PCAImageFilter (and therefore the
DimensionalityReduction application), if whitening is not requested, each eigenvector is multiplied by the corresponding eigenvalue. This doesn't really makes sense and will often result in output images with very high variance for no reason. The whitening mode remains unchanged.
To summarize, if
E is the matrix of eigenvectors and
D the diagonal matrix of eigenvalues of the input data correlation matrix:
on the transformation will be
D^-1/2 * E^T
off will be
E^T (instead of
D * E^T)
A test is added for
PCAImageFilter with whitening set to false (this is currently not tested)
see bug report : #1998 (closed)
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Check before merging:
git diff develop... -U0 --no-color | clang-format-diff.py -p1 -i on latest changes and commit