OpenCV中的逆傅立叶变换

X(u) = 1/N * sum(x(n) * e^(-2*pi*i*n*u/N))

import cv2
import numpy as np

# 加载图像
img = cv2.imread('image.jpg', cv2.IMREAD_GRAYSCALE)

# 将图像填充为偶数尺寸
rows, cols = img.shape
if rows % 2 != 0:
    img = cv2.copyMakeBorder(img, 0, 1, 0, 0, cv2.BORDER_REPLICATE)
if cols % 2 != 0:
    img = cv2.copyMakeBorder(img, 0, 0, 0, 1, cv2.BORDER_REPLICATE)

# 快速傅立叶变换
dft = cv2.dft(np.float32(img), flags=cv2.DFT_COMPLEX_OUTPUT)

# 计算逆傅立叶变换
idft = cv2.dft(dft, flags=cv2.DFT_INVERSE | cv2.DFT_SCALE, nonzeroRows=rows // 2)

# 显示原始图像和逆傅立叶变换后的图像
cv2.imshow('Original Image', img)
cv2.imshow('IDFT Image', np.abs(idft))

cv2.waitKey(0)
cv2.destroyAllWindows()