python用opencv 图像傅里叶变换_Python

傅里叶变换
dft = cv.dft(np.float32(img),flags = cv.DFT_COMPLEX_OUTPUT)
傅里叶逆变换
img_back = cv.idft(f_ishift)

实验：将图像转换到频率域，低通滤波，将频率域转回到时域，显示图像

				?

									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()

python用opencv 图像傅里叶变换

原文链接：https://www.cnblogs.com/wojianxin/p/12684306.html

python用opencv 图像傅里叶变换

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