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--- processing:backgroundgeneral [2019/09/04 18:39] – ↷ Page name changed from processing:background to processing:backgroundgeneral smerkel
+++ processing:backgroundgeneral [2019/09/05 14:55] (current) – smerkel
@@ Line 1: / Line 1: @@
-====== Evaluate background ======
+====== Background evaluation and subtraction ======
-One necessary step of the data processing is the subtraction of the background. One way to do it is to create an average or a median image of the whole file series and then subtract each single image by this average/median. This method has the advantage that you not only get rid of the background noise but also all those reflections which are visible homogeneously in every image, such as pressure media, artefacts on the detector or some diamond spots.
+Diffraction data typically include multiple contributions. These include
+  * noise, from the detector, the source, etc
+  * diffraction from anything within the path of the x-ray beam, which is not your sample,
+  * diffraction from the larger sample grains, that give rise to well-defined diffraction spots,
+  * diffraction from the smaller sample grains (i.e. a fine matrix), that does not show up as well-defined diffraction spots but rather continuous diffraction rings.
-===== Subtract average or median? =====
+Most of these should be removed before further processing. Multigrain crystallography relies on the indexing of well-defined diffraction spots.
-Creating an average image can be done with ''timelessMeanFileSeries'' which is part of the [[software:timelesstools|TIMEleSS tools]]. Creating the median can be done with ''median.py'' which comes with [[software:fabian|Fabian]].
+===== Average and median images =====
+Background evaluation always involve the calculation of average and median images. In the average image, the intensity at each pixel is the average of the intensity at this pixels for all images in the ω scan. In the median image, the intensity at each pixel is the median of the intensity at this pixels for all images in the ω scan.
+The average image is a representation of the data that includes
+  * the background,
+  * the diffraction from the //surrounding matrix// (the //powder portion of the sample//) that gives rise to continuous diffraction rings,
+  * the diffraction from the //sample grains//, that give rise to well-defined diffraction spots.
+The median image is a representation of the data that includes
+  * the background,
+  * the diffraction from the //surrounding matrix// (the //powder portion of the sample//) that gives rise to continuous diffraction rings in the image.
+The diffraction from the //sample grains//, that give rise to well-defined diffraction spots are removed and **//do not contribute//** to the median image!
+Creating an average image can be done with [[xray_data:averagemanyedf|timelessMeanFileSeries]] which is part of the [[software:timelesstools|TIMEleSS tools]]. Creating the median can be done with ''median.py'' which comes with [[software:fabian|Fabian]]. You can also calculate median and average images with [[software:imagemath|ImageMath]] but we have not used it in a while. There is an issue with file formats.
+The median image is less affected by outliers than the average and is probably a better representation of your background. For some purposes you might still need to use the average image.
+===== Testing and subtracting the background =====
+The most efficient way is to test your background with [[software:fabian|Fabian]]. You can
+  * load an example diffraction image,
+  * select ''Image'' > ''Correction'' > ''Background image''
+  * select ''Image'' > ''Correction'' > ''Subtract background''
+You will be able to visualize the effect you the background subtraction and whether your evaluation is satisfactory.
+Typically, subtracting the ω-median from a single ω-step diffraction image will be efficient at removing
+  * noise, from the detector, the source, etc
+  * diffraction from anything within the path of the x-ray beam, which is not your sample, as long as it is in the form of a powder,
+  * diffraction from the smaller sample grains (i.e. a fine matrix), that does not show up as well-defined diffraction spots but rather continuous diffraction rings.
+It will not work, however, for complex environments such as diamond anvil cells for which the diamond anvils give rise to strong and well defined diamond diffraction spots.
-The median image is less affected by outliers than the average. Therefore, if you have strong diamond peaks in some of the images, you will probably still see them also on the average image while there are none in the median one. Because of that, for subtracting the background the median image should be preferred. However, for other purposes you might still need the average image.
 ===== When to subtract the background? =====