Add `voronoi_tessellation` tool

[kostrykin]

For the contributor:

• [x] - I have read the CONTRIBUTING.md document.
• [x] - License permits unrestricted use (educational + commercial).
• [x] - This PR adds or updates a tool or tool collection.
  • [x] - This PR adds a new tool or tool collection.
  • [ ] - This PR updates an existing tool or tool collection.
  • [x] - Tools added/updated by this PR comply with the Naming and Annotation Conventions for Tools in the Image Community in Galaxy (or explain why they do not).
• [ ] - This PR does something else (explain below).

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The added tool takes an image with labels as input and yields an image with the corresponding Voronoi tessellation (aka Voronoi diagram, Dirichlet tessellation). This mimics the behavior of the ImageJ function Process ‣ Binary ‣ Voronoi: https://bioimagebook.github.io/chapters/2-processing/6-transforms/imagej.html#voronoi

xref #105

[kostrykin]

I don't understand much about images, but are both images included here supposed to be black and the same size?

Short answer: The images are fine, I just double-checked them.

Long answer: They are not really black :)

In [1]: import skimage.io

In [2]: skimage.io.imread('input1.tiff')
Out[2]: 
array([[0, 0, 0, 0, 0, 0, 3, 3, 3, 3],
       [0, 1, 1, 0, 0, 0, 3, 3, 3, 3],
       [0, 1, 1, 0, 0, 0, 3, 3, 3, 3],
       [0, 0, 0, 0, 0, 0, 3, 3, 3, 3],
       [0, 0, 0, 0, 0, 0, 3, 3, 3, 3],
       [0, 0, 0, 0, 0, 0, 3, 3, 3, 3],
       [0, 0, 0, 0, 0, 0, 0, 4, 4, 4],
       [0, 2, 2, 0, 0, 0, 0, 4, 4, 4],
       [0, 2, 2, 0, 0, 0, 0, 0, 0, 0],
       [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype=uint8)

In [3]: skimage.io.imread('input1_result.tiff')
Out[3]: 
array([[1, 1, 1, 1, 3, 3, 3, 3, 3, 3],
       [1, 1, 1, 1, 1, 3, 3, 3, 3, 3],
       [1, 1, 1, 1, 1, 3, 3, 3, 3, 3],
       [1, 1, 1, 1, 3, 3, 3, 3, 3, 3],
       [1, 1, 1, 1, 3, 3, 3, 3, 3, 3],
       [2, 2, 2, 2, 3, 3, 3, 3, 3, 3],
       [2, 2, 2, 2, 2, 3, 3, 4, 4, 4],
       [2, 2, 2, 2, 2, 4, 4, 4, 4, 4],
       [2, 2, 2, 2, 2, 4, 4, 4, 4, 4],
       [2, 2, 2, 2, 2, 2, 4, 4, 4, 4]], dtype=uint8)

The pixel values just all are very close to 0, which makes it look black, but in fact it's very dark gray. The exact values do not really matter, they are just arbitrary labels for distinct image regions.

[bgruening]

Ok, as I said, I have no clue about images ;)