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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 NTRS2001

Spatial/Spectral Identification of Endmembers from AVIRIS Data using Mathematical Morphology

During the last several years, a number of airborne and satellite hyperspectral sensors have been developed or improved for remote sensing applications. Imaging spectrometry allows the detection of materials, objects and regions in a particular scene with a high degree of accuracy. Hyperspectral data typically consist of hundreds of thousands of spectra, so the analysis of this information is a key issue. Mathematical morphology theory is a widely used nonlinear technique for image analysis and pattern recognition. Although it is especially well suited to segment binary or grayscale images with irregular and complex shapes, its application in the classification/segmentation of multispectral or hyperspectral images has been quite rare. In this paper, we discuss a new completely automated methodology to find endmembers in the hyperspectral data cube using mathematical morphology. The extension of classic morphology to the hyperspectral domain allows us to integrate spectral and spatial information in the analysis process. In Section 3, some basic concepts about mathematical morphology and the technical details of our algorithm are provided. In Section 4, the accuracy of the proposed method is tested by its application to real hyperspectral data obtained from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) imaging spectrometer. Some details about these data and reference results, obtained by well-known endmember extraction techniques, are provided in Section 2. Finally, in Section 5 we expose the main conclusions at which we have arrived.

Plaza, Antonio↗
DOE OSTI2022

The maximum extent of the filaments and sheets in the cosmic web: an analysis of the SDSS DR17

Filaments and sheets are striking visual patterns in cosmic web. The maximum extent of these large-scale structures are difficult to determine due to their structural variety and complexity. We construct a volume-limited sample of galaxies in a cubic region from the SDSS, divide it into smaller subcubes and shuffle them around. We quantify the average filamentarity and planarity in the 3D galaxy distribution as a function of the density threshold and compare them with those from the shuffled realizations of the original data. The analysis is repeated for different shuffling lengths by varying the size of the subcubes. The average filamentarity and planarity in the shuffled data show a significant reduction when the shuffling scales are smaller than the maximum size of the genuine filaments and sheets. We observe a statistically significant reduction in these statistical measures even at a shuffling scale of $\sim 130 \, {{\, \rm Mpc}}$, indicating that the filaments and sheets in three dimensions can extend up to this length scale. They may extend to somewhat larger length scales that are missed by our analysis due to the limited size of the SDSS data cube. We expect to determine these length scales by applying this method to deeper and larger surveys in future.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2014

Erasing the Variable: Empirical Foreground Discovery for Global 21 cm Spectrum Experiments

Spectral measurements of the 21 cm monopole background have the promise of revealing the bulk energetic properties and ionization state of our universe from z approx. 6 − 30. Synchrotron foregrounds are orders of magnitude larger than the cosmological signal, and are the principal challenge faced by these experiments. While synchrotron radiation is thought to be spectrally smooth and described by relatively few degrees of freedom, the instrumental response to bright foregrounds may be much more complex. To deal with such complexities, we develop an approach that discovers contaminated spectral modes using spatial fluctuations of the measured data. This approach exploits the fact that foregrounds vary across the sky while the signal does not. The discovered modes are projected out of each line-of-sight of a data cube. An angular weighting then optimizes the cosmological signal amplitude estimate by giving preference to lower-noise regions. Using this method, we show that it is essential for the passband to be stable to at least approx. 10(exp −4). In contrast, the constraints on the spectral smoothness of the absolute calibration are mainly aesthetic if one is able to take advantage of spatial information. To the extent it is understood, controlling polarization to intensity leakage at the approx. 10(exp −2) level will also be essential to rejecting Faraday rotation of the polarized synchrotron emission. Subject headings: dark ages, reionization, first stars - methods: data analysis - methods: statistical

Variable↗
NASA NTRS2017

Structure in the 3D Galaxy Distribution: III. Fourier Transforming the Universe: Phase and Power Spectra

We demonstrate the effectiveness of a relatively straightforward analysis of the complex 3D Fourier transform of galaxy coordinates derived from redshift surveys. Numerical demonstrations of this approach are carried out on a volume-limited sample of the Sloan Digital Sky Survey redshift survey. The direct unbinned transform yields a complex 3D data cube quite similar to that from the Fast Fourier Transform (FFT) of finely binned galaxy positions. In both cases deconvolution of the sampling window function yields estimates of the true transform. Simple power spectrum estimates from these transforms are roughly consistent with those using more elaborate methods. The complex Fourier transform characterizes spatial distributional properties beyond the power spectrum in a manner different from (and we argue is more easily interpreted than) the conventional multi-point hierarchy. We identify some threads of modern large scale inference methodology that will presumably yield detections in new wider and deeper surveys.

Galactic clusters↗
NASA NTRS2017

Structure in the 3D Galaxy Distribution. III. Fourier Transforming the Universe: Phase and Power Spectra

We demonstrate the effectiveness of a relatively straightforward analysis of the complex 3D Fourier transform of galaxy coordinates derived from redshift surveys. Numerical demonstrations of this approach are carried out on a volume-limited sample of the Sloan Digital Sky Survey redshift survey. The direct unbinned transform yields a complex 3D data cube quite similar to that from the Fast Fourier Transform of finely binned galaxy positions. In both cases, deconvolution of the sampling window function yields estimates of the true transform. Simple power spectrum estimates from these transforms are roughly consistent with those using more elaborate methods. The complex Fourier transform characterizes spatial distributional properties beyond the power spectrum in a manner different from (and we argue is more easily interpreted than) the conventional multipoint hierarchy. We identify some threads of modern large-scale inference methodology that will presumably yield detections in new wider and deeper surveys.

Galaxies↗
NASA NTRS1992

Groundbased near-IR observations of the surface of Venus

We present images of the nightside of Venus taken in the near-infrared windows at 1.0, 1.1, 1.18, 1.28, 1.31, and 2.3 microns with the new infrared camera/spectrometer IRIS on the Anglo-Australian Telescope. These data were taken in spectral-mapping mode. This technique involves scanning the telescope perpendicular to the slit, while collecting spectra at successive slit positions across the planet. We produce data cubes with one spectral and two spatial dimensions. Images can be extracted over any wavelength regions. Each image has square pixels of 0.8 inch resolution. We reduced the scattered light from the sunlit crescent in images extracted from each window by subtracting images taken on either side of the window, where the Venus atmosphere is opaque. Unlike the short wavelength windows, which reveal thermal contrasts that originate primarily from the surface and deep atmosphere, the emission in the 2.3 microns window is produced at much higher altitudes (30-40 km). Emission contrasts seen near 2.3 microns are associated with horizontal variations in the cloud optical depths, and have rotation periods of about six days. We detect large contrasts in infrared emission (20-40 percent) across the disc of Venus in the 1.0-, 1.1-, 1.18-, 1.28-, and 1.31-micron images. Contrasts at these wavelengths may be due to a combination of variations in the optical depths of the overlying sulfuric acid clouds and differences in surface emission. Comparison with the 2.3-micron images show that the patterns seen in the 1.28- and 1.31-micron windows are consistent with cloud optical depth variations alone and require no contribution from the surface. However, images at 1.0, 1.1, and 1.8 microns from July 1991 show a dark feature having a contrast that increases with decreasing wavelength. This behavior is contrary to that expected of cloud absorption. Images taken on three successive days in October show another dark feature that is stationary with respect to the surface. These regions of lower emission correspond closely to the high-altitude surface regions of Beta Regio and Aphrodite Terra. The images can potentially reveal the near-infrared emissiveity of the surface of Venus, thereby complementing Magellan radar reflectivity and ground based radio emissivity measurements. The contrast ratio between highlands and plains is much smaller than would be expected for blackbody radiation from the surface along. Unlike at radio wavelengths, where the atmosphere is essentially transparent, at near-infrared wavelengths the atmosphere emits, absorbs, and scatters radiation, and can modify the observed topographically induced contrasts. The additional radiation from the atmosphere reduces the contrast, and further modification would be expected if terrain at different altitudes has different emissivities. A fit to our data therefore requires, and may constrain, a model of the lowest scale height of the atmosphere.

Meadows, V. S.↗
DOE OSTI2023

CASPI: collaborative photon processing for active single-photon imaging

Image sensors capable of capturing individual photons have made tremendous progress in recent years. However, this technology faces a major limitation. Because they capture scene information at the individual photon level, the raw data is sparse and noisy. Here we propose CASPI: Collaborative Photon Processing for Active Single-Photon Imaging, a technology-agnostic, application-agnostic, and training-free photon processing pipeline for emerging high-resolution single-photon cameras. By collaboratively exploiting both local and non-local correlations in the spatio-temporal photon data cubes, CASPI estimates scene properties reliably even under very challenging lighting conditions. We demonstrate the versatility of CASPI with two applications: LiDAR imaging over a wide range of photon flux levels, from a sub-photon to high ambient regimes, and live-cell autofluorescence FLIM in low photon count regimes. We envision CASPI as a basic building block of general-purpose photon processing units that will be implemented on-chip in future single-photon cameras.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Optical recognition of constructs using hyperspectral imaging and detection (ORCHID)

Abstract Challenges to deep sample imaging have necessitated the development of special techniques such as spatially offset optical spectroscopy to collect signals that have travelled through several layers of tissue. However, these techniques provide only spectral information in one dimension (i.e., depth). Here, we describe a general and practical method, referred to as Optical Recognition of Constructs Using Hyperspectral Imaging and Detection (ORCHID). The sensing strategy integrates (1) the spatial offset detection concept by computationally binning 2D optical data associated with digital offsets based on selected radial pixel distances from the excitation source; (2) hyperspectral imaging using tunable filter; and (3) digital image binding and collation. ORCHID is a versatile modality that is designed to collect optical signals deep inside samples across three spatial (X, Y, Z) as well as spectral dimensions. The ORCHID method is applicable to various optical techniques that exhibit narrow-band structures, from Raman scattering to quantum dot luminescence. Samples containing surface-enhanced Raman scattering (SERS)-active gold nanostar probes and quantum dots embedded in gel were used to show a proof of principle for the ORCHID concept. The resulting hyperspectral data cube is shown to spatially locate target emitting nanoparticle volumes and provide spectral information for in-depth 3D imaging.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Disturbed, diffuse, or just missing? A global study of the H I content of Hickson compact groups

Hickson compact groups (HCGs) are dense configurations of four to ten galaxies, whose H I morphology appears to follow an evolutionary sequence of three phases, with gas initially confined to galaxies, then significant amounts spread throughout the intra-group medium, and finally with almost no gas remaining in the galaxies themselves. It has also been suggested that several groups may harbour a diffuse H I component that is resolved out by interferometric observations. The H I deficiency of HCGs is expected to increase as the H I morphological phase progresses along the evolutionary sequence. If this is the case, H I deficiency would be a rough proxy for the age and evolutionary state of a HCG. We aim to test this hypothesis for the first time using a large sample of HCGs and to investigate the evidence for diffuse H I in HCGs. We performed a uniform reduction of all publicly available VLA H I observations (38 HCGs) with a purpose-built pipeline that also maximises the reproducibility of this study. The resulting H I data cubes were then analysed with the latest software tools to perform a manual separation of emission features into those belonging to galaxies and those extending into the intra-group medium. We thereby classified the H I morphological phase of each group as well as quantified their H I deficiency compared to galaxies in isolation. We find little evidence that H I deficiency can be used as a proxy for the evolutionary phase of a compact group in either of the first two phases, with the distribution of H I deficiency being consistent in both. However, for the final phase, the distribution clearly shifts to high H I deficiencies, with more than 90% of the expected H I content typically missing. Across all HCGs studied, we identify a few cases where there is strong evidence for a diffuse gas component in the intra-group medium, which might be detectable with improved observations. We also classify a new sub-phase where groups contain a lone H I -bearing galaxy, but are otherwise devoid of gas. The new morphological phase we have identified is likely the result of an evolved, gas-poor group acquiring a new, gas-rich member. The large spread of H I deficiencies in the first two morphological phases suggests that there is a broad range of initial H I content in HCGs, which is perhaps influenced by large-scale environment, and that the timescale for morphological changes is, in general, considerably shorter than the timescale for the destruction or consumption of neutral gas in these systems.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Gulf of Mexico Miocene CO2 Site Characterization Mega Transect

The project Gulf of Mexico Miocene CO2 Site Characterization Mega Transect is one of 9 site characterization projects that were implemented as part of ARRA (American Recovery and Reinvestment Act). Data from this project was used to improve resolution of data in NATCARB in the area of study. Data related to this study has already been incorporated in NATCARB Atlas. The University of Texas at Austin study focused on (1) collecting high-resolution, 3-D (HR3D) seismic datasets of the shallow geologic section to evaluate the capacity of potential reservoirs and the sealing capacity of the confining system, and (2) producing a regional CO2 atlas of Miocene age units of the upper Texas coast submerged lands (southeast Texas). The goal of the study was to evaluate the capability of the Miocene age geologic section of Texas submerged lands to permanently store large volumes of anthropogenic CO2. The geographic locations of three HR3D, “P-Cable” seismic surveys collected in the near-shore waters of southeast Texas offers a vertical and horizontal view (data “cube”) example from the second survey. The dataset's high quality allowed for defining recognizable geologic morphologies (shapes) and possible fluid content, which are important for determining an area’s prospects for geologic storage. The regional CO2 atlas of Miocene age units highlights several topics, including: (1) a regional analyses of petroleum systems as analogs for CO2 storage; (2) petrography, petrology, and extent of confining systems of the Miocene section; (3) static capacity estimate; and (4) examples of characterization methodologies of prospect areas. The HR3D datasets and regional analyses within the CO2 atlas of the offshore Texas Miocene provide a sound basis for a future generation of specific CO2 prospects in the study area.

.las↗
DOE OSTI2021

Performance of Pulsed Thermal Tomography Imaging with Machine Learning-Based Classification of Defects in Additively Manufactured Structures

Additive manufacturing (AM) is an emerging method for cost-efficient fabrication of complex topology nuclear reactor parts from high-strength corrosion resistance alloys, such as stainless steel and Inconel. AM of metallic structures for nuclear energy applications is currently based on laser powder bed fusion (LPBF) process. Some of the challenges with using LPBF method for nuclear manufacturing include the possibility of introducing pores into metallic structures. Integrity of AM structures needs to be evaluated nondestructively because material flaws could lead to premature failures in high temperature nuclear reactor environment. Currently, there exist limited capabilities to evaluate actual AM structures non-destructively. Pulsed Thermal Tomography Imaging (PTT) provides a capability for non-destructive evaluation (NDE) of subsurface defects in arbitrary size structures. The PTT method is based on recording material surface temperature transients with infrared (IR) camera following thermal pulse delivered on material surface with flash light. The PTT method has advantages for NDE of actual AM structures because the method involves one-sided non-contact measurements and fast processing of large sample areas captured in one image. Following initial qualification of an AM component for deployment in a nuclear reactor, a PTT system can also be used for in-service nondestructive evaluation (NDE) applications. In this report, we describe recent progress in enhancing PTT capabilities in detecting and visualizing microscopic defects in metallic specimens. The thermal tomography (TT) algorithm obtains depth reconstructions of spatial effusivity from the data cube of sequentially recorded surface temperatures. However, interpretation of TT images is non-trivial because of blurring of images with increasing depth. To address this challenge, we have developed a deep learning convolutional neural network (CNN) to classify size and orientation subsurface defects in simulated TT images. CNN is trained on a database of TT images created for a set of simulated metallic structures with elliptical subsurface voids. Test of CNN performance demonstrate the ability to classify radii and angular orientation of subsurface defects in TT images. In addition, we have shown that CNN trained on elliptical defects is capable of classifying irregular-shaped defects obtained from scanning electron microscopy (SEM) of stainless steel sections printed with LPBF.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Pulsed Thermal Tomography Nondestructive Examination of Additively Manufactured Reactor Materials and Components. Third Annual Progress Report

Additive manufacturing (AM) of high-strength corrosion resistance alloys for nuclear energy applications, such as stainless steel and Inconel, is currently based on laser powder bed fusion (LPBF) process. Some of the challenges with using LPBF method for nuclear manufacturing include the possibility of introducing pores into metallic structures. Probability of crack initiation at the pore depends on size, shape, and orientation of the defect. Pulsed Infrared Thermography Imaging (PIT) provides a capability for non-destructive evaluation (NDE) of sub-surface defects in arbitrary size structures. The PIT method is based on recording material surface temperature transients with infrared (IR) camera following thermal pulse delivered on material surface with flash light. The PIT method has advantages for NDE of actual AM structures because the method involves one-sided non-contact measurements and fast processing of large sample areas captured in one image. Following initial qualification of an AM component for deployment in a nuclear reactor, a PIT system can also be used for in-service nondestructive evaluation (NDE) applications. In this report, we describe recent progress in enhancing PIT capabilities in detecting microscopic subsurface defects in metals, and classifying shapes and orientation of pores in thermal images. For detection of microscopic defects in PIT imaging data, we have developed Spatial Temporal Denoised Thermal Source Separation (STDTSS) unsupervised machine learning (ML) image processing algorithm. We show that flat bottom hole (FBH) defects as small as 200µm in SS316 and IN718 specimens, can be detected with STDTSS algorithm. To the best of our knowledge, these are the smallest detected defects which are reported in literature. For classification of defects shapes, we have previously developed thermal tomography (TT) algorithm to obtain depth reconstructions of material defects from data cube of sequentially recorded surface temperatures. However, interpretation of TT images is non-trivial because of blurring with increasing depth. To address this challenge, we have developed a deep learning convolutional neural network (CNN) to classify size and orientation subsurface defects in simulated TT images.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Heating and Acceleration of Solar Wind by Parametric Decay Instability Mediated Turbulence

One of the main goals of this project to understand the origin of density fluctuations in the solar winds, as revealed by the NASA’s Flagship satellite Parker Solar Probe (PSP) measurements, which motivates us to simulate and analyze magnetohydrodynamic (MHD) turbulence in the compressible regime. To achieve this goal, we have developed a set of sophisticated turbulence driving methods to study how MHD turbulence will develop under different time-correlated fluctuations at large-scales. Another key advance is that we have developed a new 3+1 (three spatial plus time domain) 4D FFT analysis of simulation data-cubes so that we can perform the spatio-temporal spectrum and mode decomposition studies on MHD turbulence.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1986

Planetary Fabry-Perot spectroscopy

Uranus and Jupiter HD/H2 spectra determine bulk D/H ratios which are significantly different from theoretical expectations, with the Uranus D/H about half the Jovian value. Feasibility of Mars photochemistry study with a PEPSIOS spectrometer was demonstrated with visible band O2, H2O, and CO2 spectra; and near infrared (1.57 micron) spectra of CO and CO2; and NASA/IRTF observations have been proposed in support of the Mars Observer mission objectives. Analysis of monochromatic images clearly resolve the azimuthal and radial structure in the Jovian nebula (ion partitioning, temperature structure, ion/neutral interactions), adding a unique and important post-Voyager perspective and providing a baseline for forthcoming Galileo experiments. Simultaneous ground based and IUE observations of Jovian nebula are under analysis. Doppler resolved image sequences (data cubes) of Io sodium neutrals clearly isolate the high velocity charge exchange jet, a sensitive ground-based probe of the tenuous neutral atmosphere of Io.

Trauger, J. T.↗
NASA NTRS1990

Intensity dependent spread processor and workstation

The Intensity Dependent Spread (IDS) is an adaptive algorithm which is modified according to the local intensity in the scene. (This results in a nonlinear process which cannot take advantage of rather nice linear transform methods.) The computation is similar to a neural net whereby intensity information is moving from each input pixel to a set of surrounding output pixels in a manner described by Cornsweet and Yellott. A prototype of a very large scale integration IDS processor is being developed and implemented in a workstation environment. The workstation consists of a SUN 3/260 and a DATACUBE pipeline processor. The IDS prototype is a board set which operates in the DATA CUBE processor. The SUN 3/260 performs control, background processing, IDS simulation and image display functions.

Westrom, George↗
NASA NTRS1990

Fabry-Perot observations of comet Austin

Preliminary results of a program to observe Comet Austin (1990c1) from 16 April to 4 May and from 11 May to 27 May 1990 using the West Auxiliary of the McMath Solar Telescope on Kitt Peak, Arizona were presetned. The observations were made with a 15 cm duel-etalon Fabry-Perot scanning and imaging spectrometer with two modes of operation: a high resolution mode with a velocity resolution of 1.2 km/s and a medium resolution mode with a velocity resolution 10 km/s. Scanning data was obtained with an RCA C31034A photomultiplier tube and imaging data was obtained with a Photometrics LN2 cooled CCD camera with a 516 by 516 Ford chip. The results include: (1) information on the coma outflow velocity from high resolution spectral profiles of (OI)6300 and NH2 emissions, (2) gaseous water production rates from medium resolution observation of (OI)6300, (3) spectra of H2O(+) emissions in order to study the ionized component of the coma, (4) spatial distribution of H2O(+) emission features from sequences of velocity resolved images (data cubes), and (5) spatial distribution of (OI)6300 and NH2 emissions from medium resolution images. The field of view on the sky was 10.5 arcminutes in diameter. In the imaging mode the CCD was binned 4 by 4 resulting in 7.6 sec power pixel and a subarray readout for a field of view of 10.5 min.

Schultz, David↗
NASA NTRS1990

A kinematic determination of the structure of the double ring planetary nebula NGC 2392, the Eskimo

Slit spectra and existing 'velocity cube' data have been used to determine the structure of the double ring PN NGC 2392. The inner shell is a stellar wind-sculpted prolate spheroid with a ratio of axes of 2:1 and the approaching end of the long axis pointed 20 deg from the line of sight in P.A. = 200 deg. The outer ring is caused by an outer disk with density dropping off with distance from the central star and with distance from its plane, which is the same as the equatorial band of high density in the inner shell. The outer disk contains a ring of higher density knots at a distance of 16 arcsec and is losing material through free expansion, forming an outer envelope of increasing velocity. Forbidden S II spectra are used to determine the densities in all of the major regions of the nebula. It is argued that the filamentary cores at the centers of the knots seen in the outer ring originate in the sublimation of bodies formed at the same time as the parent star.

O'Dell, C. R.↗
NASA NTRS1994

Removing cosmic-ray hits from multiorbit HST Wide Field Camera images

We present an optimized algorithm that removes cosmic rays ('CRs') from multiorbit Hubble Space Telescope (HST) Wide Field/Planetary Camera ('WF/PC') images. It computes the image noise in every iteration from the WF/PC CCD equation. This includes all known sources of random and systematic calibration errors. We test this algorithm on WF/PC stacks of 2-12 orbits as a function of the number of available orbits and the formal Poissonian sigma-clipping level. We find that the algorithm needs greater than or equal 4 WF/PC exposures to locate the minimal sky signal (which is noticeably affected by CRs), with an optimal clipping level at 2-2.5 x sigma(sub Poisson). We analyze the CR flux detected on multiorbit 'CR stacks,' which are constructed by subtracting the best CR filtered images from the unfiltered 8-12 orbit average. We use an automated object finder to determine the surface density of CRS as a function of the apparent magnitude (or ADU flux) they would have generated in the images had they not been removed. The power law slope of the CR 'counts' (gamma approximately = 0.6 for N(m) m(exp gamma)) is steeper than that of the faint galaxy counts down to V approximately = 28 mag. The CR counts show a drop off between 28 less than or approximately V less than or approximately 30 mag (the latter is our formal 2 sigma point source sensitivity without spherical aberration). This prevents the CR sky integral from diverging, and is likely due to a real cutoff in the CR energy distribution below approximately 11 ADU per orbit. The integral CR surface density is less than or approximately 10(exp 8)/sq. deg, and their sky signal is V approximately = 25.5-27.0 mag/sq. arcsec, or 3%-13% of our NEP sky background (V = 23.3 mag/sq. arcsec), and well above the EBL integral of the deepest galaxy counts (B(sub J) approximately = 28.0 mag/sq. arcsec). We conclude that faint CRs will always contribute to the sky signal in the deepest WF/PC images. Since WFPC2 has approximately 2.7x lower read noise and a thicker CCD, this will result in more CR detections than in WF/PC, potentially affecting approximately 10%-20% of the pixels in multiorbit WFPC2 data cubes.

Windhorst, Rogier A.↗