학술논문

Source separation algorithms for the analysis of hyper-spectral observations of very small interstellar dust particles
Document Type
Conference
Source
2009 First Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2009. WHISPERS '09. First Workshop on. :1-4 Aug, 2009
Subject
Computing and Processing
Signal Processing and Analysis
Source separation
Algorithm design and analysis
Hyperspectral imaging
Blind source separation
Sparse matrices
Hydrocarbons
Infrared spectra
Telescopes
Chemicals
Signal analysis
Source Separation Methods
Infrared Spectroscopy
Interstellar Medium
Language
ISSN
2158-6268
2158-6276
Abstract
The mid-infrared (mid-IR) spectrum of our galaxy is dominated by continuum and band emission due to carbonaceous very small dust particles amongst which are polycyclic aromatic hydrocarbon (PAH) molecules. Because they absorb the UV photons of massive stars and re-emit this energy in the infrared, IR spectro-imaging of extended interstellar (or circumstellar) regions is a powerful tool to diagnose the nature of these particles together with the local physical conditions. In this paper, we review how the applications of blind / bayesian source separation (BSS) methods applied to mid-IR hyperspectral data can help analyzing these data. We then discuss, in the light of simulations in progress, how BSS methods could be used to identify specific PAH molecules in the interstellar medium when applied to the hyper-spectral data of forthcoming IR telescopes (Herschel, SOFIA, SPICA).