22 July 1997 Temporal change enhancement in multispectral images remotely sensed from satellites
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Proceedings Volume 3074, Visual Information Processing VI; (1997); doi: 10.1117/12.280611
Event: AeroSense '97, 1997, Orlando, FL, United States
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.
© (1997) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Bill P. Pfaff, Doran Baker, Lloyd G. Allred, Gene Ware, "Temporal change enhancement in multispectral images remotely sensed from satellites", Proc. SPIE 3074, Visual Information Processing VI, (22 July 1997); doi: 10.1117/12.280611; https://doi.org/10.1117/12.280611
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KEYWORDS
Principal component analysis

Genetic algorithms

Earth observing sensors

Satellites

Composites

Multispectral imaging

Satellite imaging

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