DETECTION OF FAINT EXTENDED SOURCES IN HYPERSPECTRAL DATA AND APPLICATION TO HDF-S MUSE OBSERVATIONS

Abstract : Circum-Galactic Medium surrounding galaxies has been punctually detected, but its morphology remains largely unknown. The Multi-Unit Spectroscopic Explorer (MUSE) spectro-imager provides for the first time both spectral and spatial resolution to spatially map such features. The problem lies in the statistical detection of faint spatially-extended sources in massive hyperspectral images such as provided by MUSE, and has not been previously handled. This paper presents a statistical detection method based on hypothesis testing tackling this problem. The proposed strategy is step-by-step validated over alternative ways with simulations. Then, results on MUSE observations are presented.
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Communication dans un congrès
IEEE International Conference on Accoustic, Speech and Signal Processing 2016, Mar 2016, Shanghai, China. IEEE International Conference on Accoustic, Speech and Signal Processing 2016, 〈http://2016.ieeeicassp.org/default.asp〉
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Jean-Baptiste Courbot, Vincent Mazet, Emmanuel Monfrini, Christophe Collet. DETECTION OF FAINT EXTENDED SOURCES IN HYPERSPECTRAL DATA AND APPLICATION TO HDF-S MUSE OBSERVATIONS. IEEE International Conference on Accoustic, Speech and Signal Processing 2016, Mar 2016, Shanghai, China. IEEE International Conference on Accoustic, Speech and Signal Processing 2016, 〈http://2016.ieeeicassp.org/default.asp〉. 〈hal-01266333〉

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