[Numpy-discussion] strange behavior convolving via fft
Stéfan van der Walt
Mon May 11 15:25:53 CDT 2009
If you have MxN and PxQ signals, you must pad them to shape M+P-1 x
N+Q-1, in order to prevent circular convolution (i.e. values on the
one end sliding back in at the other).
2009/5/11 Chris Colbert <email@example.com>:
> Did I pad my example incorrectly? Both images were upped to the larger
> nearest power of 2 (256)...
> Does the scipy implementation do this differently? I thought that since FFTW
> support has been dropped, that scipy and numpy use the same routines...
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