python用opencv 圖像傅裡葉變換
傅裡葉變換
dft = cv.dft(np.float32(img),flags = cv.DFT_COMPLEX_OUTPUT)
傅裡葉逆變換
img_back = cv.idft(f_ishift)
實驗:將圖像轉換到頻率域,低通濾波,將頻率域轉回到時域,顯示圖像
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.xticks([]), plt.yticks([]) plt.show()
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