subspaceProject()
will basically give you a dimensionality reduction.
projection = (images[0] - mean) * evs
Subtracting the mean ensures that the images approximate a subspace. Presumably evs is the truncated right singular vectors.
and for subspaceReconstruct()
reconstruction = projection * transpose(evs) + mean
The reconstruction is just the reverse of the projection, except since evs is truncated, it can not be perfect.
See PCA