Principal component analysis

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Revision as of 13:27, 10 January 2019 by Hfuchs (Talk | contribs)

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Using QGIS OTB plugin

  • In the search engine of the Processing Toolbox, type PCA and select DimensionalityReduction(pca) under Image Filtering of the Orfeo Toolbox.
  • Under the Parameter tab, select Multispectral band file as the input layer.
  • Select pca under the Algorithm tab.
  • Enter 4 as the number of components.
  • Specify the directory to save the output file.
  • Untick output file after running algorithm (inverse output image) option.
  • Click on Run to execute the algorithm.

Using OTB standalone

  • Type into the search box of the Windows taskbar: mapla.bat. Click on mapla.bat to open Monteverdi Application Launcher.
  • In the search engine of Mapla, type Dimension and double click Dimensionality Reduction.
  • Specify a multispectral image as Input Image.
  • Specify directory and name for the Output image. Select the output data type float from the pull-down list.
  • Select PCA from the drop-down list as Algorithm.
  • Enter 4 as number of components.
  • Click on Execute.

Pca otb.pngPca result.png

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