- Basic statistics: create table with mean, std dev, min, and max for each band
- Correlation matrix: show the correlation matrix for each pair of bands.
- Variance-covariance matrix: show this matrix for each pair of bands. The correlation matrix is computed from this matrix and is probably easier to interpret.
- Eigen vectors and PC loadings: shows the relative magnitude of each eigenvector, and the loadings on each vector of each variable.
- Principal component results: show the PC images.
- Load PC images
- Max PC bands: only this number of new grids will be created. Get a senses of the number of pick by looking at the eigen vectors. The 25 shown here only makes sense of hyperspectral imagery.
- Min explanation to show (%): the higher principal components typically only show noise, so you can limit the images to display by specifing the minimium amount of the variation a component must explain.