  By forming measurement matrices with the Kronecker product of two random
matrices, image encryption in computational ghost imaging is investigated. The
two-dimensional images are conveniently reconstructed with the pseudo-inverse
matrices of the two random matrices. To suppress the noise, the method of
truncated singular value decomposition can be applied to either or both of the
two pseudo-inverse matrices. Further, our proposal facilitates for image
encryption since more matrices can be involved in forming the measurement
matrix. Two permutation matrices are inserted into the matrix sequence. The
image information can only be reconstructed with the correct permutation
matrices and the matrix sequence in image decryption. The experimental results
show the facilitations our proposal. The technique paves the way for the
practicality and flexibility of computational ghost imaging.
