title: scipy.ndimage.filters.convolve and multiplying Fourier Transforms give different results
body: <p>Here's my code:</p>
  
  <pre><code>from scipy.ndimage import filters
  import numpy
  
  a = numpy.array([[2,43,42,123,461],[453,12,111,123,55] ,[123,112,233,12,255]])
  b = numpy.array([[0,2,2,3,0],[0,15,12,100,0],[0,45,32,22,0]])
  
  ab = filters.convolve(a,b, mode='constant', cval=0)
  
  af = numpy.fft.fftn(a)
  bf = numpy.fft.fftn(b)
  
  abf = af*bf
  
  abif = numpy.fft.ifftn(abf)
  
  print numpy.around(ab)
  print numpy.around(abif)
  </code></pre>
  
  <p>The results are:</p>
  
  <pre><code>[[ 1599  2951  7153 13280 18311]
   [ 8085 51478 13028 40239 30964]
   [18192 32484 23527 36122  8726]]
  
  [[ 37416.+0.j  32251.+0.j  46375.+0.j  32660.+0.j  23986.+0.j]
   [ 30265.+0.j  33206.+0.j  62450.+0.j  19726.+0.j  17613.+0.j]
   [ 40239.+0.j  38095.+0.j  24492.+0.j  51478.+0.j  13028.+0.j]]
  </code></pre>
  
  <p>How can I fix my way of doing convolution using FFT so to guarantee that it gives the same result as <code>scipy.ndimage.filters.convolve</code>?</p>
  
  <p>Thank you.</p>