一、numpy傅立叶变换和反变换
import cv2
import numpy as np
import matplotlib.pyplot as plt
img = cv2.imread('Set5/001_HR.png')
(r, g, b)=cv2.split(img)
img=cv2.merge([b,g,r])
f = np.fft.fft2(img)
fshift = np.fft.fftshift(f)
s1 = np.log(np.abs(fshift))
plt.subplot(221),plt.imshow(img),plt.title('original')
plt.xticks([]),plt.yticks([])
f1shift = np.fft.ifftshift(np.abs(fshift))
img_back = np.fft.ifft2(f1shift)
img_back = np.abs(img_back)
img_back = (img_back-np.amin(img_back))/(np.amax(img_back)-np.amin(img_back))
plt.subplot(222),plt.imshow(img_back,'gray'),plt.title('only Amplitude')
plt.xticks([]),plt.yticks([])
f2shift = np.fft.ifftshift(np.angle(fshift))
img_back = np.fft.ifft2(f2shift)
img_back = np.abs(img_back)
img_back = (img_back-np.amin(img_back))/(np.amax(img_back)-np.amin(img_back))
plt.subplot(223),plt.imshow(img_back,'gray'),plt.title('only phase')
plt.xticks([]),plt.yticks([])
s1 = np.abs(fshift)
s1_angle = np.angle(fshift)
s1_real = s1*np.cos(s1_angle)
s1_imag = s1*np.sin(s1_angle)
s2 = np.zeros(img.shape,dtype=complex)
s2.real = np.array(s1_real)
s2.imag = np.array(s1_imag)
f2shift = np.fft.ifftshift(s2)
img_back = np.fft.ifft2(f2shift)
img_back = np.abs(img_back)
img_back = (img_back-np.amin(img_back))/(np.amax(img_back)-np.amin(img_back))
plt.subplot(224),plt.imshow(img_back,'gray'),plt.title('another way')
plt.xticks([]),plt.yticks([])
plt.show()
二、tensorflow傅立叶变换示例：幅值和相位
import cv2
import numpy as np
import matplotlib.pyplot as plt
import tensorflow as tf
from skimage import measure
from skimage import img_as_ubyte
"""
img = cv2.imread('Set5/001_HR.png',0)
f = np.fft.fft2(img)
fshift = np.fft.fftshift(f)
s1 = np.log(np.abs(f))
s2 = np.log(np.abs(fshift))
plt.subplot(121),plt.imshow(s1,'gray'),plt.title('original')
sess = tf.InteractiveSession()
xs = tf.placeholder(dtype=tf.complex64,shape=(img.shape[0],img.shape[1]))
f1=tf.fft2d(xs)
f1_dis=f1.eval(feed_dict={xs:img})
f1shift = np.fft.fftshift(f1_dis)
ss1 = np.log(np.abs(f1_dis))
ss1 = np.float64(ss1)
plt.subplot(122),plt.imshow(ss1,'gray'),plt.title('fft_original')
plt.show()
"""
"""
Ihr = cv2.imread('Set5/003_HR.png',1)
Ilr = cv2.imread('Set5/003_EnhanceNet-PAT.png',1)
ph_out=[]
for i,img in enumerate([Ihr,Ilr]):
f = np.fft.fft2(img)
fshift = np.fft.fftshift(f)
ph_f = np.angle(f)
ph_out.append(ph_f)
ph_fshift = np.angle(fshift)
index='22'+ str(i+1)
plt.subplot(int(index)),plt.imshow(ph_f,'gray'),plt.title('original')
shape = Ihr.shape
sess = tf.InteractiveSession()
xs = tf.placeholder(dtype=tf.complex64, shape=([2, shape[1], shape[0], shape[2]]))
fhr = tf.fft2d(xs[0])
flr = tf.fft2d(xs[1])
ph_fhr = tf.cast(tf.angle(fhr),dtype=tf.float64)
ph_flr = tf.cast(tf.angle(flr),dtype=tf.float64)
ph_fhr, ph_flr = sess.run([ph_fhr,ph_flr],feed_dict={xs:[Ihr, Ilr]})
print ("MSE of ph_fhr and ph_out[0]:",measure.compare_mse(ph_fhr,ph_out[0]))
print ("MSE of ph_fhr and ph_flr:",measure.compare_mse(ph_fhr,ph_flr))
plt.show()
"""
"""
Ihr = cv2.imread('Set5/003_HR.png',1)
Ilr = cv2.imread('Set5/003_EnhanceNet-PAT.png',1)
nhr = np.fft.fft2(Ihr)
nlr = np.fft.fft2(Ilr)
amp_nhr = np.log(np.abs(nhr))
amp_nlr = np.log(np.abs(nlr))
shape = Ihr.shape
sess = tf.InteractiveSession()
xs = tf.placeholder(dtype=tf.complex64, shape=([2, shape[1], shape[0], shape[2]]))
fhr = tf.fft2d(xs[0])
flr = tf.fft2d(xs[1])
amp_fhr = tf.cast(tf.log(tf.abs(fhr)),dtype=tf.float64)
amp_flr = tf.cast(tf.log(tf.abs(flr)),dtype=tf.float64)
amp_fhr, amp_flr = sess.run([amp_fhr,amp_flr],feed_dict={xs:[Ihr, Ilr]})
print ("MSE of ph_fhr and ph_out[0]:",measure.compare_mse(amp_fhr,amp_flr))
"""
sess = tf.InteractiveSession()
theta0 = tf.atan2(1.0, 1.0) # pi/4
x0 = tf.constant(1.0)
y = tf.Variable(0.4)
c = tf.complex(x0, y)
c = tf.expand_dims(c,0)
c = tf.fft(c)
theta = tf.angle(c)
err = (theta - theta0)**2
optimize = tf.train.GradientDescentOptimizer(1e-1).minimize(err)
sess.run(tf.global_variables_initializer())
for i in range(10000):
sess.run(optimize)
if i % 10 == 0:
print(sess.run(c))
a=tf.constant(1e-8,tf.complex64,tf.shape())
三、numpy相位交换，幅值不变
import cv2
import numpy as np
import matplotlib.pyplot as plt
from skimage import measure
from skimage import img_as_ubyte
img_flower = cv2.imread('../../datasets/SuperResolution/EnhanceNet_Urban100/Urban100/039_HR.png',1)
img_man = cv2.imread('../../datasets/SuperResolution/EnhanceNet_Urban100/Urban100/039_EnhanceNet-E.png',1)
print ("PSNR of 0 and 1:",measure.compare_psnr(img_flower,img_man))
(r, g, b)=cv2.split(img_flower)
img_flower=cv2.merge([b,g,r])
(r, g, b)=cv2.split(img_man)
img_man=cv2.merge([b,g,r])
print ("PSNR of 0 and 1:",measure.compare_mse(img_flower,img_man))
plt.subplot(221),plt.imshow(img_flower,'gray'),plt.title('001_HR')
plt.xticks([]),plt.yticks([])
plt.subplot(222),plt.imshow(img_man,'gray'),plt.title('001_EnhanceNet-PAT')
plt.xticks([]),plt.yticks([])
f1 = np.fft.fft2(img_flower)
f1shift = np.fft.fftshift(f1)
f1_A = np.abs(f1shift)
f1_P = np.angle(f1shift)
f2 = np.fft.fft2(img_man)
f2shift = np.fft.fftshift(f2)
f2_A = np.abs(f2shift)
f2_P = np.angle(f2shift)
img_new1_f = np.zeros(img_flower.shape,dtype=complex)
img1_real = f1_A*np.cos(f2_P)
img1_imag = f1_A*np.sin(f2_P)
img_new1_f.real = np.array(img1_real)
img_new1_f.imag = np.array(img1_imag)
f3shift = np.fft.ifftshift(img_new1_f)
img_new1 = np.fft.ifft2(f3shift)
img_new1 = np.abs(img_new1)
img_new1 = (img_new1-np.amin(img_new1))/(np.amax(img_new1)-np.amin(img_new1))
plt.subplot(223),plt.imshow(img_new1,'gray'),plt.title('another way')
plt.xticks([]),plt.yticks([])
img_new2_f = np.zeros(img_flower.shape,dtype=complex)
img2_real = f2_A*np.cos(f1_P)
img2_imag = f2_A*np.sin(f1_P)
img_new2_f.real = np.array(img2_real)
img_new2_f.imag = np.array(img2_imag)
f4shift = np.fft.ifftshift(img_new2_f)
img_new2 = np.fft.ifft2(f4shift)
img_new2 = np.abs(img_new2)
img_new2 = (img_new2-np.amin(img_new2))/(np.amax(img_new2)-np.amin(img_new2))
plt.subplot(224),plt.imshow(img_as_ubyte(img_new2),'gray'),plt.title('another way')
plt.xticks([]),plt.yticks([])
plt._imsave("test.jpg",img_new2)
print ("PSNR of 0 and 4:",measure.compare_mse(img_flower,img_as_ubyte(img_new2)))
plt.show()
四、几个简单的画图函数：
import numpy as np
from PIL import Image
import matplotlib
import matplotlib.path as path
import matplotlib.pyplot as plt
import matplotlib.patches as patches
from matplotlib.ticker import MultipleLocator
fig = plt.figure(figsize=(8,6), dpi=72,facecolor="white")
axes = plt.subplot(211, aspect=1, axisbelow=True)
lena = np.array(Image.open("output/001_HR.png"))
im = plt.imshow(lena, origin = 'upper', interpolation='nearest')
axes.set_xticks([])
axes.set_yticks([])
axes = plt.axes([0.05,0.00,0.40,0.50], frameon=False)
patch1 = patches.Circle((.5,.5), radius=.45, transform=axes.transAxes,
linewidth=2, facecolor='none', edgecolor='black',zorder=2)
patch2 = patches.Circle((.5,.5), radius=.46, transform=axes.transAxes,
linewidth=2, facecolor='white', edgecolor='white',zorder=1)
im = plt.imshow(lena[215:315,285:385], origin = 'upper', zorder=3,
interpolation='nearest', clip_path=patch1)
axes.set_xticks([])
axes.set_yticks([])
axes.add_patch(patch1)
axes.add_patch(patch2)
plt.show()
import numpy as np
import matplotlib.pyplot as plt
img001_HR = plt.imread('output/001_HR.png',0)
img001_En = plt.imread('output/001_EnhanceNet-PAT.png',0)
img002_HR = plt.imread('output/002_HR.png',0)
img002_En = plt.imread('output/002_EnhanceNet-PAT.png',0)
img003_HR = plt.imread('output/003_HR.png',0)
img003_En = plt.imread('output/003_EnhanceNet-PAT.png',0)
img004_HR = plt.imread('output/004_HR.png',0)
img004_En = plt.imread('output/004_EnhanceNet-PAT.png',0)
img005_HR = plt.imread('output/001_HR.png',0)
img005_En = plt.imread('output/001_EnhanceNet-PAT.png',0)
plt.subplot(521),plt.imshow(img001_HR,'gray'),plt.title('img001_HR')
plt.subplot(522),plt.imshow(img001_En,'gray'),plt.title('img001_En')
plt.subplot(523),plt.imshow(img002_HR,'gray'),plt.title('img002_HR')
plt.subplot(524),plt.imshow(img002_En,'gray'),plt.title('img002_En')
plt.subplot(525),plt.imshow(img003_HR,'gray'),plt.title('img003_HR')
plt.subplot(526),plt.imshow(img003_En,'gray'),plt.title('img003_En')
plt.subplot(527),plt.imshow(img004_HR,'gray'),plt.title('img004_HR')
plt.subplot(528),plt.imshow(img004_En,'gray'),plt.title('img004_En')
"""
plt.subplot(529),plt.imshow(img005_HR,'gray'),plt.title('img005_HR')
#plt.subplot(5210),plt.imshow(img005_En,'gray'),plt.title('img005_En')
"""
plt.show()
