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Proceedings Paper

Automated simultaneous multiple feature classification of MTI data
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Paper Abstract

Los Alamos National Laboratory has developed and demonstrated a highly capable system, GENIE, for the two-class problem of detecting a single feature against a background of non-feature. In addition to the two-class case, however, a commonly encountered remote sensing task is the segmentation of multispectral image data into a larger number of distinct feature classes or land cover types. To this end we have extended our existing system to allow the simultaneous classification of multiple features/classes from multispectral data. The technique builds on previous work and its core continues to utilize a hybrid evolutionary-algorithm-based system capable of searching for image processing pipelines optimized for specific image feature extraction tasks. We describe the improvements made to the GENIE software to allow multiple-feature classification and describe the application of this system to the automatic simultaneous classification of multiple features from MTI image data. We show the application of the multiple-feature classification technique to the problem of classifying lava flows on Mauna Loa volcano, Hawaii, using MTI image data and compare the classification results with standard supervised multiple-feature classification techniques.

Paper Details

Date Published: 2 August 2002
PDF: 11 pages
Proc. SPIE 4725, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery VIII, (2 August 2002); doi: 10.1117/12.478767
Show Author Affiliations
Neal R. Harvey, Los Alamos National Lab. (United States)
James P. Theiler, Los Alamos National Lab. (United States)
Lee K. Balick, Los Alamos National Lab. (United States)
Paul A. Pope, Los Alamos National Lab. (United States)
John J. Szymanski, Los Alamos National Lab. (United States)
Simon J. Perkins, Los Alamos National Lab. (United States)
Reid B. Porter, Los Alamos National Lab. (United States)
Steven P. Brumby, Los Alamos National Lab. (United States)
Jeffrey J. Bloch, Los Alamos National Lab. (United States)
Nancy A. David, Los Alamos National Lab. (United States)
Mark C. Galassi, Los Alamos National Lab. (United States)


Published in SPIE Proceedings Vol. 4725:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery VIII
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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