A Variational Approach for Denoising Hyperspectral Images Corrupted by Poisson Distributed Noise
| Affiliation auteurs | !!!! Error affiliation !!!! |
| Titre | A Variational Approach for Denoising Hyperspectral Images Corrupted by Poisson Distributed Noise |
| Type de publication | Conference Paper |
| Year of Publication | 2014 |
| Auteurs | Deger F, Mansouri A, Pedersen M, Hardeberg JYngve, Voisin Y |
| Editor | Elmoataz A, Lezoray O, Nouboud F, Mammass D |
| Conference Name | IMAGE AND SIGNAL PROCESSING, ICISP 2014 |
| Publisher | European Assoc Image & Signal Proc; Int Assoc Pattern Recognit; Inst Univ Technologie; Univ Caen Basse Normandie; ENSICAEN; Ctr Natl Rech Sci; Conseil Reg Basse Normandie; Conseil Gen Manche; Communaut Urbaine Cherbourg |
| Conference Location | HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY |
| ISBN Number | 978-3-319-07998-1; 978-3-319-07997-4 |
| Résumé | Poisson distributed noise, such as photon noise is an important noise source in multi- and hyperspectral images. We propose a variational based denoising approach, that accounts the vectorial structure of a spectral image cube, as well as the poisson distributed noise. For this aim, we extend an approach for monochromatic images, by a regularisation term, that is spectrally and spatially adaptive and preserves edges. In order to take the high computational complexity into account, we derive a Split Bregman optimisation for the proposed model. The results show the advantages of the proposed approach compared to a marginal approach on synthetic and real data. |