Belkin-O’Reilly Algorithm#

A contextual median filter that avoids smoothing fine structures. Based on Belkin & O’Reilly (2009).

Definition#

The BOA is a 3x3 median filter that is applied only if:

  • the central pixel is not a 5-peak

  • and the central pixel is a 3-peak

The central pixel is a 5-peak if its value is a maximum or minimum along four 5-points 1D slices of the surrounding 5x5 window (east-west, north-south, diagonals). The central pixel is a 3-peak if its value is a maximum or minimum in the surrounding 3x3 window.

Note

Despite what could be understood from the figure 8 of Belkin & O’Reilly (2009), the algorithm does not filter out lonely, aberrant pixels. If your data has such kind of noise, consider the Contextual Median Filter.

Functions#

Supported types and requirements#

Supported input types: Numpy, Dask, Xarray

Requirements:

  • numpy

  • numba

Other implementations#

Language

Notes

boar

R

pyBOA

Pure Python (Xarray)

This is pure Python but is written in a way that should prove efficient

JUNO

Pure Python (Xarray, Pandas)

This is pure Python and may be slow

boac

C

References#

[belkin_2009]

Belkin, I. M. and O’Reilly, J. E.: “An algorithm for oceanic front detection in chlorophyll and SST satellite imagery“, J. Marine Syst., 78, 319–326, DOI:10.1016/j.jmarsys.2008.11.018, 2009

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