Posted by
Michael Elbaum on
Aug 26, 2005; 7:33am
URL: http://imagej.273.s1.nabble.com/Non-uniform-illumination-and-noise-reduction-tp3704964p3704968.html
I second the suggestion. Most likely the non-uniformity in your
illumination field does not change or flicker in time. (if it does you
should probably replace the Hg lamp!) You can take a blank image simply
with some free fluorophore in solution. Then you need to boost
sensitivity in the dim regions or suppress it in the bright ones,
relatively. This is "flat-field"ing with what ought to be a uniformly
bright image. You should divide each frame by the blank, with some
appropriate normalization in the arithmetic to match the brightnesses.
If you want to keep things quantitative you should first subtract a dark
image from your stack, or the average value of a dark image, so that
zero light gives zero pixel value. You should subtract it from the blank
as well, but make sure there are no zero values. In the end each pixel
should have the same sensitivity to fluorescence with no dependence on
its position.
good luck...
Michael Elbaum
>>> Joel Sheffield <
[hidden email]> 08/25/05 6:36 PM >>>
Can you get an image of the illuminating field without the sample?
If so, you could subtract, or divide (depending on what works for
you)this image from each of the frames, and then adjust b/c.
Alternatively, you might be able to create a pseudo background by
taking one of your original images and carrying out a blur operation
to reduce the effect of the sample, but retain the broad intensity
distribution.
Joel
> Hello,
> I'm trying to analyze some calcium dye fluorescence images. The
> illuminating field appears to be non-uniform, and I'm looking for a
> good way to calculate and remove the background illumination. So far,
> I've tried both the built-in "Subtract Background" command (Process ->
> Subtract Background) and the plugin "Background Correction"
> (
http://rsb.info.nih.gov/ij/plugins/background.html). These both to
> seem to work reasonably well, but the second does not work for a
> multiframe image. I was wondering if anyone had any experience with
> these two tools, and if they could provide any insight into how these
> tools work, and if there are others I should be considering.
>
> Because the image set is a 500 frame t-series, it seems like the best
> algorithm would be one that uses the data from every frame to
> calculate the best possible approximation of the illuminating field.
> Additionally, such a utility could identify likely points of noise
> because the noise will change much more rapidly (from frame to frame)
> than the actual signal. Is there anything like this for ImageJ that
> anyone can recommend? I would really appreciate any suggestions or
> insight.
>
> Thanks,
> Michael Chelen
Joel B. Sheffield, Ph.D.
Biology Department, Temple University
1900 North 12th Street
Philadelphia, PA 19122
[hidden email]
(215) 204 8839, fax (215) 204 0486
http://astro.temple.edu/~jbs