import numpy as np
from skimage import img_as_float
import matplotlib.pyplot as plt
from skimage import io
import math
import numpy.matlib
file_name2='C:/Users/xpp/Desktop/Lena.png'
img=io.imread(file_name2)
img=img_as_float(img)
row,col,channel=img.shape
img_out=img*1.0
R=(min(row,col)/2)
gamma=0.00001
center_x=(col-1)/2.0
center_y=(row-1)/2.0
xx=np.arange (col)
yy=np.arange (row)
x_mask=numpy.matlib.repmat(xx,row,1)
y_mask=numpy.matlib.repmat(yy,col,1)
y_mask=np.transpose(y_mask)
xx_dif=x_mask-center_x
yy_dif=center_y-y_mask
r=np.sqrt(xx_dif*xx_dif yy_dif*yy_dif)
theta= np.arctan(yy_dif/xx_dif)
mask_1=xx_dif<0
theta=theta*(1-mask_1) (theta math.pi)*mask_1
r_new=R*np.power(r/R,gamma)
x_new=r_new*np.cos(theta) center_x
y_new=center_y-r_new*np.sin(theta)
int_x=np.floor(x_new)
int_x=int_x.astype(int)
int_y=np.floor(y_new)
int_y=int_y.astype(int)
for ii in range(row):
for jj in range (col):
new_xx=int_x [ii,jj]
new_yy=int_y [ii,jj]
if x_new [ii,jj]<0 or x_new [ii,jj]>col-1 :
continue
if y_new [ii,jj]<0 or y_new [ii,jj]>row-1 :
continue
img_out[ii,jj,:]=img[new_yy,new_xx,:]
plt.figure(1)
plt.title('original')
plt.imshow(img)
plt.axis('off')
plt.figure(2)
plt.title('result')
plt.imshow(img_out)
plt.axis('off')
plt.show()
算法：图像凹凸形变是 PS 滤镜中的一种几何变换– Fish lens，像通过凸镜或凹镜观察图像。
