Virtual foreward scattered detector (VFSD) functionality

[hakonanes]

Create functions (or a dedicated VFSD class) to streamline formation of VFSD images. Desired functionality:

1. Bin signal axis to 5 x 5 pixel pattern
2. Form images from any number of bins
3. Form RGB image by coloring three bins

Focus should be on maximising the contrast in each image, by e.g. using histogram equalization (http://scikit-image.org/docs/dev/auto_examples/color_exposure/plot_equalize.html). The latter is related to #14.

[tinabe]

Is interactive plotting something you have in mind for point 3? We could create 3 RGB markers that can be moved around to create a virtual interative image, hopefully by inheriting from pyxem or HS.

A simple solution would be to input 3 numbers corresponding to which pixels to use for each of the RGB channels. I think this should be used for point 2 in your list, at least.

[hakonanes]

Yes, it would be ideal if the image formation function could take in either of:

1. Bin index (say (3, 3) for the centre bin, if 5 x 5 bins)
2. List of bin indices
3. One hyperspy.roi.BaseInteractiveROI
4. Multiple hyperspy.roi.BaseInteractiveROI

If a list of bin indices or ROIs are passed, the user should also be able to determine if they should be colored and in what color (a three element list for each image, or simply 'R', 'G' or 'B').

[hakonanes]

After discussions with Jarle Hjelen: a forth feature could be creating VFSD images from two vertical rectangles on either side of the detector and subtract or add them to enhance topographical contrast similar to humans' stereopsis (binocular vision, https://en.wikipedia.org/wiki/Binocular_vision#Stereopsis).

[hakonanes]

A way to test this functionality against commercial solutions is to compare our results to:

• Bruker Nano's three images acquired from backscatter electrons incident on their FSD below the EBSD detector (one intensity for R, G, and B per pattern), available in e.g. this dataset uploaded by Wilkinson and Collins (https://zenodo.org/record/1288431#.XSbooyZS9hE) in the HDF group 'Scan 0/SEM/SEM Image'.
• EDAX TSL's three images from their VFSD called PRIAS bottom strip, centre square and top strip, available in e.g. these datasets uploaded by De Graef, Pascal, and Jackson (https://kilthub.cmu.edu/articles/Data_Sets_and_Analysis_Results_Accompanying_a_Dictionary_Indexing_Tutorial_Paper/7792505) in the HDF groups 'Scan x/EBSD/Data/PRIAS Bottom Strip' etc., with x = 1, 4, or 6 for the three scans in the file.

Since Bruker has a FSD, I guess the best way to test is towards TSL's datasets.

[hakonanes]

Relevant literature (updated as more is found):

• Prior et al. (1996)
• Day & Quested (1999)
• Wright et al. (2015)
• Nolze et al. (2017)
• Britton et al. (2018)
• Brodusch et al. (2018)

[hakonanes]

This functionality is largely supported with:

• s.virtual_forward_scatter_detector()
• s.get_virtual_image()

What we should have is a version of pyXem's VDFGenerator to streamline typical results desired. Typical results include RGB image from three bins in a 5 x 5 px detector (as done in the above referenced paper by Wrgith et al. (2015)), phase contrast image (upper part of detector) and topography contrast image (lower part of detector).

[hakonanes]

The 5 x 5 array is very similar to Aimo Winkelmann's 7 x 7 arrays in the aloe/xcdskd project:

• example usage: https://xcdskd.readthedocs.io/en/latest/arbse/arbse_AstroEBSD.html
• implementation: https://github.com/wiai/xcdskd/blob/master/src/aloe/image/arbse.py

We should focus on his implementation, perhaps let the user determine how fine the array should be.

This array should be its own class... with the different imaging possibilities showcased in the example usage link as methods? This way other possible signals can use the same class, not just EBSD.

[hakonanes]

Although not that automated, all these things are possible, with some know-how, via kikuchipy.signals.ebsd.EBSD.virtual_backscatter_electron_imaging() and kikuchipy.signals.ebsd.EBSD.get_virtual_image().