Temporal change enhancement in multispectral images remotely sensed from satellites

Bill P. Pfaff; Doran Baker; Lloyd G. Allred; Gene Ware

doi:10.1117/12.280611

22 July 1997 Temporal change enhancement in multispectral images remotely sensed from satellites

Bill P. Pfaff, Doran Baker, Lloyd G. Allred, Gene Ware

Proceedings Volume 3074, Visual Information Processing VI; (1997) https://doi.org/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.

Citation Download Citation

Bill P. Pfaff, Doran Baker, Lloyd G. Allred, and Gene Ware "Temporal change enhancement in multispectral images remotely sensed from satellites", Proc. SPIE 3074, Visual Information Processing VI, (22 July 1997); https://doi.org/10.1117/12.280611

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