cat = np.array(cat, dtype="f")
earth = np.array(earth, dtype="f")
# make sure we can combine these images directly
assert cat.shape == earth.shape
# take fourier transforms
ft_e = fft2(cat)
ft_m = fft2(earth)
# shift so hi-freq stuff is in the center
ft_e = fftshift(ft_e)
ft_m = fftshift(ft_m)
# use gaussian filter as a low pass filter
flo, _ = gaussian_filter(cat.shape, sigma=15)
# create a high pass filter
fhi = 1 - flo
# lowpass on earth, high-pass on cat
lo_e = ifft2(ifftshift(flo * ft_e))
hi_m = ifft2(ifftshift(fhi * ft_m))
# high pass on earth, low-pass on cat
lo_m = ifft2(ifftshift(flo * ft_m))
hi_e = ifft2(ifftshift(fhi * ft_e))
hybrid = lo_e + hi_m
hybrid_rev = lo_m + hi_e
einstein = np.array(einstein, dtype='f')
marilyn = np.array(marilyn, dtype='f')
# make sure we can combine these images directly
assert cat.shape == earth.shape
# take fourier transforms
ft_e = fft2(cat)
ft_m = fft2(earth)
# shift so hi-freq stuff is in the center
ft_e = fftshift(ft_e)
ft_m = fftshift(ft_m)
# use gaussian filter as a low pass filter
flo, _ = gaussian_filter(einstein.shape, sigma=10)
# create a high pass filter
fhi = 1 - flo
# lowpass on earth, high-pass on cat
lo_e = ifft2(ifftshift(flo * ft_e))
hi_m = ifft2(ifftshift(fhi * ft_m))
# high pass on earth, low-pass on cat
lo_m = ifft2(ifftshift(flo * ft_m))
hi_e = ifft2(ifftshift(fhi * ft_e))
# combine the lowpassed and highpassed images to produce the hybrid
hybrid = lo_e + hi_m
hybrid_rev = lo_m + hi_e
