Principal component analysis
From AWF-Wiki
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= Using OTB standalone = | = Using OTB standalone = | ||
* Type into the search box of the Windows taskbar: {{typed|text=mapla.bat}}. Click on mapla.bat to open Monteverdi Application Launcher. | * Type into the search box of the Windows taskbar: {{typed|text=mapla.bat}}. Click on mapla.bat to open Monteverdi Application Launcher. | ||
− | * In the search engine of | + | * In the search engine of Mapla, type {{typed|text=Dimension}} and double click '''Dimensionality Reduction'''. |
* Specify a multispectral image as Input Image. | * Specify a multispectral image as Input Image. | ||
* Specify directory and name for the Output image. Select the output data type {{button|text=float}} from the pull-down list. | * Specify directory and name for the Output image. Select the output data type {{button|text=float}} from the pull-down list. |
Revision as of 13:57, 2 December 2018
Using QGIS OTB plugin
Does currently not work in OTB plugin for QGIS 3.4.
- 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.