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====== Clean up diamond anvil cell data ======

Typical diamond anvil cell data for multigrain XRD has to be pre-processed and cleaned.

Elements that should be addressed are:
  * shadows from the tungsten carbide diamond seats,
  * single-crystal diffraction spots from the diamond anvils,
  * additional diffraction from very small grains (powder rings), pressure media, etc.

===== Shadows =====

Diamond anvil cells have a limited opening and create shadows due to the seat supporting the diamonds.

We we started multigrain crystallography experiments, we though this was going to be a problem and created a script called [[software:remove-shadow|timelessDACShadow]] to do so.

As a matter of fact, this is not very useful as there simply nothing in these regions. You can probably leave the shadows as they are.

===== Diamond spots removal =====

==== General idea ====

Processing of the single-crystal diffraction spots from the diamond anvils is performed using the  [[software:timelessDiamondSpotRemoval|timelessDiamondSpotRemoval script]], which is part of the [[software:timelesstools|TIMEleSS tools]].

The idea is that diamond diffraction is
  * very intense (often saturate the detector),
  * extends over many pixels (in X and Y) and in ω.

The ''timelessDiamondSpotRemoval'' script does the following
 - reduce the resolution of the image, to make it blur and get rid of the small features,
 - apply a median filter on the reduced image to clear out small diffraction spots, which are probably originating from the sample,
 - detect diamond diffraction spots based on a threshold in intensity,
 - create a mask based on the detected diamond diffraction spots,
 - expand the mask in X, Y, and ω to account for the fact that the real diamond diffraction spots are wider and appear over wider omega ranges than detected by the above steps.

''timelessDiamondSpotRemoval''  requires a median image. Median will be removed in this script. Once 

In addition, you can define a disk, at the center of the image, in which nothing should be removed. This option is for samples with very intense diffraction spots on the inner rings which could be confused with diamond spots based on intensity criteria.

==== Step by step instructions ====

In the first round, you should test the spot detection. This is performed by running ''timelessDiamondSpotRemoval [options] spots''. You should play on the ''scale'', ''filtersize'', and ''threshold'' parameters. As you run the script, it will show you the original image, and the location where it detected diamond spots. Play with the above parameters until you are satisfied with the diamond spot detection, and  only diamond spots. You do not want this script to detect sample spots.

In a second round , you use ''timelessDiamondSpotRemoval [options] plotMask''. It will run the diamond spot detection (use the parameters you found in the previous steps), create a mask, and plot it in overlay to the diffraction images. Grow your mask with ''growXY'' and ''growXYO''. You can also force the script to ignore a disk-shape region in the center of the image with the ''c_rawy'', ''c_rawz'', and ''radius'' parameters.

Third step: ''timelessDiamondSpotRemoval [options] clearMask''. Use the same option as above. It will show you the result of your mask.

Final step: ''timelessDiamondSpotRemoval [options] save'', to save the clean images in new files.

==== Detailed example ====

[{{:processing:diamondremoval:orginal-image.jpg?direct&300 | Original diffraction image.}}] 
[{{ :processing:diamondremoval:diamond-removed-median.jpg?direct&300|Same image, after running the diamond removal script}}]

In the above example, the ''timelessDiamondSpotRemoval'' script is used to
  * remove the median
  * erase the image region with diamond spots.
The exact command with ran was
   timelessDiamondSpotRemoval -P Images/ -n imagestem_ -f 0990 -l 1000 -d 5 -m image_median.edf --newpath=DiamRem/ --filtersize=11 --growXY=10 --growXYO=10 -t 0.75 save

The parameters were chosen as follow
  * ''Images/'' was the path to the images to process,
  * We processed images ''imagestem_00990.edf'' to ''imagestem_01000.edf'',
  * The file with the median image was ''image_median.edf''
  * We saved the new images in ''DiamRem/''
  * ''filtersize=11'' was a good setting to detect diamond spots, and only those. A smaller value was catching sample peaks as well,
  * ''growXY=10'': grow the mask by 10 pixels in both x and y,
  * ''growXYO'': grow the mask by 10 pixels in omega, but also x and y (in addition to the previous growth),
  * a threshold of 0.75 (relative units) worked well.
Note that the number of pixels used to grow the mask may be different from the final size of the mask. The final mask will be larger than your settings (there is a scaling applied somewhere).

As a test, the image below shows the [[processing:search_for_peaks|sample peaks we extracted]] from the final image. This would not have been possible on the raw diffraction image.

[{{ :processing:diamondremoval:diamond-removed-median-peaks.jpg?direct&300 | Peaks extracted from the diffraction image, after running the diamond removal script }}]

==== Inpainting ====

By default, the [[software:timelessDiamondSpotRemoval|timelessDiamondSpotRemoval script]] replaces the masked region with the median intensity of the image. Sometimes, this can lead to problems. 

In such case, you can use //inpainting// which will try to fill the gap as well as possible. This is done by adding ''--inpaint True'' to the command line arguments.

The script will be significantly slower, but gaps will be filled with values matching the mask's surroundings. As a matter of fact, we have had little use of this option but, at least, it is available.


[{{:processing:diamondremoval:diamond-removed-median.jpg?direct&300 | Diffraction image, after running the diamond removal script and replacing masked values with the image median}}] 
[{{ :processing:diamondremoval:diamond-removed-inpaint.jpg?direct&300|Same diffraction image, after running the diamond removal script and replacing masked values with inpainting}}]
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