A performance analysis of the optical- mechanical scanner as an imaging system for planetary landers
Performance analysis of optical-mechanical scanner as imaging system for planetary landers
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Performance analysis of optical-mechanical scanner as imaging system for planetary landers
A PC-based interactive image processing system to analyze Indian Geosynchronous Satellite (Insat) data has been developed for Asian monsoon studies. The system, known as a Microbased Image Display and Graphics Enhancement Tool (MIDGET), is designed as a workstation terminal in a supercomputer environment. The MIDGET system is described and the analysis procedures used with the system are discussed. The applications of the MIDGET system include monitoring monsoon evolution and the behavior of organized tropical storms, the analysis of low-frequency intraseasonal oscillations, diagnostic studies of cloudiness, retrieval of monsoon precipitation, and statistical prediction of monsoon cloud bands associated with intraseasonal fluctuations of monsoon rainfall.
The launch of Landsat-4 in July 1982 represents a continuation in the remote sensing of earth resources. The 80-m spatial resolution provided by the Multispectral Scanner (MSS) on board the satellite is fine enough to resolve many natural features and land-use details in both rural and urban settings. The second sensor of the spacecraft, the Thematic Mapper (TM), introduces a new era of sensing with refined spatial resolution (30 m) and expanded spectral coverage (7 bands). This paper describes results from engineering studies of the characteristics of digital image data from the two Landsat-4 sensors. These studies form a part of the Landsat-4 Image Data Quality Analysis program (LIDQA). The image data were generally found to be of high quality and the TM provided several improvements over the MSS, in its spatial and spectral characteristics.
The launch of LANDSAT-4 in July 1982 represents a continuation in the remote sensing of earth resources. The 80-m spatial resolution provided by the Multispectral Scanner (MSS) on board the satellite is fine enough to resolve many natural features and land-use details in both rural and urban settings. The second sensor of the spacecraft, the Thematic Mapper (TM), introduce a new era of sensing with refined spatial resolution (30 m) and expanded spectral coverage (7 bands). This paper describes results from engineering studies of the characteristics of digital image data from the two LANDSAT-4 sensors are described. These studies form a part of the LANDSAT-4 Image Data Quality Analysis program (LIDQA). The image data were generally found to be of high quality and the TM provided several improvements over the MSS, in its spatial and spectral characteristics.
High resolution images of non-spherical objects, such as Viking images of Phobos and the anticipated Galileo images of Gaspra, lend themselves to conventional planetary cartographic procedures: control network analysis, stereophotogrammetry, image mosaicking in 2D or 3D, and airbrush mapping. There remains the problem of a suitable map projection for bodies which are extremely elongated or irregular in shape. Many bodies will soon be seen at lower resolution (5-30 pixels across the disk) in images from speckle interferometry, the Hubble Space Telescope, ground-based radar, distinct spacecraft encounters, and closer images degraded by smear. Different data with similar effective resolutions are available from stellar occultations, radar or lightcurve convex hulls, lightcurve modeling of albedo variations, and cometary jet modeling. With such low resolution, conventional methods of shape determination will be less useful or will fail altogether, leaving limb and terminator topography as the principal sources of topographic information. A method for shape determination based on limb and terminator topography was developed. It has been applied to the nucleus of Comet Halley and the jovian satellite Amalthea. The Amalthea results are described to give an example of the cartographic possibilities and problems of anticipated data sets.
A clear goal of the Virtual Observatory (VO) is to enable new science through analysis of integrated astronomical archives. An additional and powerful possibility of the VO is to link and integrate these new analyses with planning of new observations. By providing tools that can be used for observation planning in the VO, the VO will allow the data lifecycle to come full circle: from theory to observations to data and back around to new theories and new observations. The Scientist's Expert Assistant (SEA) Simulation Facility (SSF) is working to combine the ability to access existing archives with the ability to model and visualize new observations. Integrating the two will allow astronomers to better use the integrated archives of the VO to plan and predict the success of potential new observations. The full circle lifecycle enabled by SEA can allow astronomers to make substantial leaps in the quality of data and science returns on new observations. Our paper will examine the exciting potential of integrating archival analysis with new observation planning, such as performing data calibration analysis on archival images and using that analysis to predict the success of new observations, or performing dynamic signal-to-noise analysis combining historical results with modeling of new instruments or targets. We will also describe how the development of the SSF is progressing and what has been its successes and challenges.
A clear goal of the Virtual Observatory (VO) is to enable new science through analysis of integrated astronomical archives. An additional and powerful possibility of the VO is to link and integrate these new analyses with planning of new observations. By providing tools that can be used for observation planning in the VO, the VO will allow the data lifecycle to come full circle: from theory to observations to data and back around to new theories and new observations. The Scientist's Expert Assistant (SEA) Simulation Facility (SSF) is working to combine the ability to access existing archives with the ability to model and visualize new observations. Integrating the two will allow astronomers to better use the integrated archives of the VO to plan and predict the success of potential new observations more efficiently, The full circle lifecycle enabled by SEA can allow astronomers to make substantial leaps in the quality of data and science returns on new observations. Our paper examines the exciting potential of integrating archival analysis with new observation planning, such as performing data calibration analysis on archival images and using that analysis to predict the success of new observations, or performing dynamic signal-to-noise analysis combining historical results with modeling of new instruments or targets. We will also describe how the development of the SSF is progressing and what have been its successes and challenges.
Results are presented from a baseline study using an synthetic stereo image pair to test the Automatic Stereo Analysis (ASA) technique for reproducing cloud top structure. The ASA analysis, display, and calibration procedures are described. A GEO/LEO (GOES/NOAA AVHRR) image pair from Hurrican Allen in 1980 is used to illustrate the results that can be obtained using the ASA technique. Also, results are presented from applying the ASA technique to a GEO/GEO (GOES/GOES) image pair of Hurricane Gilbert in 1988.
In this work, the implementation and use of AVHRR (Advanced Very High Resolution Radiometer) images for subpixel analysis is studied. The work consists of two parts, the first is making training data, the second is using the training data to design a neural net subpixel analyzer. Most work on subpixel analysis has been done with images with more spectral bands. AVHRR images were chosen because of their easy acquisition, and because the five spectral bands allow investigation into the development of training data. The first step in subpixel analysis is the development of training data. This consists of image to be classified, and the classification of each pixel. In order to do the classification, a high spatial resolution image is typically needed in order to manually create a classified image. It is difficult to have both the image of interest, and a high spatial resolution image of the same area taken at the same time. Thus it was studied whether a subsampled image taken from the image of interest could serve as the training data. Statistical work has been done showing the unusefulness of this approach. In the second part of the analysis, a feedforward neural net was trained and used to classify the AVHRR images. Results of these tests, comparing the neural net with typical statistical based schemes are shown.
The ability to detect, measure, and locate the source of contaminants, especially heavy metals and radionuclides, is of ongoing interest. A common tool for contaminant identification and bioremediation is vegetation that can accumulate and indicate recent and historic pollution. However, large-scale sampling can be costly and labor-intensive. Hence, non-invasive in-situ techniques such as laser-induced fluorescence (LIF) are becoming useful and effective ways to observe the health of plants through the excitation of organic molecules, e.g., chlorophyll. The technique presented utilizes images collected of LIF in moss to identify different metals and environmental stressors. Analysis through image processing of LIF response was key to identifying Cu, Zn, Pb, and a mixture of the metals at nmol/cm 2 levels. Specifically, the RGB values from each image were used to create density histograms of each color channel’s relative pixel abundance at each decimal code value. These histograms were then used to compare color shifts linked to the successful identification of contaminated moss samples. Photoperiod and extraneous environmental stressors had minimal impact on the histogram color shift compared to metals and presented with a response that differentiated them from metal contamination.
Hover predictions of tiltrotor aircraft are hampered by the lack of accurate and computationally efficient models for rotor/wing interactional aerodynamics. This paper summarizes the development of an approximate, potential flow solution for the rotor-on-rotor and wing-on-rotor interactions. This analysis is based on actuator disk and vortex theory and the method of images. The analysis is applicable for out-of-ground-effect predictions. The analysis is particularly suited for aircraft preliminary design studies. Flow field predictions from this simple analytical model are validated against experimental data from previous studies. The paper concludes with an analytical assessment of the influence of rotor-on-rotor and wing-on-rotor interactions. This assessment examines the effect of rotor-to-wing offset distance, wing sweep, wing span, and flaperon incidence angle on tiltrotor inflow and performance.
The focus of this project is to use Infrared Thermography, a non-destructive test, to detect detrimental cracks and voids beneath the surface of materials used in the space program. This project will consist of developing a simulation model of the Infrared Thermography inspection of the Graphite/Epoxy specimen. The simulation entails finding the correct physical properties for this specimen as well as programming the model for thick voids or flat bottom holes. After the simulation is completed, an Infrared Thermography inspection of the actual specimen will be made. Upon acquiring the experimental test data, an analysis of the data for the actual experiment will occur, which includes analyzing images, graphical analysis, and analyzing numerical data received from the infrared camera. The simulation will then be corrected for any discrepancies between it and the actual experiment. The optimized simulation material property inputs can then be used for new simulation for thin voids. The comparison of the two simulations, the simulation for the thick void and the simulation for the thin void, provides a correlation between the peak contrast ratio and peak time ratio. This correlation is used in the evaluation of flash thermography data during the evaluation of delaminations.
Remote spectral measurements of light reflected or emitted from terrestrial scenes is commonly integrated over areas sufficiently large that the surface comprises more than one component. Techniques have been developed to analyze multispectral or imaging spectrometer data in terms of a wide range of mixtures of a limited number of components. Spectral mixture analysis has been used primarily for visible and near-infrared images, but it may also be applied to thermal infrared data. Two approaches are reviewed: binary mixing and a more general treatment for isothermal mixtures of a greater number of components.
A neural network based data analysis and decision making system to increase the autonomy of a planetary rover or similar exploratory vehicle is presented. A hierarchical series of neural networks for real time analysis of scientific images is used. The system under development emphasizes analysis of multispectral images by classifier and feature detector neural networks, to provide information on the mineral composition of a scene. A hierarchy of alternating analysis and decision making networks is being developed to allow increasingly fine scale analysis in regions of the image that are potentially important. It is noted that this system will facilitate both the selection of high priorty scientific information for transmission to earth, and the autonomous collection of rocks and soil for sample return.
Assessing DNA damage induction, repair and consequences of such damages requires measurement of specific DNA lesions by methods that are independent of biological responses to such lesions. Lesions affecting one DNA strand (altered bases, abasic sites, single strand breaks (SSB)) as well as damages affecting both strands (clustered damages, double strand breaks) can be quantified by direct measurement of DNA using gel electrophoresis, gel imaging and number average length analysis. Damage frequencies as low as a few sites per gigabase pair (10(9)bp) can be quantified by this approach in about 50ng of non-radioactive DNA, and single molecule methods may allow such measurements in DNA from single cells. This review presents the theoretical basis, biochemical requirements and practical aspects of this approach, and shows examples of their applications in identification and quantitation of complex clustered damages.
PAC Skyview 2.0 is interactive program for display and analysis of astronomical images. Includes large set of functions for display, analysis and manipulation of images. "Man" pages with descriptions of functions and examples of usage included. Skyview used interactively or in "server" mode, in which another program calls Skyview and executes commands itself. Skyview capable of reading image data files of four types, including those in FITS, S, IRAF, and Z formats. Written in C.
Several sequences of the dark (Jupiter-illuminated) side of Io obtained during the Voyager 2 encounter present opporunity for understanding several problems relating to the surface composition of Io. The existence or absence of SO2 condensates on the night side is a sensitive indicator of an SO2 atmosphere. Preliminary analysis of the night side Io images suggests localized brightenings of approximately 25% may exist. Examination of the night side images represents an even more sensitive indicator for pure sulfur. Between 60 and 130 degrees (the minimum nighttime and maximum daytime temperatures, respectively), the relative spectral reflectance for yellow sulfur observed in the Voyager green and clear filters decreases by 25%. This decrease should be detectable on the nightside images. A search of the Voyager 2 Jupiter-illuminated images yielded a single pair of green and clear images. In these images one hemisphere of Io is Sun-illuminated and the other is Jupiter illuminated. Geologically similar regions of Io are being selected to obtain average color ratios of specific geologic units for both day and night sides.
The author has identified the following significant results. A procedure was developed to extract cross-band textural features from ERTS MSS imagery. Evolving from a single image texture extraction procedure which uses spatial dependence matrices to measure relative co-occurrence of nearest neighbor grey tones, the cross-band texture procedure uses the distribution of neighboring grey tone N-tuple differences to measure the spatial interrelationships, or co-occurrences, of the grey tone N-tuples present in a texture pattern. In both procedures, texture is characterized in such a way as to be invariant under linear grey tone transformations. However, the cross-band procedure complements the single image procedure by extracting texture information and spectral information contained in ERTS multi-images. Classification experiments show that when used alone, without spectral processing, the cross-band texture procedure extracts more information than the single image texture analysis. Results show an improvement in average correct classification from 86.2% to 88.8% for ERTS image no. 1021-16333 with the cross-band texture procedure. However, when used together with spectral features, the single image texture plus spectral features perform better than the cross-band texture plus spectral features, with an average correct classification of 93.8% and 91.6%, respectively.