  The article presents a computationally effective algorithm for calculating
the multiresolution discrete Fourier transform (MrDFT). The algorithm is based
on the idea of reducing the computational complexity which was introduced by
Wen and Sandler [10] and utilizes the vectorization of calculating process at
each stage of the considered transformation. This allows for the use of a
computational process parallelization and results in a reduction of computation
time. In the description of the computational procedure, which describes the
algorithm, we use the matrix notation. This notation enables to represent
adequately the space-time structures of the implemented computational process
and directly map these structures into the constructions of a high-level
programming language or into a hardware realization space.
