numpy 傅里叶变换与反变换高低通滤波与带通滤波

#coding=utf-8

import cv2
import numpy as np
import matplotlib.pyplot as plt

img=cv2.imread('test1-angle.jpg',cv2.IMREAD_GRAYSCALE)
# f = np.fft.fft2(img)
# fshift = np.fft.fftshift(f)
# #取绝对值：将复数变化成实数
# #取对数的目的为了将数据变化到较小的范围（比如0-255）
# s1 = np.log(np.abs(f))
# s2 = np.log(np.abs(fshift))
# print(np.shape(s1))
# print(s1[0:20,0:20])
# cv2.imshow('s1',np.array(s1,dtype=int))
# cv2.imshow('s2',s2)
# cv2.waitKey()
# plt.subplot(321),plt.imshow(s1,'gray'),plt.title('original')
# plt.subplot(322),plt.imshow(s2,'gray'),plt.title('center')
# ph_f = np.angle(f)
# ph_fshift = np.angle(fshift)
# # print(ph_f)
# # print(ph_fshift)
# plt.subplot(323),plt.imshow(ph_f,'gray'),plt.title('original')
# plt.subplot(324),plt.imshow(ph_fshift,'gray'),plt.title('center')
#
# # 逆变换
# f1shift = np.fft.ifftshift(fshift)
# img_back = np.fft.ifft2(f1shift)
# # 出来的是复数，无法显示
# img_back = np.abs(img_back)
# plt.subplot(325), plt.imshow(img_back, 'gray'), plt.title('img back')
# plt.show()

plt.subplot(121),plt.imshow(img,'gray'),plt.title('origial')
plt.xticks([]),plt.yticks([])
#--------------------------------
rows,cols = img.shape
# mask = np.ones(img.shape,np.uint8)
# mask[rows/2-30:rows/2+30,cols/2-30:cols/2+30] = 0 #高通滤波
# mask = np.zeros(img.shape,np.uint8)
# mask[rows/2-80:rows/2+80,cols/2-80:cols/2+80] = 1 #低通滤波
#--------------------------------
#--------------------------------理想的带通滤波器
rows,cols = img.shape
mask1 = np.ones(img.shape,np.uint8)
mask1[rows/2-8:rows/2+8,cols/2-8:cols/2+8] = 0
mask2 = np.zeros(img.shape,np.uint8)
mask2[rows/2-80:rows/2+80,cols/2-80:cols/2+80] = 1
mask = mask1*mask2
#--------------------------------
f1 = np.fft.fft2(img)
f1shift = np.fft.fftshift(f1)
f1shift = f1shift*mask
f2shift = np.fft.ifftshift(f1shift) #对新的进行逆变换
img_new = np.fft.ifft2(f2shift)
#出来的是复数，无法显示
img_new = np.abs(img_new)
#调整大小范围便于显示
img_new = 255-(img_new-np.amin(img_new))/(np.amax(img_new)-np.amin(img_new))
plt.subplot(122),plt.imshow(img_new,'gray'),plt.title('Highpass')
plt.xticks([]),plt.yticks([])
plt.show()