wave_transform.py 文件源码

def iuwt_1D(wave):
    """
    Inverse Starlet transform.
    INPUTS:
        wave: wavelet decomposition of an image.
    OUTPUTS:
        out: image reconstructed from wavelet coefficients
    OPTIONS:
        convol2d:  if set, a 2D version of the filter is used (slower, default is 0)

    """
    mode = 'nearest'

    lvl,n1= np.shape(wave)
    h = np.array([1./16, 1./4, 3./8, 1./4, 1./16])
    n = np.size(h)

    cJ = np.copy(wave[lvl-1,:])


    for i in np.linspace(1,lvl-1,lvl-1):

        newh = np.zeros((1,n+(n-1)*(2**(lvl-1-i)-1)))
        newh[0,np.int_(np.linspace(0,np.size(newh)-1,len(h)))] = h
        H = np.dot(newh.T,newh)

        ###### Line convolution

        cnew = sc.convolve1d(cJ,newh[0,:],axis = 0, mode = mode)
        cJ = cnew+wave[lvl-1-i,:]

    out = cJ
    return out