docs: add tophat explanation for baseline correction (#106)

Author: EscapedGibbon

docs/Tutorials/Correcting baseline with topHat.md

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+There are moments when an image doesn't have a perfect lightning and you have uneven background like here.
+
+![sudoku](./images/topHat%20correction/sudoku.png)
+
+So, when extracting regions of interest the regular way you will have a mask like that:
+
+```ts
+//The default algorithm used is
+//"otsu".
+mask = image.threshold();
+```
+
+![Global threshold](./images/topHat%20correction/globalThreshMask.jpg)
+
+The cause of this is the nature of the threshold algorithm. In ImageJS it takes a global threshold variable, which means that the algorithms calculate one value and compare it with all the pixels to create a Mask. Obviously, such approach is not very effective when there are smooth shades and uneven illumination.
+One of the ways to deal with uneven illumination and improve the output is to apply `topHat`() method. It is a method that subtracts the result of morphological opening from the original image.
+
+```ts
+image = image.grey().invert();
+//Big structuring element is necessary for
+const kernel = Array(101).fill(Array(101).fill(1));
+image = image.topHat({ kernel });
+```
+
+![topHat comparison](./images/topHat%20correction/topHatComp.png)
+
+Therefore if we look at the histograms of these two images at a given point we will see that the intensities are spread more evenly after topHat, rather than before.
+
+### Histogram before applying topHat
+
+![](./images/topHat%20correction/histBeforeTopHat.svg)
+
+### Histogram after applying topHat
+
+![](./images/topHat%20correction/histAfterTopHat.svg)