| Issue |
EAS Publications Series
Volume 59, 2013
New Concepts in Imaging: Optical and Statistical Models
|
|
|---|---|---|
| Page(s) | 403 - 416 | |
| Section | Statistical Models in Signal and Image Processing | |
| DOI | https://doi.org/10.1051/eas/1359018 | |
| Published online | 13 March 2013 | |
D. Mary, C. Theys and C. Aime (eds)
EAS Publications Series, 59 (2013) 403-416
Restoration of Hyperspectral Astronomical Data with Spectrally Varying Blur
1
Université de Lyon, 69003 Lyon, France; Université Lyon 1,
Observatoire de Lyon, 9 avenue
Charles André, 69230
Saint-Genis Laval,
France ; CNRS, UMR 5574, Centre de Recherche
Astrophysique de Lyon; École Normale Supérieure de Lyon, 69007
Lyon,
France
2
Université de Lyon, 42023
Saint-Etienne,
France, CNRS, UMR 5516, Laboratoire Hubert
Curien, 42000
Saint-Etienne,
France, Université de Saint-Etienne,
Jean Monnet, 42000
Saint-Etienne,
France
In this paper we present a method for hyper-spectral image restoration for integral field spectrographs (IFS) data. We specifically address two topics: (i) the design of a fast approximation of spectrally varying operators and (ii) the comparison between two kind of regularization functions: quadratic and spatial sparsity functions. We illustrate this method with simulations coming from the Multi Unit Spectroscopic Explorer (MUSE) instrument. It shows the clear increase of the spatial resolution provided by our method as well as its denoising capability.
© EAS, EDP Sciences 2013