傅立葉變換
dft = cv.dft(np.float32(img),flags = cv.DFT_COMPLEX_OUTPUT)
傅立葉逆變換
img_back = cv.idft(f_ishift)

實驗：將影象轉換到頻率域，低通濾波，將頻率域轉回到時域，顯示影象

import numpy as np
import cv2 as cv
from matplotlib import pyplot as plt

img = cv.imread('d:/paojie_g.jpg',0)
rows,cols = img.shape
crow,ccol = rows//2,cols//2

dft = cv.dft(np.float32(img),flags = cv.DFT_COMPLEX_OUTPUT)
dft_shift = np.fft.fftshift(dft)

# create a mask first,center square is 1,remaining all zeros
mask = np.zeros((rows,cols,2),np.uint8)
mask[crow-30:crow+31,ccol-30:ccol+31,:] = 1

# apply mask and inverse DFT
fshift = dft_shift*mask
f_ishift = np.fft.ifftshift(fshift)
img_back = cv.idft(f_ishift)
img_back = cv.magnitude(img_back[:,:,0],img_back[:,1])

plt.subplot(121),plt.imshow(img,cmap = 'gray')
plt.title('Input Image'),plt.xticks([]),plt.yticks([])
plt.subplot(122),plt.imshow(img_back,cmap = 'gray')
plt.title('Low Pass Filter'),plt.yticks([])
plt.show()