计算 Python 中图像的 fft2

Question

I am experimenting with Fourier transformations and the built-in NumPy.fft library. I was trying to see the difference between computing just fft2 of an image and fftshift on fft2 of an image. But for some reason, I am not getting the results that I was expecting. I have tried changing images as well but regardless of what I use, I get the same results as below. If someone could help me out here, it would be awesome. This is the code I used:

import numpy as np
import cv2
import matplotlib.pyplot as plt
from scipy import ndimage, fftpack

light = cv2.imread("go_light.jpeg")
dark = cv2.imread("go_dark.jpeg")

g_img = cv2.cvtColor(dark, cv2.COLOR_BGR2GRAY)
di = (np.abs((np.fft.fft2(g_img))))
dm = np.abs(np.fft.fftshift(np.fft.fft2(g_img)))


plt.figure(figsize=(6.4*5, 4.8*5), constrained_layout=False)
plt.subplot(151), plt.imshow(di, "gray"), plt.title("fft");
plt.subplot(152), plt.imshow(dm, "gray"), plt.title("fftshift");
plt.show()

Answer 1

di and dm are floating point values. Matplotlib can't do that. First, try di.astype(np.int8) . However, many of the values are out of range. You may need to scale the array.