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NASA NTRS2007

Mapped Landmark Algorithm for Precision Landing

A report discusses a computer vision algorithm for position estimation to enable precision landing during planetary descent. The Descent Image Motion Estimation System for the Mars Exploration Rovers has been used as a starting point for creating code for precision, terrain-relative navigation during planetary landing. The algorithm is designed to be general because it handles images taken at different scales and resolutions relative to the map, and can produce mapped landmark matches for any planetary terrain of sufficient texture. These matches provide a measurement of horizontal position relative to a known landing site specified on the surface map. Multiple mapped landmarks generated per image allow for automatic detection and elimination of bad matches. Attitude and position can be generated from each image; this image-based attitude measurement can be used by the onboard navigation filter to improve the attitude estimate, which will improve the position estimates. The algorithm uses normalized correlation of grayscale images, producing precise, sub-pixel images. The algorithm has been broken into two sub-algorithms: (1) FFT Map Matching (see figure), which matches a single large template by correlation in the frequency domain, and (2) Mapped Landmark Refinement, which matches many small templates by correlation in the spatial domain. Each relies on feature selection, the homography transform, and 3D image correlation. The algorithm is implemented in C++ and is rated at Technology Readiness Level (TRL) 4.

Johnson, Andrew↗
NASA NTRS2016

Photospheric Current Spikes as Possible Predictors of Flares

Flares involve generation of the largest current densities in the solar atmosphere. This suggests the hypothesis that prior to a large (M,X) flare there are related time dependent changes in the photospheric current distribution, and hence in the resistive heating rate in neutral line regions (NLRs). If this is true, these changes might be useful predictors of flares. Evidence supporting this hypothesis is presented. Results from a data driven, near photospheric, 3D magnetohydrodynamic type model suggest the model might be useful for predicting M and X flares several hours to several days in advance. The model takes as input the photospheric magnetic field observed by the Helioseismic & Magnetic Imager (HMI) on the Solar Dynamics Observatory (SDO) satellite. The model computes quantities in every active region (AR) pixel for 14 ARs, with spurious Doppler periods due to SDO orbital motion filtered out of the time series of the magnetic field for each pixel. Spikes in the NLR resistive heating rate Q, appearing as increases by orders of magnitude above background values in the time series of Q are found to occur, and appear to be correlated with the occurrence of M or X flares a few hours to a few days later. The subset of spikes analyzed at the pixel level are found to occur on HMI and granulation scales of 1 arcsec and 12 minutes. Spikes are found in NLRs with and without M or X flares, and outside as well as inside NLRs, but the largest spikes are localized in the NLRs of ARs with M or X flares, and associated with horizontal magnetic field strengths several hG, and vertical magnetic field strengths several orders of magnitude smaller, suggesting that the spikes are associated with current sheets.

Goodman, Michael L.↗
NASA NTRS1995

Bringing "Scientific Expeditions" Into the Schools

Two new technologies, the FASTexpedition and Remote FAST, have been developed that provide remote, 3D, high resolution, dynamic, interactive viewing of scientific data (such as simulations or measurements of fluid dynamics). The FASTexpedition permits one to access scientific data from the World Wide Web, take guided expeditions through the data, and continue with self controlled expeditions through the data. Remote FAST permits collaborators at remote sites to simultaneously view an analysis of scientific data being controlled by one of the collaborators. Control can be transferred between sites. These technologies are now being used for remote collaboration in joint university, industry, and NASA projects in computational fluid dynamics (CFD) and wind tunnel testing. Also, NASA Ames Research Center has initiated a project to make scientific data and guided expeditions through the data available as FASTexpeditions on the World Wide Web for educational purposes. Previously, remote visualiZation of dynamic data was done using video format (transmitting pixel information) such as video conferencing or MPEG movies on the Internet. The concept for this new technology is to send the raw data (e.g., grids, vectors, and scalars) along with viewing scripts over the Internet and have the pixels generated by a visualization tool running on the viewer's local workstation. The visualization tool that is currently used is FAST (Flow Analysis Software Toolkit). The advantages of this new technology over using video format are: 1. The visual is much higher in resolution (1280xl024 pixels with 24 bits of color) than typical video format transmitted over the network. 2. The form of the visualization can be controlled interactively (because the viewer is interactively controlling the visualization tool running on his workstation). 3. A rich variety of guided expeditions through the data can be included easily. 4. A capability is provided for other sites to see a visual analysis of one site as the analysis is interactively performed. Control of the analysis can be passed from site to site. 5. The scenes can be viewed in 3D using stereo vision. 6. The network bandwidth used for the visualization using this new technology is much smaller than when using video format. (The measured peak bandwidth used was 1 Kbit/sec whereas the measured bandwidth for a small video picture was 500 Kbits/sec.)

Watson, Val↗
NASA NTRS2016

Photospheric Current Spikes as Possible Predictors of Flares

Flares involve generation of the largest current densities in the solar atmosphere. This suggests the hypothesis that prior to a large (M,X) flare there are related time dependent changes in the photospheric current distribution, and hence in the resistive heating rate in neutral line regions (NLRs). If this is true, these changes might be useful predictors of flares. Preliminary evidence supporting this hypothesis is presented. Results from a data driven, near photospheric, 3D magnetohydrodynamic type model suggest the model might be useful for predicting M and X flares several hours to several days in advance. The model takes as input the photospheric magnetic field observed by the Helioseismic and Magnetic Imager (HMI) on the Solar Dynamics Observatory (SDO) satellite. The model computes quantities in every active region (AR) pixel for 14 ARs, with spurious Doppler periods due to SDO orbital motion filtered out of the time series of the magnetic field for each pixel. Spikes in the NLR resistive heating rate Q, appearing as increases by orders of magnitude above background values in the time series of Q are found to occur, and appear to be correlated with the occurrence of M or X flares a few hours to a few days later. The subset of spikes analyzed at the pixel level are found to occur on HMI and granulation scales of 1 arcsec and 12 minutes. Spikes are found in NLRs with and without M or X flares, and outside as well as inside NLRs, but the largest spikes are localized in the NLRs of ARs with M or X flares, and associated with horizontal magnetic field strengths approximately several hG, and vertical magnetic field strengths several orders of magnitude smaller. The spikes may be signatures of horizontal current sheets associated with emerging magnetic flux.

Goodman, Michael L.↗
NASA NTRS2016

Automated Segmentation and Classification of Coral using Fluid Lensing from Unmanned Airborne Platforms

In recent years, there has been a growing interest among biologists in monitoring the short and long term health of the world's coral reefs. The environmental impact of climate change poses a growing threat to these biologically diverse and fragile ecosystems, prompting scientists to use remote sensing platforms and computer vision algorithms to analyze shallow marine systems. In this study, we present a novel method for performing coral segmentation and classification from aerial data collected from small unmanned aerial vehicles (sUAV). Our method uses Fluid Lensing algorithms to remove and exploit strong optical distortions created along the air-fluid boundary to produce cm-scale resolution imagery of the ocean floor at depths up to 5 meters. A 3D model of the reef is reconstructed using structure from motion (SFM) algorithms, and the associated depth information is combined with multidimensional maximum a posteriori (MAP) estimation to separate organic from inorganic material and classify coral morphologies in the Fluid-Lensed transects. In this study, MAP estimation is performed using a set of manually classified 100 x 100 pixel training images to determine the most probable coral classification within an interrogated region of interest. Aerial footage of a coral reef was captured off the coast of American Samoa and used to test our proposed method. 90 x 20 meter transects of the Samoan coastline undergo automated classification and are manually segmented by a marine biologist for comparison, leading to success rates as high as 85%. This method has broad applications for coastal remote sensing, and will provide marine biologists access to large swaths of high resolution, segmented coral imagery.

algorithms segments classifications↗
NASA NTRS2015

Automated Segmentation and Classification of Coral Using Fluid Lensing from Unmanned Airborne Platforms

In recent years, there has been a growing interest among biologists in monitoring the short and long term health of the worlds coral reefs. The environmental impact of climate change poses a growing threat to these biologically diverse and fragile ecosystems, prompting scientists to use remote sensing platforms and computer vision algorithms to analyze shallow marine systems. In this study, we present a novel method for performing coral segmentation and classification from aerial data collected from small unmanned aerial vehicles (sUAV). Our method uses Fluid Lensing algorithms to remove and exploit strong optical distortions created along the air-fluid boundary to produce cm-scale resolution imagery of the ocean floor at depths up to 5 meters. A 3D model of the reef is reconstructed using structure from motion (SFM) algorithms, and the associated depth information is combined with multidimensional maximum a posteriori (MAP) estimation to separate organic from inorganic material and classify coral morphologies in the Fluid-Lensed transects. In this study, MAP estimation is performed using a set of manually classified 100 x 100 pixel training images to determine the most probable coral classification within an interrogated region of interest. Aerial footage of a coral reef was captured off the coast of American Samoa and used to test our proposed method. 90 x 20 meter transects of the Samoan coastline undergo automated classification and are manually segmented by a marine biologist for comparison, leading to success rates as high as 85. This method has broad applications for coastal remote sensing, and will provide marine biologists access to large swaths of high resolution, segmented coral imagery.

algorithms segments classifications↗
NASA NTRS2011

Visual Object Recognition and Tracking of Tools

A method has been created to automatically build an algorithm off-line, using computer-aided design (CAD) models, and to apply this at runtime. The object type is discriminated, and the position and orientation are identified. This system can work with a single image and can provide improved performance using multiple images provided from videos. The spatial processing unit uses three stages: (1) segmentation; (2) initial type, pose, and geometry (ITPG) estimation; and (3) refined type, pose, and geometry (RTPG) calculation. The image segmentation module files all the tools in an image and isolates them from the background. For this, the system uses edge-detection and thresholding to find the pixels that are part of a tool. After the pixels are identified, nearby pixels are grouped into blobs. These blobs represent the potential tools in the image and are the product of the segmentation algorithm. The second module uses matched filtering (or template matching). This approach is used for condensing synthetic images using an image subspace that captures key information. Three degrees of orientation, three degrees of position, and any number of degrees of freedom in geometry change are included. To do this, a template-matching framework is applied. This framework uses an off-line system for calculating template images, measurement images, and the measurements of the template images. These results are used online to match segmented tools against the templates. The final module is the RTPG processor. Its role is to find the exact states of the tools given initial conditions provided by the ITPG module. The requirement that the initial conditions exist allows this module to make use of a local search (whereas the ITPG module had global scope). To perform the local search, 3D model matching is used, where a synthetic image of the object is created and compared to the sensed data. The availability of low-cost PC graphics hardware allows rapid creation of synthetic images. In this approach, a function of orientation, distance, and articulation is defined as a metric on the difference between the captured image and a synthetic image with an object in the given orientation, distance, and articulation. The synthetic image is created using a model that is looked up in an object-model database. A composable software architecture is used for implementation. Video is first preprocessed to remove sensor anomalies (like dead pixels), and then is processed sequentially by a prioritized list of tracker-identifiers.

English, James↗
NASA NTRS2013

NASA Tech Briefs, April 2013

Topics covered include: Fully Integrated, Miniature, High-Frequency Flow Probe Utilizing MEMS Leadless SOI Technology; Nanoscale Surface Plasmonics Sensor With Nanofluidic Control; Advanced Dispersed Fringe Sensing Algorithm for Coarse Phasing Segmented Mirror Telescopes; Neural Network Back-Propagation Algorithm for Sensing Hypergols; Bulk Moisture and Salinity Sensor; Change-Based Satellite Monitoring Using Broad Coverage and Targetable Sensing; Circularly Polarized Microwave Antenna Element with Very Low Off-Axis Cross-Polarization; Ultra-Low Heat-Leak, High-Temperature Superconducting Current Leads for Space Applications; Flash Cracking Reactor for Waste Plastic Processing; An Automated Safe-to-Mate (ASTM) Tester; Wireless Chalcogenide Nanoionic-Based Radio-Frequency Switch; Compute Element and Interface Box for the Hazard Detection System; DOT Transmit Module; Composite Aerogel Multifoil Protective Shielding; Li-Ion Electrolytes with Improved Safety and Tolerance to High-Voltage Systems; Polymer-Reinforced, Non-Brittle, Lightweight Cryogenic Insulation; Controlled, Site-Specific Functionalization of Carbon Nanotubes with Diazonium Salts; Regenerable Sorbent for CO2 Removal; Sprayable Aerogel Bead Compositions With High Shear Flow Resistance and High Thermal Insulation Value; Lexan Linear Shaped Charge Holder with Magnets and Backing Plate; Robotic Ankle for Omnidirectional Rock Anchors; Wind, Wave, and Tidal Energy Without Power Conditioning; An Active Heater Control Concept to Meet IXO Type Mirror Module Thermal-Structural Distortion Requirement; Waterless Clothes-Cleaning Machine; Integrated Electrical Wire Insulation Repair System; LVGEMS Time-of-Flight Mass Spectrometry on Satellites; Surface Inspection Tool for Optical Detection of Surface Defects; Per-Pixel, Dual-Counter Scheme for Optical Communications; Certification-Based Process Analysis; Surface Navigation Using Optimized Waypoints and Particle Swarm Optimization; Smart-Divert Powered Descent Guidance to Avoid the Backshell Landing Dispersion Ellipse; Estimating Foreign-Object-Debris Density from Photogrammetry Data; Adaptive Sampling of Spatiotemporal Phenomena with Optimization Criteria; Building a 2.5D Digital Elevation Model From 2D Imagery; Eyes on the Earth 3D; Target Trailing With Safe Navigation for Maritime Autonomous Surface Vehicles; Adams-Based Rover Terramechanics and Mobility Simulator - ARTEMIS; ISTP CDF Skeleton Editor; Uplink Summary Generator (ULSGEN) Version 1.0; Robotics On-Board Trainer (ROBoT); Software Engineering Tools for Scientific Models; Automatic Data Filter Customization Using a Genetic Algorithm; Tracker Toolkit; Towards Efficient Scientific Data Management Using Cloud Storage; On a Formal Tool for Reasoning About Flight Software Cost Analysis; A Nanostructured Composites Thermal Switch Controls Internal and External Short Circuit in Lithium Ion Batteries; Spacecraft Crew Cabin Condensation Control; and Functional Near-Infrared Spectroscopy Signals Measure Neuronal Activity in the Cortex.

Source record↗
NASA NTRSDate not supplied

Adaptive Wavelength Scanning Lidar (AWSL) for 3D Mapping from Space

We present the design and performance of an adaptive wavelength scanning lidar (AWSL) for highly efficient mapping from low Earth orbit (LEO). Mapping is accomplished by steering a laser beam across 1,200 resolvable spots using wavelength tuning and grating dispersion. Any subset of these 1,200 spots can be selected by wavelength switching. The design is validated with an 1550-nm prototype using a fast wavelength-tuned (500-kHz) pulsed (2-ns) fiber laser with the beam dispersed by gratings for beam steering. Reflected pulses are detected with an eight-pixel detector array with single-photon sensitivity. Eight lidar returns are time-multiplexed to one output that is digitized with a single 1-GSPS-digitizer, to save power. A grating spectrometer rejects solar background noise spatially and spectrally, and images laser footprints on to the detector array. The gratings retain the fiber laser beam quality. We are developing a 1030-nm AWSL intended for a LEO SmallSat platform.

Guangning Yang↗
NASA NTRS1998

Computation of the Effects of Inhomogeneous Clouds on Retrieval of Remotely Sensed Properties

Current and future earth observation programs depend on satellite measurements of radiance to retrieve the properties of clouds on a global basis. At present, this retrieval is made assuming that the clouds in the instrument field of view are plane parallel and independent of adjacent pixels. While this assumption is known to be false except in very limited cases, its impact can be evaluated, and if possible corrected, based on emerging theoretical techniques. In this study, the Spherical Harmonic Discrete Ordinate Method (SHDOM, Evans, 1996) has been used to assess the sensitivity of the retrieval to a variety of cloud parameters. SHDOM allows the plane parallel assumption to be relaxed and makes 2D and even 3D radiative solutions practical. A previous study (Chambers et al., 1996) assessed the effect of horizontal inhomogeneity in 45 LANDSAT scenes of boundary layer clouds over ocean. The four scenes studied here represent overcast, broken, scattered and strongly thermally forced cloud fields and are used to perform sensitivity studies to a wider variety of parameters. Comparisons are made at three solar zenith angles (theta (sub 0) = 0, 49, and 63 degrees) to avoid ambiguity in the results due to solar zenith angle.

Chambers, Lin H.↗
NASA NTRS2013

Raster-Based Approach to Solar Pressure Modeling

An algorithm has been developed to take advantage of the graphics processing hardware in modern computers to efficiently compute high-fidelity solar pressure forces and torques on spacecraft, taking into account the possibility of self-shading due to the articulation of spacecraft components such as solar arrays. The process is easily extended to compute other results that depend on three-dimensional attitude analysis, such as solar array power generation or free molecular flow drag. The impact of photons upon a spacecraft introduces small forces and moments. The magnitude and direction of the forces depend on the material properties of the spacecraft components being illuminated. The parts of the components being lit depends on the orientation of the craft with respect to the Sun, as well as the gimbal angles for any significant moving external parts (solar arrays, typically). Some components may shield others from the Sun. The purpose of this innovation is to enable high-fidelity computation of solar pressure and power generation effects of illuminated portions of spacecraft, taking self-shading from spacecraft attitude and movable components into account. The key idea in this innovation is to compute results dependent upon complicated geometry by using an image to break the problem into thousands or millions of sub-problems with simple geometry, and then the results from the simpler problems are combined to give high-fidelity results for the full geometry. This process is performed by constructing a 3D model of a spacecraft using an appropriate computer language (OpenGL), and running that model on a modern computer's 3D accelerated video processor. This quickly and accurately generates a view of the model (as shown on a computer screen) that takes rotation and articulation of spacecraft components into account. When this view is interpreted as the spacecraft as seen by the Sun, then only the portions of the craft visible in the view are illuminated. The view as shown on the computer screen is composed of up to millions of pixels. Each of those pixels is associated with a small illuminated area of the spacecraft. For each pixel, it is possible to compute its position, angle (surface normal) from the view direction, and the spacecraft material (and therefore, optical coefficients) associated with that area. With this information, the area associated with each pixel can be modeled as a simple flat plate for calculating solar pressure. The vector sum of these individual flat plate models is a high-fidelity approximation of the solar pressure forces and torques on the whole vehicle. In addition to using optical coefficients associated with each spacecraft material to calculate solar pressure, a power generation coefficient is added for computing solar array power generation from the sum of the illuminated areas. Similarly, other area-based calculations, such as free molecular flow drag, are also enabled. Because the model rendering is separated from other calculations, it is relatively easy to add a new model to explore a new vehicle or mission configuration. Adding a new model is performed by adding OpenGL code, but a future version might read a mesh file exported from a computer-aided design (CAD) system to enable very rapid turnaround for new designs

Wright, Theodore W. II↗
NASA NTRS2017

Gaussian Mixture Models for Temporal Depth Fusion

Sensing the 3D environment of a moving robot is essential for collision avoidance. Most 3D sensors produce dense depth maps, which are subject to imperfections due to various environmental factors. Temporal fusion of depth maps is crucial to overcome those. Temporal fusion is traditionally done in 3D space with voxel data structures, but it can be approached by temporal fusion in image space, with potential benefits in reduced memory and computational cost for applications like reactive collision avoidance for micro air vehicles. In this paper, we present an efficient Gaussian Mixture Models based depth map fusion approach, introducing an online update scheme for dense representations. The environment is modeled from an ego-centric point of view, where each pixel is represented by a mixture of Gaussian inverse-depth models. Consecutive frames are related to each other by transformations obtained from visual odometry. This approach achieves better accuracy than alternative image space depth map fusion techniques at lower computational cost.

Matthies, Larry↗
NASA NTRS1995

Remote Visualization and Remote Collaboration On Computational Fluid Dynamics

A new technology has been developed for remote visualization that provides remote, 3D, high resolution, dynamic, interactive viewing of scientific data (such as fluid dynamics simulations or measurements). Based on this technology, some World Wide Web sites on the Internet are providing fluid dynamics data for educational or testing purposes. This technology is also being used for remote collaboration in joint university, industry, and NASA projects in computational fluid dynamics and wind tunnel testing. Previously, remote visualization of dynamic data was done using video format (transmitting pixel information) such as video conferencing or MPEG movies on the Internet. The concept for this new technology is to send the raw data (e.g., grids, vectors, and scalars) along with viewing scripts over the Internet and have the pixels generated by a visualization tool running on the viewer's local workstation. The visualization tool that is currently used is FAST (Flow Analysis Software Toolkit).

Watson, Val↗
NASA NTRS2011

In Situ Surface Characterization

Operation of in situ space assets, such as rovers and landers, requires operators to acquire a thorough understanding of the environment surrounding the spacecraft. The following programs help with that understanding by providing higher-level information characterizing the surface, which is not immediately obvious by just looking at the XYZ terrain data. This software suite covers three primary programs: marsuvw, marsrough, and marsslope, and two secondary programs, which together use XYZ data derived from in situ stereo imagery to characterize the surface by determining surface normal, surface roughness, and various aspects of local slope, respectively. These programs all use the Planetary Image Geometry (PIG) library to read mission-specific data files. The programs themselves are completely multimission; all mission dependencies are handled by PIG. The input data consists of images containing XYZ locations as derived by, e.g., marsxyz. The marsuvw program determines surface normals from XYZ data by gathering XYZ points from an area around each pixel and fitting a plane to those points. Outliers are rejected, and various consistency checks are applied. The result shows the orientation of the local surface at each point as a unit vector. The program can be run in two modes: standard, which is typically used for in situ arm work, and slope, which is typically used for rover mobility. The difference is primarily due to optimizations necessary for the larger patch sizes in the slope case. The marsrough program determines surface roughness in a small area around each pixel, which is defined as the maximum peak-to-peak deviation from the plane perpendicular to the surface normal at that pixel. The marsslope program takes a surface normal file as input and derives one of several slope-like outputs from it. The outputs include slope, slope rover direction (a measure of slope radially away from the rover), slope heading, slope magnitude, northerly tilt, and solar energy (compares the slope with the Sun s location at local noon). The marsuvwproj program projects a surface normal onto an arbitrary plane in space, resulting in a normalized 3D vector, which is constrained to lie in the plane. The marsuvwrot program rotates the vectors in a surface normal file, generating a new surface normal file. It also can change coordinate systems for an existing surface normal file. While the algorithms behind this suite are not particularly unique, what makes the programs useful is their integration into the larger in situ image processing system via the PIG library. They work directly with space in situ data, understanding the appropriate image metadata fields and updating them properly. The secondary programs (marsuvwproj, marsuvwrot) were originally developed to deal with anomalous situations on Opportunity and Spirit, respectively, but may have more general applicability.

Deen, Robert G.↗
NASA NTRSDate not supplied

Towards Physics Guided Optical Flow for Tracking Atmospheric Motion

Observations of atmospheric 3D winds are critical for improving short-range and long-range forecasting. Such advancement in forecasting directly applies to research in a number of areas including convective processes, wildfire plumes and tornado prediction. Atmospheric Motion Vectors (AMVs) provide a passively sensed approach to quantifying horizontal motion and cloud heights, which are typically sourced from geostationary sensors due to the availability of high frequency observations. Recent work has shown that estimating AMVs by tracking individual pixels with dense optical flow is a promising new direction. In this work, we compare state-of-the-art convolutional neural networks for optical flow in a physics-guided deep learning framework for predicting AMVs. The approach is semi-supervised and uses physically informed wind vectors from high-resolution numerical simulations for supervised learning followed by fine-tuning though warping and reconstruction of full-disk geostationary images (GOES-16). In the vertical direction, we use labels from the CALIPSO low-earth orbit satellite to predict cloud height from 16-band geostationary images with a neural network. We present results for both tasks on held-out time periods and secondary datasets.

Geostationary↗
NASA NTRS2013

A CANDELS-3d-HST Synergy: Resolved Star Formation Patterns at 0.7 less than z less than 1.5

We analyze the resolved stellar populations of 473 massive star-forming galaxies at 0.7 < z < 1.5, with multiwavelength broadband imaging from CANDELS andHalpha surface brightness profiles at the same kiloparsec resolution from 3D-HST. Together, this unique data set sheds light on how the assembled stellar mass is distributed within galaxies, and where new stars are being formed. We find the Halpha morphologies to resemble more closely those observed in the ACS I band than in the WFC3 H band, especially for the larger systems. We next derive a novel prescription for Halpha dust corrections, which accounts for extra extinction toward H II regions. The prescription leads to consistent star formation rate (SFR) estimates and reproduces the observed relation between the Halpha/UV luminosity ratio and visual extinction, on both a pixel-by-pixel and a galaxy-integrated level. We find the surface density of star formation to correlate with the surface density of assembled stellar mass for spatially resolved regions within galaxies, akin to the so-called "main sequence of star formation" established on a galaxy-integrated level. Deviations from this relation toward lower equivalent widths are found in the inner regions of galaxies. Clumps and spiral features, on the other hand, are associated with enhanced H alpha equivalent widths, bluer colors, and higher specific SFRs compared to the underlying disk. Their Halpha/UV luminosity ratio is lower than that of the underlying disk, suggesting that the ACS clump selection preferentially picks up those regions of elevated star formation activity that are the least obscured by dust. Our analysis emphasizes that monochromatic studies of galaxy structure can be severely limited by mass-to-light ratio variations due to dust and spatially inhomogeneous star formation histories.

SYNERGY↗
NASA NTRS2005

Advanced Three-Dimensional Display System

A desktop-scale, computer-controlled display system, initially developed for NASA and now known as the VolumeViewer(TradeMark), generates three-dimensional (3D) images of 3D objects in a display volume. This system differs fundamentally from stereoscopic and holographic display systems: The images generated by this system are truly 3D in that they can be viewed from almost any angle, without the aid of special eyeglasses. It is possible to walk around the system while gazing at its display volume to see a displayed object from a changing perspective, and multiple observers standing at different positions around the display can view the object simultaneously from their individual perspectives, as though the displayed object were a real 3D object. At the time of writing this article, only partial information on the design and principle of operation of the system was available. It is known that the system includes a high-speed, silicon-backplane, ferroelectric-liquid-crystal spatial light modulator (SLM), multiple high-power lasers for projecting images in multiple colors, a rotating helix that serves as a moving screen for displaying voxels [volume cells or volume elements, in analogy to pixels (picture cells or picture elements) in two-dimensional (2D) images], and a host computer. The rotating helix and its motor drive are the only moving parts. Under control by the host computer, a stream of 2D image patterns is generated on the SLM and projected through optics onto the surface of the rotating helix. The system utilizes a parallel pixel/voxel-addressing scheme: All the pixels of the 2D pattern on the SLM are addressed simultaneously by laser beams. This parallel addressing scheme overcomes the difficulty of achieving both high resolution and a high frame rate in a raster scanning or serial addressing scheme. It has been reported that the structure of the system is simple and easy to build, that the optical design and alignment are not difficult, and that the system can be built by use of commercial off-the-shelf products. A prototype of the system displays an image of 1,024 by 768 by 170 (=133,693,440) voxels. In future designs, the resolution could be increased. The maximum number of voxels that can be generated depends upon the spatial resolution of SLM and the speed of rotation of the helix. For example, one could use an available SLM that has 1,024 by 1,024 pixels. Incidentally, this SLM is capable of operation at a switching speed of 300,000 frames per second. Implementation of full-color displays in future versions of the system would be straightforward: One could use three SLMs for red, green, and blue, respectively, and the colors of the voxels could be automatically controlled. An optically simpler alternative would be to use a single red/green/ blue light projector and synchronize the projection of each color with the generation of patterns for that color on a single SLM.

Geng, Jason↗
NASA NTRS1998

Influence of Subpixel Scale Cloud Top Structure on Reflectances from Overcast Stratiform Cloud Layers

Recent observational studies have shown that satellite retrievals of cloud optical depth based on plane-parallel model theory suffer from systematic biases that depend on viewing geometry, even when observations are restricted to overcast marine stratus layers, arguably the closest to plane parallel in nature. At moderate to low sun elevations, the plane-parallel model significantly overestimates the reflectance dependence on view angle in the forward-scattering direction but shows a similar dependence in the backscattering direction. Theoretical simulations are performed that show that the likely cause for this discrepancy is because the plane-parallel model assumption does not account for subpixel, scale variations in cloud-top height (i.e., "cloud bumps"). Monte Carlo simulation, comparing ID model radiances to radiances from overcast cloud field with 1) cloud-top height variation, but constant cloud volume extinction; 2) flat tops but horizontal variations in cloud volume extinction; and 3) variations in both cloud top height and cloud extinction are performed over a approximately equal to 4 km x 4 km domain (roughly the size of an individual GAC AVHRR pixel). The comparisons show that when cloud-top height variations are included, departures from 1D theory are remarkably similar (qualitatively) to those obtained observationally. In contrast, when clouds are assumed flat and only cloud extinction is variable, reflectance differences are much smaller and do not show any view-angle dependence. When both cloud-top height and cloud extinction variations are included, however, large increases in cloud extinction variability can enhance reflectance difference. The reason 3D-1D reflectance differences are more sensitive to cloud-top height variations in the forward-scattering direction (at moderate to low, sun elevations) is because photons leaving the cloud field in that direction experience fewer scattering events (low-order scattering) and are restricted to the topmost portions of the cloud. While reflectance deviations from 1D theory are much larger for bumpy clouds than for flat clouds with variable cloud extinction, differences in cloud albedo are comparable for these two cases.

Loeb, N. G.↗