Ideal low-pass filter in the Frequency Domain I try to create a low-pass filter to apply it for an image.

$$H(U, V)=1 \text{, if }D(U,V) ≤ D_0 \text{, and } 0 \text{ otherwise}$$

and $D(U, V) = \sqrt{U^2 + V^2}$

U,V = np.shape(padded)
H = np.zeros((U,V))
D = np.zeros((U,V))
#cut off point
D0 = 5
for u in range(U):
    for v in range(V):
        D[u,v] = np.sqrt(u**2+v**2)
        if D[u,v] &lt;= D0:
            H[u,v] = 1
        else:
            H[u,v] = 0
plt.imshow(H,cmap='gray')
plt.show()




After I Run it I expect this image

 

But I get this circle at the left top of the image as bellow :





so I think I should get the center of $\frac{U}{2}$ and $\frac{V}{2}$ but I do not know how. 

How can I get the expected filter image?!
The rule should be something like this i suppose $$D(|U - U_o/2|,|V - V_o/2|)≤ D0$$ where $U_o$ is the length of image in horizontal dimension and $V_o$ is the length of image in vertical dimension