Myujth

I am trying to implementing the inverse of Fourier transform. Here's my code:

import numpy as np 
import cv2 as cv
import math 
import cmath
from matplotlib import pyplot as plt
image="test2.bmp" 
img=cv.imread(image,cv.IMREAD_GRAYSCALE)
#foruior transform 
dft = cv.dft(np.float32(img),flags = cv.DFT_COMPLEX_OUTPUT)
#shifting for displaying 
dft_shift = np.fft.fftshift(dft)
#get the filter contains real and complex part 
t=1
a=0.1 
b=0.1
motion_filter=np.empty((img.shape[0],img.shape[1],2),dtype=np.complex_)
for x in range(img.shape[0]):
 for y in range(img.shape[1]):
 if x==0 and y==0:
 const1=math.pi*(1e-10)
 else:
 const1=math.pi*((x*a)+(y*b)) 
 #for real number
 motion_filter[x,y,0]=((t/const1)*(math.sin(const1))*(cmath.exp((0-1j)*(const1)))).real
 #for complex number
 motion_filter[x,y,1]=((t/const1)*(math.sin(const1))*(cmath.exp((0-1j)*(const1)))).imag
#processing
fshift = dft_shift*motion_filter
#shift back 
f_ishift = np.fft.ifftshift(fshift)
#inverse 
img_back = cv.idft(f_ishift)
#take real part 
img_back=img_back[:,:,0]
#show image 
plt.imshow(img_back,cmap='gray')
plt.show()

And the error occurs when doing:

img_back = cv.idft(f_ishift)

The error message is:

src data type = 15 is not supported

How can I fix the code?

According to the answer in this other question, the OpenCV idft requires a real-valued matrix where the real and imaginary components are stored along a third dimension. You create this matrix:

motion_filter=np.empty((img.shape[0],img.shape[1],2),dtype=np.complex_)

It is of the right sizes (2 along the 3rd dimension, for the real and imaginary components), but it is complex-valued. Next you multiply your Fourier-domain image (a real-valued matrix with real and imaginary components along the 3rd dimension) with this complex matrix, creating a complex-valued output:

fshift = dft_shift*motion_filter

This complex-valued output cannot be used in cv.idft. Instead, create your filter matrix as a real-valued matrix:

motion_filter=np.empty((img.shape[0],img.shape[1],2))