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Proceedings Paper

Temporal change enhancement in multispectral images remotely sensed from satellites
Author(s): Bill P. Pfaff; Doran Baker; Lloyd G. Allred; Gene Ware
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Paper Abstract

The application of principal components analysis (PCA) to multispectral satellite images is a routine way to present the data in false-color composite images. These composite images include a very high percentage of available information and have no correlation between the displayed colors. PCA routines are included in commercial GIS software, and custom algorithms are in wide use.This paper describes an early application of a new, genetic algorithm based, PCA routine. Landsat data for an Idaho farm were evaluated for temporal changes using this new algorithm, and the eigenvalues consistently converged with excellent results.

Paper Details

Date Published: 22 July 1997
PDF: 5 pages
Proc. SPIE 3074, Visual Information Processing VI, (22 July 1997); doi: 10.1117/12.280611
Show Author Affiliations
Bill P. Pfaff, Utah State Univ. (United States)
Doran Baker, Utah State Univ. (United States)
Lloyd G. Allred, Utah State Univ. (United States)
Gene Ware, Brigham Young Univ. (United States)


Published in SPIE Proceedings Vol. 3074:
Visual Information Processing VI
Stephen K. Park; Richard D. Juday, Editor(s)

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