Re: Rephrased FFT Question

Posted by Rebecca Keller on Mar 21, 2014; 1:58am
URL: http://imagej.273.s1.nabble.com/Rephrased-FFT-Question-tp5007000p5007023.html

Yes, this macro is exactly the right thing, but it is really slow even when
I make the stack 2^n (4096) images and bin it 4 x 4 x 2. (128 x 128 x 2048
total voxels.) I would think it could be much faster if implemented right,
in java perhaps? I would guess that opening all those windows is
unnecessary, but I am not sure how to *not* open them. But anyway, the
results are pretty cool--any idea what frequency is represented by each
image? Also, it's close to symmetrical over time--what's going on there,
exactly (see attached)? I would think if it were symmetrical it would be
largest in the center as well, but...

Anyway, thanks for this start--I'll see what can be done,

JPK





On Thu, Mar 20, 2014 at 12:01 PM, Brian Northan <[hidden email]> wrote:

> Hi Rebecca
>
> I am not aware of a simple solution, hopefully someone else knows.   But
> someone had a similar problem a while back and it ended up being a fairly
> involved discussion.  He had to write some macros.
>
>
> http://imagej.1557.x6.nabble.com/Automating-Image-Processing-and-Problems-with-FFTJ-td5004660.html
>
> As Herbie mentioned FFTJ is not macro-recordable, I have a slightly
> modified version of FFTJ which is recordable and is available here
>
> https://github.com/bnorthan/RogueImageJPlugins/releases
>
> It is really just a copy of the original except with the small changes
> talked about in the other thread.
>
> I played around with calling FFTJ on individual points in a time series
> using a python macro.  I think the logic is right but keep in mind it is a
> hack and pretty slow.   The proper way to do it would be to perform all
> calculations in one plugin.   This approach loops through every pixel,
> copies a time profile to a temp image then runs the plugin over and over.
>
>
> https://github.com/bnorthan/RogueImageJPlugins/blob/master/FFTJ_scriptable/macros/Time_Macro.py
>
>
>
>
> On Thu, Mar 20, 2014 at 6:02 AM, Herbie <[hidden email]> wrote:
>
> > Rebecca,
> >
> > if you manage to extract 1D-"images" from your time series of images,
> > i.e. in fact pixel sequences as 1D-images, then you may use the
> > FFTJ-PlugIn to perform 1D-FFTs of each of these series.
> >
> > <http://rsb.info.nih.gov/ij/plugins/fftj.html>
> >
> > You may use a macro to extract the n^2 1D-images (assuming that your
> > images are of size n x n). To make use of the FFT speed advantage, your
> > stack must consist of m images (time slices), where m is a power of two.
> >
> > The problem with FFTJ is, that it isn't perfectly macro-recordable. It
> > shows a dialog for choosing the result format. In other words, to fully
> > automatize processing by an IJ-macro, you need to modify the source code
> of
> > FFTJ.
> >
> > HTH
> >
> > Herbie
> >
> > ::::::::::::::::::::::::::::::::::::::::
> >
> > On 20.03.14 02:04, Rebecca Keller wrote:
> >
> >> Thanks very much for this reference, but actually it is a bit
> >> cumbersome to come in and out of imagej, since this "plugin" requires
> >> ms excel for the fft'ing.
> >>
> >> Seems like it should be possible to get the current fft algorithm to
> >> do a 1D FFT on each pixel over time, then re-output the timelapse
> >> stack as a 2D image in frequency domain. Then it would be neat, for
> >> example, to make a 2D image depth-coded by frequency. I, however,
> >> just need to get the pixels which all have the same frequencies,
> >> which should be easy enough to do using the 1D FFT pixelwise which I
> >> suggested.
> >>
> >> JPK
> >>
> >> On Wed, Mar 19, 2014 at 5:18 PM, Eric Denarier <
> >> [hidden email]> wrote:
> >>
> >>  Hi Rebecca, You may have a look to Claire Smith's CiliaFA macro. It
> >>> reveals frequencies of intensity variation in different zone of a
> >>> brightfield image. We are using it for high frequency Cilia
> >>> beating. here is a link to the paper and macro :
> >>> http://www.ciliajournal.com/content/1/1/14
> >>>
> >>>
> >>> Rebecca Keller <[hidden email]> a écrit :
> >>>
> >>> Dear List,
> >>>
> >>>>
> >>>> Let me rephrase: what I am trying to do is locate oscillations of
> >>>> a certain frequency onto a 2D visual field, i.e., convert the
> >>>> third dimension (time) of a time-lapse image series into
> >>>> frequency space. Then I could scan through frequency space (the
> >>>> new third dimension) to find groups of pixels with similar
> >>>> oscillation frequencies.
> >>>>
> >>>> So I guess what would need to be done is a 1D FFT for each pixel.
> >>>> Is there any way easily to do this with the current imagej
> >>>> tools?
> >>>>
> >>>> JPK
> >>>>
> >>>> -- ImageJ mailing list: http://imagej.nih.gov/ij/list.html
> >>>>
> >>>>
> >>> -- ImageJ mailing list: http://imagej.nih.gov/ij/list.html
> >>>
> >>>
> >> -- ImageJ mailing list: http://imagej.nih.gov/ij/list.html
> >>
> >>
> > --
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> >
>
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