>>> image = lena().astype(Float32)
>>> derfilt = array([1.0,-2,1.0],Float32)
>>> ck = signal.cspline2d(image,8.0)
>>> deriv = signal.sepfir2d(ck, derfilt, [1]) + \
>>> signal.sepfir2d(ck, [1], derfilt)
>>>
>>> ## Alternatively we could have done:
>>> ## laplacian = array([[0,1,0],[1,-4,1],[0,1,0]],Float32)
>>> ## deriv2 = signal.convolve2d(ck,laplacian,mode='same',boundary='symm')
>>>
>>> xplt.imagesc(image[::-1]) # flip image so it looks right-side up.
>>> xplt.title('Original image')
>>> xplt.eps('lena_image')
>>> xplt.imagesc(deriv[::-1])
>>> xplt.title('Output of spline edge filter')
>>> xplt.eps('lena_edge')
