Restoration of Hyperspectral Astronomical Data with Spectrally Varying Blur

F. Soulez; E. Thiébaut; L. Denis

doi:10.1051/eas/1359018

All issues

Volume 59 (2013)

EAS Publications Series, 59 (2013) 403-416

Abstract

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

New Concepts in Imaging: Optical and Statistical Models
D. Mary, C. Theys and C. Aime (eds)
EAS Publications Series, 59 (2013) 403-416

Restoration of Hyperspectral Astronomical Data with Spectrally Varying Blur

F. Soulez¹, E. Thiébaut¹ and L. Denis²

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

Abstract

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.