The following code block shows how to reconstruct the image with IFFT from the filtered Fourier coefficients:

# Reconstruct the denoised image from the filtered spectrum, keep only the real part for display.
im_new = fp.ifft2(im_fft2).real
pylab.figure(figsize=(10,10)), pylab.imshow(im_new, pylab.cm.gray),
pylab.axis('off')
pylab.title('Reconstructed Image', size=20)

The following screenshot shows the output of the preceding code—a much cleaner output image obtained from the original noisy image with filtering in the frequency domain: