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How to do phase correlation to estimate the geometrical shifts between two images?

Phase Correlation

In this notebook I will show how to use Fourier Transform to find the shifts between two misaligned images, then I will show how to use Bi-linear interpolation to align them.

In [1]:
import numpy as np
import matplotlib.pyplot as plt
import pyfits

Let's load a continuum image taken from the MURAM simulation of a plage region.

In [3]:
path = '/home/fatima/Desktop/solar_orbiter_project/codes/targets/distortion/'
sim = pyfits.getdata(path+'synth_continuum_profile.fits')
In [8]:
fig = plt.figure(figsize=(15,10))
<matplotlib.colorbar.Colorbar at 0x7f0d1a008bd0>

Let us introduce vertical and horizontal shifts.

In [42]:
def shift(x,y,del_x,del_y):
     x_s = x + del_x
     y_s = y + del_y
     return x_s, y_s
In [5]:
from scipy import interpolate
In [12]:
size = sim.shape[0]
x = y = np.arange(size)

F= interpolate.interp2d(x,y,sim, kind='linear')
In [15]:
shifted = np.zeros((size,size))
for j in range(size):
    for i in range(size):
      i_s, j_s = shift(i,j,10,3)
      shifted[j,i] = F(i_s,j_s) 
In [16]:
ax1 = fig.add_subplot(121)
ax2 = fig.add_subplot(122)
<matplotlib.image.AxesImage at 0x7f0d19b54790>