Principal component analysis
From AWF-Wiki
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= Using QGIS OTB plugin = | = Using QGIS OTB plugin = | ||
| − | + | * In the search engine of the Processing Toolbox, type {{typed|text=dimension}} and select '''DimensionalityReduction''' under Image Filtering of the Orfeo Toolbox. | |
| − | * In the search engine of the Processing Toolbox, type | + | |
* Under the Parameter tab, select Multispectral band file as the input layer. | * Under the Parameter tab, select Multispectral band file as the input layer. | ||
* Select '''pca''' under the Algorithm tab. | * Select '''pca''' under the Algorithm tab. | ||
* Enter 4 as the number of components. | * Enter 4 as the number of components. | ||
| − | * | + | * Under Inverse Output Image [optional] untick Open output file after running algorithm (See Screenshot below). |
| − | + | ||
* Click on {{button|text=Run}} to execute the algorithm. | * Click on {{button|text=Run}} to execute the algorithm. | ||
| + | [[File:qgis_otb_pca.png|400px]] | ||
= 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 | + | * Type into the search box of the Windows taskbar: {{typed|text=mapla.bat}} or navigate to C:\opt\OTB-7.2.0-Win64\mapla.bat in your Windows explorer. Click on mapla.bat to open Monteverdi Application Launcher. |
| − | * In the search engine of | + | * In the search engine of Mapla, type {{typed|text=Dimension}} under Image Filtering 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= | + | * Specify directory and name for the Output image. Select the output data type {{button|text=float}} from the pull-down list. |
| − | + | ||
* Select '''PCA''' from the drop-down list as Algorithm. | * Select '''PCA''' from the drop-down list as Algorithm. | ||
* Enter 4 as number of components. | * Enter 4 as number of components. | ||
| − | |||
* Click on {{button|text=Execute}}. | * Click on {{button|text=Execute}}. | ||
| − | [[File:pca_otb.png| | + | [[File:pca_otb.png|500px]][[File:pca_result.png|400px]] |
[[category:QGIS Tutorial]] | [[category:QGIS Tutorial]] | ||
Latest revision as of 21:12, 29 November 2020
[edit] Using QGIS OTB plugin
- In the search engine of the Processing Toolbox, type dimension and select DimensionalityReduction 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.
- Under Inverse Output Image [optional] untick Open output file after running algorithm (See Screenshot below).
- Click on Run to execute the algorithm.
[edit] Using OTB standalone
- Type into the search box of the Windows taskbar: mapla.bat or navigate to C:\opt\OTB-7.2.0-Win64\mapla.bat in your Windows explorer. Click on mapla.bat to open Monteverdi Application Launcher.
- In the search engine of Mapla, type Dimension under Image Filtering 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.
