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common use cases of FFTs in image processing/analysis #4

@psteinb

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@psteinb

Dear @haesleinhuepf @bnorthan ,

don't panic, nothing wrong with clij2. ;-) Not sure if this is the right place to ask, maybe the imagej forums might be worth trying as well.
My student @zyzzyxdonta is working on benchmarking FFTs on Power9 and ARM platforms. One of his examiners critized our benchmarking approach as non-realistic. We basically conduct warm-up runs on our synthetic data and then "only" measure the hot cache runs following this to obtain an ensemble of time measurements. This gives us more sound statistics to make inferences and compare.

So I'd love to know, where people use FFTs and with which data. So I am interested in the following questions:

  • what transforms do people use most of the time
    a) real2complex
    b) complex2complex
    c) complex2real
    My guess for the image analysis community would be a+c.
  • what are the typical signal sizes/shapes and types for the inputs: how many elements, how many dimensions, what are the datatypes used (float or double)
    No guess for this one.
  • Are FFTs used mostly in a one-off manner or or people interested in fast FFTs only if they are executed in recursive/iterative applications (think Richardson-Lucy deconvolutions)
    My guess would be that people are interested in fast FFTs for the latter exclusively.

I know that these are quite general questions, but at least some sample answers would help us.

Best,
@psteinb

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