We present a practical and efficient means to compute the singular value
decomposition (svd) of a quaternion matrix A based on bidiagonalization of A to
a real bidiagonal matrix B using quaternionic Householder transformations.
Computation of the svd of B using an existing subroutine library such as lapack
provides the singular values of A. The singular vectors of A are obtained
trivially from the product of the Householder transformations and the real
singular vectors of B. We show in the paper that left and right quaternionic
Householder transformations are different because of the noncommutative
multiplication of quaternions and we present formulae for computing the
Householder vector and matrix in each case