Principal Component Analysis

Command: Image Analysis > Principal Component Analysis

ImageLab supports the calculation of principal components of the hyperspectral images. The scores of the PCA are displayed both as score/score plot and as a score image. In order to perform the PCA you have first to load the spectral descriptors, select the scaling mode of the data and optionally load a pixel mask. After clicking the "Calculate" button, the results of the PCA are displayed on several tabsheets.

Pixels in the score/score plot can be easily related to the score image by interactively marking the pixels. In order to mark the pixels of a region you have first to activate the "mark data" button . Then you can simply draw a lasso line around the area to be marked. The marked pixels will then be highlighted in red color in both the score/score plot and the score image.


How To: Please follow these steps to perform a principal component analysis:
  1. Select a list of descriptors which should form the basis of the analysis
  2. Select the scaling mode of the data.
  3. Optionally select a pixel mask if you want to exclude particular regions of the image from the PCA
  4. Click the "Calculate" button.

Last Update: 2015-Dez-09