BLIND DECONVOLUTION OF VIDEO SEQUENCES

Ferréol Soulez (1, 2) , Éric Thiébaut (1) , Yves Tourneur (3) , Alain Gressard (4) , Raphaël Dauphin (4)

1 CRAL - Centre de Recherche Astrophysique de Lyon
2 LHC - Laboratoire Hubert Curien
3 Centre Commun de Quantimétrie
4 Service de Cardiologie de l'hopital de la Croix Rousse

We present a new blind deconvolution method for video sequence. It is derived following an inverse problem approach in a Bayesian framework. This method exploits the temporal continuity of both object and PSF. Combined with edge-preserving spatial regularization, a temporal regularization constrains the blind deconvolution problem, improving its effectiveness and its robustness. We demonstrate these improvements by processing various real video sequences obtained by different imaging techniques.

Domains: Computer Science [cs]; Signal and Image Processing; Engineering Sciences [physics]; Signal and Image processing

Ferréol Soulez, Éric Thiébaut, Yves Tourneur, Alain Gressard, Raphaël Dauphin. BLIND DECONVOLUTION OF VIDEO SEQUENCES. 15th International Conférence on Image Processing, Oct 2008, San Diego, United States. pp.0. ⟨ujm-00293656⟩