rhef#

sunkit_image.radial.rhef(smap, *, radial_bin_edges=None, application_radius=<Quantity 0. solRad>, upsilon=0.35, method='numpy', vignette=None, progress=False, fill=nan)[source]#

Implementation of the Radial Histogram Equalizing Filter (RHEF).

The filter works as follows:

Radial Histogram Equalization is a simple algorithm for removing the radial gradient to reveal coronal structure. It also significantly improves the visualization of high dynamic range solar imagery. RHE takes the input map and bins the pixels by radius, then ranks the elements in each bin sequentially and normalizes the set to 1.

Note

The returned maps have their plot_settings changed to remove the extra normalization step.

Parameters:

  • smap (sunpy.map.Map) – The SunPy map to enhance using the RHEF algorithm.

  • radial_bin_edges (astropy.units.Quantity, optional) – A two-dimensional array of bin edges of size [2, nbins] where nbins is the number of bins. These define the radial segments where filtering is applied. If None, radial bins will be generated automatically.

  • application_radius (astropy.units.Quantity, optional) – The radius above which to apply the RHEF. Only regions with radii above this value will be filtered. Defaults to 0 solar radii.

  • upsilon (float or None, optional) – A double-sided gamma function to apply to modify the equalized histograms. Defaults to 0.35.

  • method ({"inplace", "numpy", "scipy"}, optional) – Method used to rank the pixels for equalization. Defaults to ‘inplace’.

  • vignette (astropy.units.Quantity, optional) – Radius beyond which pixels will be set to NaN. Must be in units that are compatible with “R_sun” as the value will be transformed. Defaults to None.

  • progress (bool, optional) – Show a progressbar while computing. Defaults to False.

  • fill (Any, optional) – The value to be placed outside of the bounds of the algorithm. Defaults to NaN.

Returns:

sunpy.map.Map – A SunPy map with the Radial Histogram Equalizing Filter applied to it.

References

  • Gilly & Cranmer 2024, in prep.

  • The implementation is highly inspired by this doctoral thesis: Gilly, G. Spectroscopic Analysis and Image Processing of the Optically-Thin Solar Corona https://www.proquest.com/docview/2759080511

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