Good question: this is what the denmatDecomp function is for. There is more detailed info about it on this page:
http://itensor.org/docs.cgi?page=classes/decomp
Basically its interface works the same way as the svd function but you have to provide a "dir" argument (either Fromleft or Fromright) which in SVD language says whether you want U or V (the other tensor will be set equal to either SV or US where S is the singular value matrix).
Internally, denmatDecomp squares the tensor you are decomposing and then calls a Hermitian diagonalization routine on it to get just U or just V. So it is more efficient than doing a full SVD.
Miles