def mp_iuwt_recomposition(in1, scale_adjust, core_count, smoothed_array):
    """
    This function calls the a trous algorithm code to recompose the input into a single array. This is the
    implementation of the isotropic undecimated wavelet transform recomposition for multiple CPU cores.

    INPUTS:
    in1             (no default):   Array containing wavelet coefficients.
    scale_adjust    (no default):   Indicates the number of omitted array pages.
    core_count      (no default):   Indicates the number of cores to be used.
    smoothed_array  (default=None): For a complete inverse transform, this must be the smoothest approximation.

    OUTPUTS:
    recomposiiton                   Array containing the reconstructed image.
    """

    wavelet_filter = (1./16)*np.array([1,4,6,4,1])      # Filter-bank for use in the a trous algorithm.

    # Determines scale with adjustment and creates a zero array to store the output, unless smoothed_array is given.

    max_scale = in1.shape[0] + scale_adjust

    if smoothed_array is None:
        recomposition = np.zeros([in1.shape[1], in1.shape[2]])
    else:
        recomposition = smoothed_array

    # The following loops call the a trous algorithm code to recompose the input. The first loop assumes that there are
    # non-zero wavelet coefficients at scales above scale_adjust, while the second loop completes the recomposition
    # on the scales less than scale_adjust.

    for i in range(max_scale-1, scale_adjust-1, -1):
        recomposition = mp_a_trous(recomposition, wavelet_filter, i, core_count) + in1[i-scale_adjust,:,:]

    if scale_adjust>0:
        for i in range(scale_adjust-1, -1, -1):
            recomposition = mp_a_trous(recomposition, wavelet_filter, i, core_count)

    return recomposition
This function calls the a trous algorithm code to recompose the input into a single array. This is the
    implementation of the isotropic undecimated wavelet transform recomposition for multiple CPU cores.

    INPUTS:
    in1             (no default):   Array containing wavelet coefficients.
    scale_adjust    (no default):   Indicates the number of omitted array pages.
    core_count      (no default):   Indicates the number of cores to be used.
    smoothed_array  (default=None): For a complete inverse transform, this must be the smoothest approximation.

    OUTPUTS:
    recomposiiton                   Array containing the reconstructed image.