OpenCV中圖像頻率域濾波(傅里葉變換 + 高通/低通 濾波)[python]

資料來源: https://mp.weixin.qq.com/s/w2D2q5Ym7HnPWPP7VOWjJw

CV API 原型

# 傅里叶变换函数
void cv::dft(
    InputArray src,
    OutputArray dst,
    int flags = 0,
    int nonzeroRows = 0 
)

# 傅里叶逆变换函数
void cv::idft(
    InputArray src,
    OutputArray dst,
    int flags = 0,
    int nonzeroRows = 0 
)

低通

def low_pass_filter_demo():
    image = cv.imread("D:/images/test1.png", cv.IMREAD_GRAYSCALE)
    img_float32 = np.float32(image)

    rows, cols = image.shape
    crow, ccol = rows//2 , cols//2

    # FFT变换
    dft = cv.dft(img_float32, flags = cv.DFT_COMPLEX_OUTPUT)
    dft_shift = np.fft.fftshift(dft)

    # 创建低通滤波器，低频区域为 1， 高频区域为 0
    mask = np.zeros((rows, cols, 2), np.uint8)
    mask[crow-30:crow+30, ccol-30:ccol+30] = 1

    # 滤波
    fshift = dft_shift*mask

    # 逆变换
    f_ishift = np.fft.ifftshift(fshift)
    img_back = cv.idft(f_ishift)
    img_back = cv.magnitude(img_back[:,:,0],img_back[:,:,1])
    cv.normalize(img_back, img_back, 0, 1.0, cv.NORM_MINMAX)

    cv.imshow("input", image);
    cv.imshow("low-pass-filter", img_back)
    cv.imwrite("D:/low_pass.png", np.uint8(img_back*255))
    cv.waitKey(0)
    cv.destroyAllWindows()

高通

def high_pass_filter_demo():
    image = cv.imread("D:/images/test1.png", cv.IMREAD_GRAYSCALE)
    img_float32 = np.float32(image)

    rows, cols = image.shape
    crow, ccol = rows//2 , cols//2

    # FFT变换
    dft = cv.dft(img_float32, flags = cv.DFT_COMPLEX_OUTPUT)
    dft_shift = np.fft.fftshift(dft)

    # 创建高通滤波器，低频区域为 0， 高频区域为 1
    mask = np.ones((rows, cols, 2), np.uint8)
    mask[crow-30:crow+30, ccol-30:ccol+30] = 0

    # 滤波
    fshift = dft_shift*mask

    # 逆变换
    f_ishift = np.fft.ifftshift(fshift)
    img_back = cv.idft(f_ishift)
    img_back = cv.magnitude(img_back[:,:,0],img_back[:,:,1])
    cv.normalize(img_back, img_back, 0, 1.0, cv.NORM_MINMAX)

    cv.imshow("input", image);
    cv.imshow("high-pass-filter", img_back)
    cv.imwrite("D:/high_pass.png", np.uint8(img_back*255))
    cv.waitKey(0)
    cv.destroyAllWindows()