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ASCL Code Record

[ascl:1805.009] STARBLADE: STar and Artefact Removal with a Bayesian Lightweight Algorithm from Diffuse Emission

STARBLADE (STar and Artefact Removal with a Bayesian Lightweight Algorithm from Diffuse Emission) separates superimposed point-like sources from a diffuse background by imposing physically motivated models as prior knowledge. The algorithm can also be used on noisy and convolved data, though performing a proper reconstruction including a deconvolution prior to the application of the algorithm is advised; the algorithm could also be used within a denoising imaging method. STARBLADE learns the correlation structure of the diffuse emission and takes it into account to determine the occurrence and strength of a superimposed point source.

Code site:
https://gitlab.mpcdf.mpg.de/ift/starblade
Appears in:
http://adsabs.harvard.edu/abs/2018arXiv180405591K
Bibcode:
2018ascl.soft05009K

ascl:1805.009
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