低通滤波与高通滤波

概念

代码

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

img = cv2.imread('face.png',0)

img_float32 = np.float32(img)

dft = cv2.dft(img_float32,flags = cv2.DFT_COMPLEX_OUTPUT)
dft_shift = np.fft.fftshift(dft)

rows,cols = img.shape
crow,ccol = int(rows/2),int(cols/2)        #中心位置
'''
#低通滤波
mask = np.zeros((rows,cols,2),np.uint8)
mask[crow-30:crow+30,ccol-30:ccol+30] = 1
'''
#高通滤波
mask = np.ones((rows,cols,2),np.uint8)
mask[crow-30:crow+30,ccol-30:ccol+30] = 0


#IDFT
fshift = dft_shift*mask
f_ishift = np.fft.ifftshift(fshift)
img_back = cv2.idft(f_ishift)
img_back = cv2.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('Result'),plt.xticks([]),plt.yticks([])
plt.show()

低通滤波