get_image_quality#

EBSD.get_image_quality(normalize: bool = True, show_progressbar: bool | None = None) → ndarray | Array[source]#

Compute the image quality map of patterns in an EBSD scan.

The image quality \(Q\) is calculated based on the procedure defined by Krieger Lassen [Lassen, 1994].

Parameters:

normalize: Whether to normalize patterns to a mean of zero and standard deviation of 1 before calculating the image quality. Default is True.
show_progressbar: Whether to show a progressbar. If not given, the value of hyperspy.api.preferences.General.show_progressbar is used.

Returns:

image_quality_map: Image quality map of same shape as navigation axes. This is a Dask array if the signal is lazy.

See also

kikuchipy.pattern.get_image_quality

Examples

Load an example dataset, remove the static and dynamic background and compute \(Q\)

>>> import kikuchipy as kp
>>> s = kp.data.nickel_ebsd_small()
>>> s
<EBSD, title: patterns Scan 1, dimensions: (3, 3|60, 60)>
>>> s.remove_static_background()
>>> s.remove_dynamic_background()
>>> iq = s.get_image_quality()
>>> iq
array([[0.19935645, 0.16657268, 0.18803978],
       [0.19040637, 0.1616931 , 0.17834103],
       [0.19411428, 0.16031407, 0.18413563]], dtype=float32)

Examples using `EBSD.get_image_quality`#

Neighbour pattern averaging

get_image_quality#

Examples using EBSD.get_image_quality#

Examples using `EBSD.get_image_quality`#