[SciPy-User] 2d convolution

josef.pktd@gmai... josef.pktd@gmai...
Mon Mar 22 20:08:11 CDT 2010

On Mon, Mar 22, 2010 at 8:17 PM, Nico Schlömer <nico.schloemer@gmail.com> wrote:
>> If it is much faster than the n-dimensional fft convolution
> For me it is about 60(!) times faster, see the attached graph (mind
> the log scaling).
> I had NxN data with NxN kernels convolved.
> The source code for producing the figure is attached as well.
>> be worth writing a fftconvolve2
> What remains to be checked is the ratio for the case where the kernel
> is a lot smaller than the data. If that turns out to be equally fast,
> I don't see any reason to keep the current implementation of
> scipy.signal.fftconvolve.

I'm using it (or tried to use it) also for 3d data, so we still want
to keep the nd version.

You could file an enhancement ticket for a fftconvolve2d

A few weeks ago there was also the remark in a thread that
signal.convolve2d is faster than the nd version.

I'm not an image processing person, so I don't know what the optimal
convolution behavior for this is, and what could be a replacement for

There is also a convolution in ndimage but I have no idea about it's
performance, and I don't know if scikits.image has any special

> Anyway, this may also be related to that other discussion going on
> about FFTW. I'm not sure what the current status about FFT
> implementations in SciPy is, but at first glance there seem to be
> quite a few really, which to me seems redundant and unhelpful.
> Does anyone have more insight here?

fftw has been removed from scipy.  scipy.fft and numpy.fft are plain vanilla.



> Cheers,
> Nico
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