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Automated Image Registration (AIR) of MTI Imagery

Description: This paper describes an algorithm for the registration of imagery collected by the Multispectral Thermal Imager (MTI). The Automated Image Registration (AIR) algorithm is entirely image-based and is implemented in an automated fashion, which avoids any requirement for human interaction. The AIR method differs from the 'direct georeferencing' method used to create our standard coregistered product since explicit information about the satellite's trajectory and the sensor geometry are not required. The AIR method makes use of a maximum cross-correlation (MCC) algorithm, which is applied locally about numerous points within any two images being compared. The MCC method is used to determine the row and column translations required to register the bands of imagery collected by a single SCA (band-to-band registration), and the raw and column translations required to regisler the imagery collected by the three SCAs for any individual band (SCA-to-SCA registration). Of particular note is the use of reciprocity and a weighted least squares approach to obtaining the band-to-band registration shifts. Reciprocity is enforced by using the MCC method to determine the row and column translations between all pair-wise combinations of bands. This information is then used in a weighted least squares approach to determine the optimum shift values between an arbitrarily selected reference band and the other 15 bands. The individual steps of the AIR methodology, and the results of registering MTI imagery through use of this algorithm, are described.
Date: January 1, 2003
Creator: Pope, P. A. (Paul A.) & Theiler, J. P. (James P.)
Partner: UNT Libraries Government Documents Department

Image processing technology

Description: This is the final report of a two-year, Laboratory-Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). The primary objective of this project was to advance image processing and visualization technologies for environmental characterization. This was effected by developing and implementing analyses of remote sensing data from satellite and airborne platforms, and demonstrating their effectiveness in visualization of environmental problems. Many sources of information were integrated as appropriate using geographic information systems.
Date: July 1, 1996
Creator: Van Eeckhout, E.; Pope, P. & Balick, L.
Partner: UNT Libraries Government Documents Department

Waste site characterization through digital analysis of historical aerial photographs at Los Alamos National Laboratory and Eglin Air Force Base

Description: Historical aerial photographs are used to provide a physical history and preliminary mapping information for characterizing hazardous waste sites at Los Alamos National Laboratory and Eglin Air Force Base. The examples cited show how imagery was used to accurately locate and identify previous activities at a site, monitor changes that occurred over time, and document the observable of such activities today. The methodology demonstrates how historical imagery (along with any other pertinent data) can be used in the characterization of past environmental damage.
Date: May 1, 1995
Creator: Van Eeckhout, E.; Pope, P.; Wells, B.; Rofer, C. & Martin, B.
Partner: UNT Libraries Government Documents Department

Environmental waste site characterization utilizing aerial photographs and satellite imagery: Three sites in New Mexico, USA

Description: The proper handling and characterization of past hazardous waste sites is becoming more and more important as world population extends into areas previously deemed undesirable. Historical photographs, past records, current aerial satellite imagery can play an important role in characterizing these sites. These data provide clear insight into defining problem areas which can be surface samples for further detail. Three such areas are discussed in this paper: (1) nuclear wastes buried in trenches at Los Alamos National Laboratory, (2) surface dumping at one site at Los Alamos National Laboratory, and (3) the historical development of a municipal landfill near Las Cruces, New Mexico.
Date: April 1, 1996
Creator: Van Eeckhout, E.; Pope, P.; Becker, N.; Wells, B.; Lewis, A. & David, N.
Partner: UNT Libraries Government Documents Department

Environmental management policy analysis using complex system simulation

Description: The two primary modules of Envirosim (the model of Los Alamos TA-55 and the WIPP transport/storage model) have been combined into one application, with the simulated waste generated by TA-55 operations being fed to storage, packaging, and transport simulation entities. Three simulation scenarios were executed which demonstrate the usefulness of Envirosim as a policy analysis tool for use in planning shipments to WIPP. A graphical user interface (GUI) has been implemented using IDL (Interactive Data Language) which allows the analyst to easily view simulation results. While IDL is not necessarily the graphics interface that would be selected for a production version of Envirosim, it does provide some powerful data manipulation capabilities, and it runs on a variety of platforms.
Date: April 1, 1999
Creator: Van Eeckhout, E.; Roberts, D.; Oakes, R.; Shieh, A.; Hardie, W. & Pope, P.
Partner: UNT Libraries Government Documents Department

Environmental waste site characterization utilizing aerial photographs, remote sensing, and surface geophysics

Description: Six different techniques were used to delineate 40 year old trench boundary at Los Alamos National Laboratory. Data from historical aerial photographs, a magnetic gradient survey, airborne multispectral and thermal infra-red imagery, seismic refraction, DC resistivity, and total field magnetometry were utilized in this process. Each data set indicated a southern and northern edge for the trench. Average locations and 95% confidence limits for each edge were determined along a survey line perpendicular to the trench. Trench edge locations were fairly consistent among all six techniques. Results from a modeling effort performed with the total magnetic field data was the least consistent. However, each method provided unique and complementary information, and the integration of all this information led to a more complete characterization of the trench boundaries and contents.
Date: April 18, 1996
Creator: Pope, P.; Van Eeckhout, E.; Rofer, C.; Baldridge, S.; Ferguson, J.; Jiracek, G. et al.
Partner: UNT Libraries Government Documents Department

Automated coregistration of MTI spectral bands.

Description: In the focal plane of a pushbroom imager, a linear array of pixels is scanned across the scene, building up the image one row at a time. For the Multispectral Thermal Imager (MTI), each of fifteen different spectral bands has its own linear array. These arrays are pushed across the scene together, but since each band's array is at a different position on the focal plane, a separate image is produced for each band. The standard MTI data products resample these separate images to a common grid and produce coregistered multispectral image cubes. The coregistration software employs a direct 'dead reckoning' approach. Every pixel in the calibrated image is mapped to an absolute position on the surface of the earth, and these are resampled to produce an undistorted coregistered image of the scene. To do this requires extensive information regarding the satellite position and pointing as a function of time, the precise configuration of the focal plane, and the distortion due to the optics. These must be combined with knowledge about the position and altitude of the target on the rotating ellipsoidal earth. We will discuss the direct approach to MTI coregistration, as well as more recent attempts to 'tweak' the precision of the band-to-band registration using correlations in the imagery itself.
Date: January 1, 2002
Creator: Theiler, J. P. (James P.); Galbraith, A. E. (Amy E.); Pope, P. A. (Paul A.); Ramsey, K. A. (Keri A.) & Szymanski, J. J. (John J.)
Partner: UNT Libraries Government Documents Department

Feature extraction from multiple data sources using genetic programming.

Description: Feature extration from imagery is an important and long-standing problem in remote sensing. In this paper, we report on work using genetic programming to perform feature extraction simultaneously from multispectral and digital elevation model (DEM) data. The tool used is the GENetic Imagery Exploitation (GENIE) software, which produces image-processing software that inherently combines spatial and spectral processing. GENIE is particularly useful in exploratory studies of imagery, such as one often does in combining data from multiple sources. The user trains the software by painting the feature of interest with a simple graphical user interface. GENIE then uses genetic programming techniques to produce an image-processing pipeline. Here, we demonstrate evolution of image processing algorithms that extract a range of land-cover features including towns, grasslands, wild fire burn scars, and several types of forest. We use imagery from the DOE/NNSA Multispectral Thermal Imager (MTI) spacecraft, fused with USGS 1:24000 scale DEM data.
Date: January 1, 2002
Creator: Szymanski, J. J. (John J.); Brumby, Steven P.; Pope, P. A. (Paul A.); Eads, D. R. (Damian R.); Galassi, M. C. (Mark C.); Harvey, N. R. (Neal R.) et al.
Partner: UNT Libraries Government Documents Department