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.

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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.

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

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!

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

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

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

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?

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:

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…)

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.

Köhlerillumination

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.

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!

Darkfieldmicroscopy

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

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

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…

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!

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Criticalillumination

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.

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

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!

Integral images have been introduced in by Crow (1984)[1] as a technique to improve texture rendering speed at multiple scales in perspective projections. The technique has since then been used for a number of applications. The most popular...