Imagemagick has a nice page of example applications as well.  I first
learned about it in the book "The Scientist and Engineer's Guide to
Digital Signal Processing".  For a while I saw it as a bit of a
"secret weapon" but the cat's out of the bag these days.  See the
links below:

http://www.dspguide.com/ch24/6.htm
http://www.imagemagick.org/Usage/fourier/

On Mon, Mar 20, 2017 at 2:17 PM, Ron Ganbar <ron...@gmail.com> wrote:
> He's a question:
> Can somebody properly explain FFT?
> (I'm feeling so inadequate right now. Am I the only one left who doesn't
> know what this magical acronym is?)
>
>
>
>
>
> Ron Ganbar
> email: ron...@gmail.com
> tel: +44 (0)7968 007 309 [UK]
>       +972 (0)54 255 9765 [Israel]
> url: http://ronganbar.wordpress.com/
>
> On Mon, Mar 20, 2017 at 3:42 PM, Magno Borgo <li...@borgo.tv> wrote:
>>
>> A non-nuke alternative would be to pre-render the FFT using a python
>> package like scipy or similar, which already have fast FFT implementations,
>> then load/read it inside NUKE. That might help on some pipelines, though the
>> inverse edited FFT would still be needed to handled inside Nuke to be
>> practical.
>>
>>
>>
>>
>>
>> On Mon, 20 Mar 2017 11:09:30 -0400, jon parker <parker....@gmail.com>
>> wrote:
>>
>>> Thanks for the responses! I'm not a full-time comper so am unaware of
>>> some of the tricks out there, like using ZDefocus.  And I should have
>>> added that large kernels / images are involved so the standard
>>> convolve node falls behind at the resolution we are working with.
>>>
>>> Magno, I wasn't aware of your blinkscript.  If I have some time I'll
>>> peek at the code.
>>>
>>> Someone should put together a commercial implementation for Nuke some
>>> day, sounds like there is demand out there for it.
>>>
>>> -Jon
>>>
>>> On Mon, Mar 20, 2017 at 7:18 AM, Magno Borgo <li...@borgo.tv> wrote:
>>>>
>>>> I coded a naive Blinkscript DCT (and inverse) implementation a while
>>>> back,
>>>> you can check the code and use as a start for a better implementation.
>>>>
>>>> http://www.nukepedia.com/blink/other/dct-discrete-cosine-transform
>>>>
>>>> Magno.
>>>>
>>>>
>>>>
>>>>
>>>>
>>>> On Mon, 20 Mar 2017 03:39:40 -0400, Mads Lund <madshl...@gmail.com>
>>>> wrote:
>>>>
>>>> we did some CPU vs FFT tests aswell, but I can't remember the exact
>>>> kernel
>>>> size where FFT started to be more efficient, but it was rather low. On
>>>> the
>>>> flip side Convolve on the GPU seem to have some memory problems and (at
>>>> least for us) cause some random out of memory issues, even on beefy
>>>> cards.
>>>>
>>>> We found that using gaming techniques: up-scaling low frequency areas
>>>> (then
>>>> convolving) and only full convolving of high frequency areas to be to be
>>>> quite efficient for the vast majority of our renders where the plate is
>>>> gigantic or a large kernel size is needed.
>>>> The result is perceptually indistinguishable.
>>>>
>>>>
>>>>
>>>>
>>>> man. 20. mar. 2017 kl. 06.14 skrev Deke Kincaid <dekekinc...@gmail.com>:
>>>>>
>>>>>
>>>>> The convolve node was fixed up quite a while a go(4-5 years ago, it is
>>>>> what the zdefocus is based on).  In our tests though we still find the
>>>>> FFT
>>>>> nodes faster on the farm vs convolve in CPU mode.  If you have a gpu
>>>>> farm
>>>>> then convolve is faster.
>>>>>
>>>>>
>>>>> On Sun, Mar 19, 2017 at 6:23 PM Michael Habenicht <m...@tinitron.de>
>>>>> wrote:
>>>>>>
>>>>>>
>>>>>> The latest version of the convolve node has gpu support.
>>>>>>
>>>>>> Am 20.03.2017 um 01:20 schrieb jon parker:
>>>>>> > Greetings Nuke users,
>>>>>> >
>>>>>> > I'm just wondering if there are any faster, more robust FFT tools
>>>>>> > available for Nuke besides the (hidden) built-in nodes?
>>>>>> >
>>>>>> > The built-ins do the job, but they are pretty slow and definitely
>>>>>> > prone to crashing fairly often.
>>>>>> >
>>>>>> > Or, alternatively, something that does fast image convolution, some
>>>>>> > other way, under the hood could work too.
>>>>>> >
>>>>>> > Cheers,
>>>>>> > Jon
>>>>>> > _______________________________________________
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>>>>>> >
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>>>>>
>>>>>
>>>>> _______________________________________________
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>>>>
>>>>
>>>> --
>>>> Best regards. Mads Hagbarth Lund
>>>>
>>>>
>>>>
>>>>
>>>> --
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