Widefield microscope

to me it seems you need a flat-field correction. [https://en.wikipedia.org/wiki/Flat-field_correction] This means, you should divide by the correction, not subtract it (also the Fourier filters do a subtraction, not a division). Otherwise the features in the dark (insufficiently illuminated) parts of the image get too weak. You could try, e.g., the following macro:

Your new code (right?): https://github.com/saalfeldlab/stitching-spark/blob/42e01a6fe2751980102922513df309ba25b00f70/src/main/java/org/janelia/stitching/experimental/IlluminationCorrectionSliceParallel.java#L1452

I was wondering whether there is an ImageJ workflow already for correcting brightfield illumination? I just tried an own attempt (median filter based) and I guess that would be OK but I also do not want to reinvent the wheel…

PS: Here are again results obtained from the supplied sample image. Profiles are on the image diagonal from left bottom to right top.

Darkfieldmicroscopy

unfortunately you didn’t use the provided sample image for your experiments. Furthermore, the provided sample image is JPG-compressed …

Criticalillumination

If you have more images than CDRE can digest or you’re interested in 3D flatfields (I gues you’re not ;)), you can use our not yet published scale up of the CIDRE approach https://github.com/saalfeldlab/stitching-spark.

I have now a similar dataset (a time-laps of 60 wells with 6x6 tiles per well in Brightfield) and it would be great if you would have code that I could use Thanks!

As an alternative to CIDRE there is also BaSiC. There is an update site available for it and you can find a bit of demo/documentation here. If I remember correctly it does work on stacks and was quite fast.

In fact, I do have more images. My naive approach was just to compute a median projection, thereby ideally removing the objects and only being left with the flat-field. This of course does not work very robustly if there are many objects in every image. Thus, thanks for pointing out CIDRE I will check it out!

Just for the record (maybe other people will find this post interesting): CIDRE and BaSiC are giving very similar results for my data (just different treatment of the offset due to the particular CIDRE settings that I used): image2384×1478 1.06 MB

the BioVoxxel Pseudoflatfield correction with a radius around 10 also doesn´t look too bad and it´s super easy to use. There are some artifacts in the lower left corner which I guess are due to the jpeg format of the sample image.

If you have many images from the same microscope under similar settings, you can estimate the flatfield with CIDRE https://github.com/smithk/cidre.

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CIDRE works really well! However I would need to write an other UI that enables batch-processing of many experiments and also accepts Tiff stacks as input. I guess it would make to use your new code as a starting point, rather than the original one?

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there are a few documented methods. From these, I found the FFT bandpass filter to work nice and fast, but the result using your image posted above is not necessarily of better quality compared to what you already have.

As an alternative to CIDRE there is also BaSiC . There is an update site available for it and you can find a bit of demo/documentation here . If I remember correctly it does work on stacks and was quite fast.

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What magnification? If overall magnification is small, a normal Microscope may be sub-optimum and special illumination may be needed.

In the case in question they zero out harmonic spatial waves of large periods. Division is the way to go but improved image acquisition is superior!

Köhlerillumination

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Could you please test it? Update site: EMBL-CBA And then at the very bottom of Plugins > Restoration > Illumination > BaSiC (I am not sure it will work immediately because I had some strange dependency issues…)

If you’re only after a band pass, you could also try Plugins > Integral Image Filters > Normalize Local Contrast which is even faster than the FFT bandpass. Try various block-sizes with preview checked

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I have now a similar dataset (a time-laps of 60 wells with 6x6 tiles per well in Brightfield) and it would be great if you would have code that I could use Thanks!