B&C adjustment for single images in stack

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B&C adjustment for single images in stack

Patrik G. Flammer
Dear all,

I aquire stack images (live-cell time-lapse experiment) of particle movement. Durinig the time-course I see strong bleaching of the fluorophores. As I am primarily interested in the movement and not in the absolute intensity, I tried to adjust B&C for every image in the stack so that I could compile a movie file. However, with the macro I used, I just modify the images once, but the saved correction is only adjusted for the last image. Is there a way to correct and save every single image of a stack?

Macro I used:
   n = nSlices;
   if (n==1) exit("Stack required");
   Stack.getStatistics(count, stackMean);
   for (i=1; i<=n; i++) {
run("Enhance Contrast", "saturated=0.5");
      setSlice(i);
      getStatistics(count, mean);
      run("Add...", "slice value="+(stackMean-mean));
   }

Thanks for your help

Patrik
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Re: B&C adjustment for single images in stack

Frank Sprenger
Just normalize all slices with enhanc contrast

no additional macro info necessary, just this line:


run("Enhance Contrast", "saturated=0.5 normalize normalize_all");



Best

Frank


On Feb 24, 2010, at 1:15 PM, Patrik G. Flammer wrote:

> Dear all,
>
> I aquire stack images (live-cell time-lapse experiment) of particle movement. Durinig the time-course I see strong bleaching of the fluorophores. As I am primarily interested in the movement and not in the absolute intensity, I tried to adjust B&C for every image in the stack so that I could compile a movie file. However, with the macro I used, I just modify the images once, but the saved correction is only adjusted for the last image. Is there a way to correct and save every single image of a stack?
>
> Macro I used:
>   n = nSlices;
>   if (n==1) exit("Stack required");
>   Stack.getStatistics(count, stackMean);
>   for (i=1; i<=n; i++) {
> run("Enhance Contrast", "saturated=0.5");
>      setSlice(i);
>      getStatistics(count, mean);
>      run("Add...", "slice value="+(stackMean-mean));
>   }
>
> Thanks for your help
>
> Patrik