实验内容： LPF（低通滤波）将高频部分去除实现傅立叶变换.
# 实现低通滤波 import cv2 import numpy as np from matplotlib import pyplot as plt img = cv2.imread('test.png', 0) i = 70 f = np.fft.fft2(img) fshift = np.fft.fftshift(f) rows, cols = img.shape print(rows, cols) crow, ccol = int(rows/2), int(cols/2) # 需强制转换为整数 fshift[0:crow-i, 0:cols] = 0 fshift[crow+i:rows, 0:cols] = 0 fshift[crow-i:crow+i, 0:ccol-i] = 0 fshift[crow-i:crow+i, ccol+i:cols] = 0 f_ishift = np.fft.ifftshift(fshift) img_back = np.fft.ifft2(f_ishift) img_back = np.abs(img_back) plt.subplot(121), plt.imshow(img, cmap='gray'), plt.title('Original') plt.xticks([]), plt.yticks([]) plt.subplot(122), plt.imshow(img_back, cmap='gray'), plt.title('Image after LPF') plt.xticks([]), plt.yticks([]) plt.show()实验结果
