SPoCA¶

About SPoCA¶

The Spatial Possibilistic Clustering Algorithm (SPoCA) produces a segmentation of EUV solar images into regions named here `classes' corresponding to Active Regions (AR), Coronal Holes (CH), and the Quiet Sun (QS). SPoCA uses a multi-channel unsupervised spatially-constrained fuzzy clustering procedure, where the classes are determined by minimization of intra-class variance.

SPoCA has been developed and maintained by the Royal Observatory of Belgium (ROB).

SPoCA web page at ROC is accessible here : http://sdoatsidc.oma.be/web/sdoatsidc/SoftwareSPoCA.

SPoCA code source¶

SPoCA is mainly developed using C++.

The source code is available from GitHub : https://github.com/bmampaey/SPoCA

SPoCA in HELIO¶

The HELIO HFC runs an instance of SPoCA at the Observatoire de Paris.

A wrapper has been developed by the HFC team in order to automatically call SPoCA using the HFC output standard formats.

The source code of the SPoCA wrapper for the HFC can be found in GitHub at : https://github.com/HELIO-HFC/SPoCA