Minimum description length approach for unsupervised spectral unmixing of multiple interfering gas species

Julien Fade (1) , Sidonie Lefebvre (2) , Nicolas Cézard (2)

1 IPR - Institut de Physique de Rennes
2 ONERA - The French Aerospace Lab [Châtillon]

We address an original statistical method for unsupervised identification and concentration estimation of spectrally interfering gas components of unknown nature and number. We show that such spectral unmixing can be efficiently achieved using information criteria derived from the Minimum Description Length (MDL) principle, outperforming standard information criteria such as AICc or BIC. In the context of spectroscopic applications, we also show that the most efficient MDL technique implemented shows good robustness to experimental artifacts.

Mots clés: Spectrum analysis; Air pollution monitoring; Spectroscopy; Absorption; Remote sensing and sensors

Domaines: Optique [physics.optics]; Physique [physics]; Sciences de l'ingénieur [physics]

Julien Fade, Sidonie Lefebvre, Nicolas Cézard. Minimum description length approach for unsupervised spectral unmixing of multiple interfering gas species. Optics Express, 2011, 19 (15), pp.13862-13872. ⟨10.1364/OE.19.013862⟩. ⟨hal-00713618⟩