction of the dimensions of data arrays by integral factors. Both the frequency and the spatial domain approaches are presented for the design and implementation of the image processing operation. It is shown that spatial domain recursive implementation of filters is much faster than nonrecursive implementations using fast fourier transforms (FFT) for the cases of interest in this work. The recursive implementation of a class of matched filters for enhancing image signal to noise ratio is described. Test patterns are used to illustrate the filtering operations. The application of the techniques to radiographic images of metallic structures is demonstrated through several examples.

Bond, A. D.↗

NASA NTRS1984

Investigation of TM Band-to-band Registration Using the JSC Registration Processor

The JSC registration processor performs scene-to-scene (or band-to-band) correlation based on edge images. The edge images are derived from a percentage of the edge pixels calculated from the raw scene data, excluding clouds and other extraneous data in the scene. Correlations are performed on patches (blocks) of the edge images, and the correlation peak location in each patch is estimated iteratively to fractional pixel location accuracy. Peak offset locations from all patches over the scene are then considered together, and a variety of tests are made to weed out outliers and other inconsistencies before a distortion model is assumed. Thus, the correlation peak offset locations in each patch indicate quantitatively how well the two TM bands register to each other over that patch of scene data. The average of these offsets indicate the overall accuracies of the band-to-band registration. The registration processor was also used to register one acquisition to another acquisition of multitemporal TM data acquired over the same ground track. Band 4 images from both acquisitions were correlated and an rms error of a fraction of a pixel was routinely obtained.

Yao, S. S.↗

NASA NTRS1997

Efficient algorithms for robust feature matching

One of the basic building blocks in any point-based registration scheme involves matching feature points that are extracted from the sensed image to their counterparts in the reference image. This leads to the fundamental problem of point matching: given two sets of points, find the affine transformation that transforms one point set so that its distance from the other point set is minimized. Because of measurement errors and the presence of outlying data points, it is important that the distance measure between two point sets be robust to these effects. We measure distances using the generalized Hausdorff distance. Point matching can be a computationally intensive task, and there have been a number of algorithms and approaches proposed for solving this problem both theoretical and applied. We present two approaches to the point matching problem, in an attempt to reduce the computational complexity of the problem, while still providing guarantees on the quality of the final match. Our first method is an approximation algorithm, which is loosely based on a branch-and-bound approach due to Huttenlocher and Rucklidge. We show that by varying the approximation error bounds, it is possible to achieve a tradeoff between the quality of the match and the running time of the algorithm. Our second method involves a Monte Carlo method for accelerating the search process used in the first algorithm. With high probability this method succeeds in finding an approximately optimal match. We establish the efficiency of our approaches empirically.

Mount, David M.↗

DOE OSTI2022

Gantryless Associated-Particle Neutron Radiography

The present work reports on the development of techniques for in-field fast-neutron radiography measurements using the associated-particle imaging (API) method. The API method employs alpha-neutron coincidences from the d+t→α+n reaction to enable fast neutron transmission imaging with excellent contrast using a wide cone beam. However, for field radiography applications, the API method is burdened by the need for the relative positions of the source and detector to be known. Fortunately, these relative positions can be inferred from transmission data. The inferred positions also enable accurate stitching of multiple images into a composite image even when using a low-resolution detector panel and acquiring images having few overlapping pixels. The developed techniques address analysis of measurements where (1) the source and detector panel are separately hand positioned rather than held in registration by a gantry, (2) multiple detector panel positions within the “coincident cone” of tagged neutrons are required to piece together an image of an item of interest, and (3) normalization measurements that have identical source-detector positioning but without the inspected object are not possible. The present work will describe the system calibrations (including timing calibrations and neutron direction calibrations) necessary for subsequent analyses, the method of locating the detector in the coincident cone of neutrons with millimeter precision using the timing and directions of coincident neutrons, the method of calculating a normalization image for a given detector panel position, and the method used to project multiple images into a common image.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS2013

Co-registration of Laser Altimeter Tracks with Digital Terrain Models and Applications in Planetary Science

We have derived algorithms and techniques to precisely co-register laser altimeter profiles with gridded Digital Terrain Models (DTMs), typically derived from stereo images. The algorithm consists of an initial grid search followed by a least-squares matching and yields the translation parameters at sub-pixel level needed to align the DTM and the laser profiles in 3D space. This software tool was primarily developed and tested for co-registration of laser profiles from the Lunar Orbiter Laser Altimeter (LOLA) with DTMs derived from the Lunar Reconnaissance Orbiter (LRO) Narrow Angle Camera (NAC) stereo images. Data sets can be co-registered with positional accuracy between 0.13 m and several meters depending on the pixel resolution and amount of laser shots, where rough surfaces typically result in more accurate co-registrations. Residual heights of the data sets are as small as 0.18 m. The software can be used to identify instrument misalignment, orbit errors, pointing jitter, or problems associated with reference frames being used. Also, assessments of DTM effective resolutions can be obtained. From the correct position between the two data sets, comparisons of surface morphology and roughness can be made at laser footprint- or DTM pixel-level. The precise co-registration allows us to carry out joint analysis of the data sets and ultimately to derive merged high-quality data products. Examples of matching other planetary data sets, like LOLA with LRO Wide Angle Camera (WAC) DTMs or Mars Orbiter Laser Altimeter (MOLA) with stereo models from the High Resolution Stereo Camera (HRSC) as well as Mercury Laser Altimeter (MLA) with Mercury Dual Imaging System (MDIS) are shown to demonstrate the broad science applications of the software tool.

Laser↗

DOE OSTI2026

Comparison of automated chemical-guided segmentation and human annotation of soil organic matter in X-ray microcomputed tomography imaging in contrasted soil types

Soil organic matter (OM) formation and persistence is strongly influenced by the spatial distribution of organic substrates and microscale soil heterogeneity by dictating OM accessibility to microorganisms. However, traditional size and/or density fractionation techniques disrupt aggregate architecture, eliminating spatial information needed to fully understand intra-aggregate OM distribution. To quantify three-dimensional OM spatial distribution and automate segmentation in X-ray microcomputed tomography (µCT) imaging without human annotation bias, we developed an iodine gas vapor (I2) based staining workflow that eliminates labor-intensive manual annotation while maintaining segmentation accuracy, using aggregates from four taxonomically diverse soils (Xerofluvent, Haploxeroll Sphagnofibrist, Palehumult) with an 8-fold range of soil organic carbon. Human annotation of 10 µCT slices by the experienced and inexperienced annotators resulted in variations up to 3% in the Dice similarity coefficient (DSC), reflecting a degree of inherent subjectivity of manual labeling. Such inconsistencies are expected to compound as the number of manually annotated slices increases. Dual-energy µCT imaging at 33.1 keV (below the iodine (I) K-edge) and 33.2 keV (above the I K-edge) was used to resolve aggregate microstructure following I2 staining. The automated image subtraction pipeline identified OM regions by the I Kedge induced brightness increases, achieving DSC values of 0.58–0.83 relative to an experienced annotator. Sensitivity analyses revealed that the reconstruction alpha value—optimized via the open-source tool TomocuPy—and the 3D registration slice count were the primary determinants of accuracy, providing a novel benchmark for dual-energy soil imaging. The pipeline without GPU acceleration achieved 9.6 to 43.2 times faster than manual annotation. Using GPU-accelerated image post-processing and affine transformation matrices, the pipeline successfully segmented OM elements for large-scale datasets (3232×3232 pixel, 2048 slices) within ~5200 s from raw file acquisition to segmented output. The high-throughput approach enables the quantification of OM spatial distribution across diverse and heterogeneous soil.

Soil microbial biomass↗

NASA NTRS2001

Robust Matching of Wavelet Features for Sub-Pixel Registration of Landsat Data

For many Earth and Space Science applications, automatic geo-registration at sub-pixel accuracy has become a necessity. In this work, we are focusing on building an operational system, which will provide a sub-pixel accuracy registration of Landsat-5 and Landsat-7 data. The input to our registration method consists of scenes that have been geometrically and radiometrically corrected. Such pre-processed scenes are then geo-registered relative to a database of Landsat chips. The method assumes a transformation composed of a rotation and a translation, and utilizes rotation- and translation-invariant wavelets to extract image features that are matched using statistically robust feature matching and a generalized Hausdorff distance metric. The registration process is described and results on four Landsat input scenes of the Washington, D.C. area are presented.

LeMoigne, Jacqueline↗

DOE OSTI2021

Time-stamping and counting of single photons using fast camera

I will discuss fast optical cameras based on the back-illuminated silicon sensor and Timepix3 ASIC. The sensor has high quantum efficiency, and the chip provides nanosecond scale time resolution and data-driven readout with 80Mpix/sec bandwidth. The intensified version of the camera is single photon sensitive and since recently has been used for registration of single photons in a variety of quantum information science and quantum imaging experiments as well as for other applications. We briefly review the camera and describe recent experiments with a Hong-Ou-Mandel interferometer to characterize its photon counting capabilities.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1987

A post-processing system for automated rectification and registration of spaceborne SAR imagery

An automated post-processing system has been developed that interfaces with the raw image output of the operational digital SAR correlator. This system is designed for optimal efficiency by using advanced signal processing hardware and an algorithm that requires no operator interaction, such as the determination of ground control points. The standard output is a geocoded image product (i.e. resampled to a specified map projection). The system is capable of producing multiframe mosaics for large-scale mapping by combining images in both the along-track direction and adjacent cross-track swaths from ascending and descending passes over the same target area. The output products have absolute location uncertainty of less than 50 m and relative distortion (scale factor and skew) of less than 0.1 per cent relative to local variations from the assumed geoid.

Curlander, John C.↗

NASA NTRS1998

Clementine High Resolution Camera Mosaicking Project: CL 6022; 80 deg S to 90 deg S Latitude, South Periapsis - Volume 22

This compact disk (CD) is part of the Clementine I high resolution (HiRes) camera lunar image mosaics developed by Malin Space Science Systems (MSSS). These mosaics were developed through calibration and semi-automated registration against the recently released geometrically and photometrically controlled Ultraviolet/Visible (UV/Vis) Basemap Mosaic, which is available through the PDS, as CD-ROM volumes CL_3001-3015. The HiRes mosaics are compiled from non-uniformity corrected, 750 nanometer ("D") filter high resolution observations from the HiRes imaging system onboard the Clementine Spacecraft. The geometric control is provided by the U.S. Geological Survey (USGS) Clementine Basemap Mosaic compiled from the 750 nm Ultraviolet/Visible Clementine imaging system. Calibration was achieved by removing the image nonuniformity largely caused by the HiRes system's light intensifier. Also provided are offset and scale factors, achieved by a fit of the HiRes data to the corresponding photometrically calibrated UV/Vis basemap that approximately transform the 8-bit HiRes data to photometric units. The mosaics on this CD are compiled from polar data (latitudes greater than 80 degrees), and are presented in the stereographic projection at a scale of 30 m/pixel at the pole, a resolution 5 times greater than that (150 m/pixel) of the corresponding UV/Vis polar basemap. This 5:1 scale ratio is in keeping with the sub-polar mosaic, in which the HiRes and UV/Vis mosaics had scales of 20 m/pixel and 100 m/pixel, respectively. The equal-area property of the stereographic projection made this preferable for the HiRes polar mosaic rather than the basemap's orthographic projection. Thus, a necessary first step in constructing the mosaic was the reprojection of the UV/Vis basemap to the stereographic projection. The HiRes polar data can be naturally grouped according to the orbital periapsis, which was in the south during the first half of the mapping mission and in the north during the second half. Images in each group have generally uniform intrinsic resolution, illumination, exposure and gain. Rather than mingle data from the two periapsis epochs, separate mosaics are provided for each, a total of 4 polar mosaics. The mosaics are divided into 100 square tiles of 2250 pixels (approximately 2.2 deg near the pole) on a side. Not all squares of this grid contain HiRes mosaic data, some inevitably since a square is not a perfect representation of a (latitude) circle, others due to the lack of HiRes data. This CD also contains ancillary data files that support the HiRes mosaic. These files include browse images with UV/Vis context stored in a Joint Photographic Experts Group (JPEG) format, index files ('imgindx.tab' and 'srcindx.tab') that tabulate the contents of the CD, and documentation files. For more information on the contents and organization of the CD volume set refer to the "FILES, DIRECTORIES AND DISK CONTENTS" section of this document. The image files are organized according to NASA's Planetary Data System (PDS) standards. An image file (tile) is organized as a PDS labeled file containing an "image object".

Malin, Michael↗

NASA NTRS1998

Clementine High Resolution Camera Mosaicking Project: CL 6020; 80 deg N to 90 deg N Latitude, South Periapsis - Volume 20

Malin, Michael↗

NASA NTRS1998

Clementine High Resolution Camera Mosaicking Project: CL 6021; 80 deg S to 90 deg S Latitude, North Periapsis - Volume 21

This compact disk (CD) is part of the Clementine I high resolution (HiRes) camera lunar image mosaics developed by Malin Space Science Systems (MSSS). These mosaics were developed through calibration and semi-automated registration against the recently released geometrically and photometrically controlled Ultraviolet/Visible (UV/Vis) Basemap Mosaic, which is available through the PDS, as CD-ROM volumes CL_3001-3015. The HiRes mosaics are compiled from non-uniformity corrected, 750 nanometer ("D") filter high resolution observations from the HiRes imaging system onboard the Clementine Spacecraft. The geometric control is provided by the U. S. Geological Survey (USGS) Clementine Basemap Mosaic compiled from the 750 nm Ultraviolet/Visible Clementine imaging system. Calibration was achieved by removing the image nonuniformity largely caused by the HiRes system's light intensifier. Also provided are offset and scale factors, achieved by a fit of the HiRes data to the corresponding photometrically calibrated UV/Vis basemap that approximately transform the 8-bit HiRes data to photometric units. The mosaics on this CD are compiled from polar data (latitudes greater than 80 degrees), and are presented in the stereographic projection at a scale of 30 m/pixel at the pole, a resolution 5 times greater than that (150 m/pixel) of the corresponding UV/Vis polar basemap. This 5:1 scale ratio is in keeping with the sub-polar mosaic, in which the HiRes and UV/Vis mosaics had scales of 20 m/pixel and 100 m/pixel, respectively. The equal-area property of the stereographic projection made this preferable for the HiRes polar mosaic rather than the basemap's orthographic projection. Thus, a necessary first step in constructing the mosaic was the reprojection of the UV/Vis basemap to the stereographic projection. The HiRes polar data can be naturally grouped according to the orbital periapsis, which was in the south during the first half of the mapping mission and in the north during the second half. Images in each group have generally uniform intrinsic resolution, illumination, exposure and gain. Rather than mingle data from the two periapsis epochs, separate mosaics are provided for each, a total of 4 polar mosaics. The mosaics are divided into 100 square tiles of 2250 pixels (approximately 2.2 deg near the pole) on a side. Not all squares of this grid contain HiRes mosaic data, some inevitably since a square is not a perfect representation of a (latitude) circle, others due to the lack of HiRes data. This CD also contains ancillary data files that support the HiRes mosaic. These files include browse images with UV/Vis context stored in a Joint Photographic Experts Group (JPEG) format, index files ('imgindx.tab' and 'srcindx.tab') that tabulate the contents of the CD, and documentation files. For more information on the contents and organization of the CD volume set refer to the "FILES, DIRECTORIES AND DISK CONTENTS" section of this document. The image files are organized according to NASA's Planetary Data System (PDS) standards. An image file (tile) is organized as a PDS labeled file containing an "image object".

Malin, Michael↗

NASA NTRS1998

Clementine High Resolution Camera Mosaicking Project: CL 6019; 80 deg N to 90 deg N Latitude, North Periapsis - Volume 19

This compact disk (CD) is part of the Clementine I high resolution (HiRes) camera lunar image mosaics developed by Malin Space Science Systems (MSSS). These mosaics were developed through calibration and semi-automated registration against the recently released geometrically and photometrically controlled Ultraviolet/Visible (UV/Vis) Basemap Mosaic, which is available through the PDS, as CD-ROM volumes CL_3001-3015. The HiRes mosaics are compiled from non-uniformity corrected, 750 nanometer ("D") filter high resolution observations from the HiRes imaging system onboard the Clementine Spacecraft. The geometric control is provided by the U. S. Geological Survey (USGS) Clementine Basemap Mosaic compiled from the 750 nm Ultraviolet/Visible Clementine imaging system. Calibration was achieved by removing the image nonuniformity largely caused by the HiRes system's light intensifier. Also provided are offset and scale factors, achieved by a fit of the HiRes data to the corresponding photometrically calibrated UV/Vis basemap that approximately transform the 8-bit HiRes data to photometric units. The mosaics on this CD are compiled from polar data (latitudes greater than 80 degrees), and are presented in the stereographic projection at a scale of 30 m/pixel at the pole, a resolution 5 times greater than that (150 m/pixel) of the corresponding UV/Vis polar basemap. This 5:1 scale ratio is in keeping with the sub-polar mosaic, in which the HiRes and UV/Vis mosaics had scales of 20 m/pixel and 100 m/pixel, respectively. The equal-area property of the stereographic projection made this preferable for the HiRes polar mosaic rather than the basemap's orthographic projection. Thus, a necessary first step in constructing the mosaic was the reprojection of the UV/Vis basemap to the stereographic projection. The HiRes polar data can be naturally grouped according to the orbital periapsis, which was in the south during the first half of the mapping mission and in the north during the second half. Images in each group have generally uniform intrinsic resolution, illumination, exposure and gain. Rather than mingle data from the two periapsis epochs, separate mosaics are provided for each, a total of 4 polar mosaics. The mosaics are divided into 100 square tiles of 2250 pixels (approximately 2.2 deg near the pole) on a side. Not all squares of this grid contain HiRes mosaic data, some inevitably since a square is not a perfect representation of a (latitude) circle, others due to the lack of HiRes data. This CD also contains ancillary data files that support the HiRes mosaic. These files include browse images with UV/Vis context stored in a Joint Photographic Experts Group (JPEG) format, index files ('imgindx.tab' and 'srcindx.tab') that tabulate the contents of the CD, and documentation files. For more information on the contents and organization of the CD volume set refer to the "FILES, DIRECTORIES AND DISK CONTENTS" section of this document. The image files are organized according to NASA's Planetary Data System (PDS) standards. An image file (tile) is organized as a PDS labeled file containing an "image object".

Malin, Michael↗