Inverse of Fourier transform gives “data type not supported” error
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?
python opencv image-processing fft opencv3.0
edited Nov 13 '18 at 16:30
Cris Luengo
19.8k52249
asked Nov 13 '18 at 13:15
kriskris
345
add a comment |
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?
python opencv image-processing fft opencv3.0
edited Nov 13 '18 at 16:30
Cris Luengo
19.8k52249
asked Nov 13 '18 at 13:15
kriskris
345
2
Did you try to search on SO before posting the question? Exact (not possible) Duplicate: stackoverflow.com/questions/30989915/…
– Rick M.
Nov 13 '18 at 13:48
Not working . I tried before
– kris
Nov 13 '18 at 13:53
Possible duplicate of TypeError: src data type = 15 is not supported
– n00dle
Nov 13 '18 at 16:02
add a comment |
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?
python opencv image-processing fft opencv3.0
edited Nov 13 '18 at 16:30
Cris Luengo
19.8k52249
asked Nov 13 '18 at 13:15
kriskris
345
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?
python opencv image-processing fft opencv3.0
python opencv image-processing fft opencv3.0
edited Nov 13 '18 at 16:30
Cris Luengo
19.8k52249
asked Nov 13 '18 at 13:15
kriskris
345
edited Nov 13 '18 at 16:30
Cris Luengo
19.8k52249
asked Nov 13 '18 at 13:15
kriskris
345
edited Nov 13 '18 at 16:30
Cris Luengo
19.8k52249
edited Nov 13 '18 at 16:30
Cris Luengo
19.8k52249
edited Nov 13 '18 at 16:30
Cris Luengo
19.8k52249
19.8k52249
asked Nov 13 '18 at 13:15
kriskris
345
asked Nov 13 '18 at 13:15
kriskris
345
asked Nov 13 '18 at 13:15
kriskris
345
345
2
Did you try to search on SO before posting the question? Exact (not possible) Duplicate: stackoverflow.com/questions/30989915/…
– Rick M.
Nov 13 '18 at 13:48
Not working . I tried before
– kris
Nov 13 '18 at 13:53
Possible duplicate of TypeError: src data type = 15 is not supported
– n00dle
Nov 13 '18 at 16:02
add a comment |
2
Did you try to search on SO before posting the question? Exact (not possible) Duplicate: stackoverflow.com/questions/30989915/…
– Rick M.
Nov 13 '18 at 13:48
Not working . I tried before
– kris
Nov 13 '18 at 13:53
Possible duplicate of TypeError: src data type = 15 is not supported
– n00dle
Nov 13 '18 at 16:02
2
2
Did you try to search on SO before posting the question? Exact (not possible) Duplicate: stackoverflow.com/questions/30989915/…
– Rick M.
Nov 13 '18 at 13:48
Did you try to search on SO before posting the question? Exact (not possible) Duplicate: stackoverflow.com/questions/30989915/…
– Rick M.
Nov 13 '18 at 13:48
Not working . I tried before
– kris
Nov 13 '18 at 13:53
Not working . I tried before
– kris
Nov 13 '18 at 13:53
Possible duplicate of TypeError: src data type = 15 is not supported
– n00dle
Nov 13 '18 at 16:02
Possible duplicate of TypeError: src data type = 15 is not supported
– n00dle
Nov 13 '18 at 16:02
add a comment |
1 Answer
1
active
oldest
votes
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))
answered Nov 13 '18 at 16:29
Cris LuengoCris Luengo
19.8k52249
Am I doing the correct way to store the real part and complex part for kernel?
– kris
Nov 14 '18 at 4:21
@kris: Looks correct to me, but I haven't tried running your code. But you are computing that complex value twice, which is not efficient.
– Cris Luengo
Nov 14 '18 at 4:42
Okay I’ll post an example later, I tried this but not working out....
– kris
Nov 14 '18 at 6:42
add a comment |
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1 Answer
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1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
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))
answered Nov 13 '18 at 16:29
Cris LuengoCris Luengo
19.8k52249
Am I doing the correct way to store the real part and complex part for kernel?
– kris
Nov 14 '18 at 4:21
@kris: Looks correct to me, but I haven't tried running your code. But you are computing that complex value twice, which is not efficient.
– Cris Luengo
Nov 14 '18 at 4:42
Okay I’ll post an example later, I tried this but not working out....
– kris
Nov 14 '18 at 6:42
add a comment |
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))
answered Nov 13 '18 at 16:29
Cris LuengoCris Luengo
19.8k52249
Am I doing the correct way to store the real part and complex part for kernel?
– kris
Nov 14 '18 at 4:21
@kris: Looks correct to me, but I haven't tried running your code. But you are computing that complex value twice, which is not efficient.
– Cris Luengo
Nov 14 '18 at 4:42
Okay I’ll post an example later, I tried this but not working out....
– kris
Nov 14 '18 at 6:42
add a comment |
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))
answered Nov 13 '18 at 16:29
Cris LuengoCris Luengo
19.8k52249
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))
answered Nov 13 '18 at 16:29
Cris LuengoCris Luengo
19.8k52249
answered Nov 13 '18 at 16:29
Cris LuengoCris Luengo
19.8k52249
answered Nov 13 '18 at 16:29
Cris LuengoCris Luengo
19.8k52249
answered Nov 13 '18 at 16:29
Cris LuengoCris Luengo
19.8k52249
19.8k52249
Am I doing the correct way to store the real part and complex part for kernel?
– kris
Nov 14 '18 at 4:21
@kris: Looks correct to me, but I haven't tried running your code. But you are computing that complex value twice, which is not efficient.
– Cris Luengo
Nov 14 '18 at 4:42
Okay I’ll post an example later, I tried this but not working out....
– kris
Nov 14 '18 at 6:42
add a comment |
Am I doing the correct way to store the real part and complex part for kernel?
– kris
Nov 14 '18 at 4:21
@kris: Looks correct to me, but I haven't tried running your code. But you are computing that complex value twice, which is not efficient.
– Cris Luengo
Nov 14 '18 at 4:42
Okay I’ll post an example later, I tried this but not working out....
– kris
Nov 14 '18 at 6:42
Am I doing the correct way to store the real part and complex part for kernel?
– kris
Nov 14 '18 at 4:21
Am I doing the correct way to store the real part and complex part for kernel?
– kris
Nov 14 '18 at 4:21
@kris: Looks correct to me, but I haven't tried running your code. But you are computing that complex value twice, which is not efficient.
– Cris Luengo
Nov 14 '18 at 4:42
@kris: Looks correct to me, but I haven't tried running your code. But you are computing that complex value twice, which is not efficient.
– Cris Luengo
Nov 14 '18 at 4:42
Okay I’ll post an example later, I tried this but not working out....
– kris
Nov 14 '18 at 6:42
Okay I’ll post an example later, I tried this but not working out....
– kris
Nov 14 '18 at 6:42
add a comment |
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2
Did you try to search on SO before posting the question? Exact (not possible) Duplicate: stackoverflow.com/questions/30989915/…
– Rick M.
Nov 13 '18 at 13:48
Not working . I tried before
– kris
Nov 13 '18 at 13:53
Possible duplicate of TypeError: src data type = 15 is not supported
– n00dle
Nov 13 '18 at 16:02