Virtual backscatter electron imaging

Interactive plotting

Angle resolved backscatter electron (BSE) imaging can be performed interactively with the method plot_virtual_bse_intensity(), adopted from pyxem, by integrating the intensities within a part, e.g. a (10 x 10) pixel rectangular region of interest (ROI), of the stack of EBSD patterns:

>>> import hyperspy.api as hs
>>> roi = hs.roi.RectangularROI(left=0, top=0, right=10, bottom=10)
>>> roi
RectangularROI(left=0, top=0, right=10, bottom=10)
>>> s.plot_virtual_bse_intensity(roi)
>>> roi
RectangularROI(left=25, top=42, right=30, bottom=47)
_images/virtual_backscatter_electron_imaging.gif

Fig. 4 Interactive virtual backscatter electron imaging.

Note that the position of the ROI on the detector is updated during the interactive plotting. See HyperSpy’s ROI user guide for more detailed use of these.

The virtual image, created from integrating the intensities within the ROI, can then be written to an image file using get_virtual_bse_intensity():

>>> import matplotlib.pyplot as plt
>>> vbse = s.get_virtual_bse_intensity(roi)
>>> vbse
<VirtualBSEImage, title: Virtual backscatter electron image, dimensions: (|200, 149)>
>>> plt.imsave(fname='/path/to/virtual_image.png', arr=vbse.data)

A VirtualBSEImage object is returned.

Generate many virtual images

Sometimes we want to get many images from parts of the detector, e.g. like what is demonstrated in the xcdskd project with the angle resolved virtual backscatter electron array (arbse/vbse array). Instead of keeping track of multiple hyperspy.roi.BaseInteractiveROI objects, we can create a detector grid of a certain shape, e.g. (5, 5), and obtain gray scale images, or combine multiple grid tiles in red, green and channels to obtain RGB images.

First, we initialize a virtual BSE image generator VirtualBSEGenerator object with a EBSD object, in this case the raw EBSD patterns without any background correction or other processing:

>>> s
<EBSD, title: Pattern, dimensions: (200, 149|60, 60)>
>>> vbse_gen = kp.generators.VirtualBSEGenerator(s)
>>> vbse_gen
VirtualBSEGenerator for <EBSD, title: Pattern, dimensions: (200, 149|60, 60)>

We can set and plot the detector grid on one of the EBSD patterns, also coloring one or more of the grid tiles red, green and blue, as is done in [Nolze2017], by calling plot_grid():

Nolze2017

G. Nolze, R. Hielscher, A. Winkelmann, “Electron backscatter diffraction beyond the mainstream,” Crystal Research and Technology 52(1) (2017), doi: https://doi.org/10.1002/crat.201600252.

>>> vbse_gen.grid_shape
(5, 5)
>>> vbse_gen.grid_shape = (10, 10)
>>> red = [(7, 1), (8, 1), (8, 2), (9, 1), (9, 2)]
>>> green = [(8, 4), (8, 5), (9, 4), (9, 5)]
>>> blue = [(7, 8), (8, 7), (8, 8), (9, 7), (9, 8)]
>>> p = vbse_gen.plot_grid(
...     rgb_channels=[red, green, blue],
...     visible_indices=True,  # Default
...     pattern_idx=(100, 87),  # Default is (0, 0)
... )
>>> p
<EBSD, title: Pattern, dimensions: (|60, 60)>

As shown above, whether to show the grid tile indices or not is controlled with the visible_indices argument, and which signal pattern to superimpose the grid upon is controlled with the pattern_idx parameter.

_images/plot_grid.jpg

Fig. 5 Detector grid tiles, with tiles to be used for creating an RGB image colored red, green and blue.

To obtain an RGB image from the detector grid tiles shown above, we use get_rgb_image() (see the docstring for all available parameters):

>>> vbse_rgb_img = vbse_gen.get_rgb_image(r=red, g=green, b=blue)
>>> vbse_rgb_img
<VirtualBSEImage, title: , dimensions: (|200, 149)>
>>> vbse_rgb_img.plot()
_images/rgb_image.jpg

Fig. 6 An RGB image formed from coloring three grey scale virtual BSE images red, green and blue.

To obtain one grey scale virtual BSE image from each grid tile, we use get_images_from_grid():

>>> vbse_imgs = vbse_gen.get_images_from_grid()
>>> vbse_imgs
<VirtualBSEImage, title: , dimensions: (5, 5|200, 149)>
>>> vbse_imgs.plot()
_images/images.jpg

Fig. 7 25 grey scale virtual BSE images, one from each tile in a (5, 5) detector grid.

It might be desirable to normalize or scale the intensities in the images, as shown e.g. in Fig. 9 in [Wright2015b]. This can be done with rescale_intensity() or normalize_intensity():

Wright2015b

S. I. Wright, M. M. Nowell, R. De Kloe, P. Camus, T. Rampton, “Electron imaging with an EBSD detector,” Ultramicroscopy 148 (2015), doi: http://dx.doi.org/10.1016/j.ultramic.2014.10.002.

>>> vbse_imgs.data.dtype
dtype('float32')
>>> print(vbse_imgs.data.min(), vbse_imgs.data.max())
5629.0 31810.0
>>> vbse_imgs.rescale_intensity()
Rescaling the image intensities:
[########################################] | 100% Completed |  0.3s
>>> print(vbse_imgs.data.min(), vbse_imgs.data.max())
-1.0 1.0

To obtain a rectangular ROI from the grid, we can use roi_from_grid():

>>> roi = vbse_gen.roi_from_grid((3, 3))  # (Row, column)
>>> roi
RectangularROI(left=18, top=18, right=24, bottom=24)