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    python用opencv 图像傅里叶变换

    作者:我坚信阳光灿烂 时间:2021-02-14 18:01

    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()

    js
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