A BLIND DEBLURRING AND IMAGE DECOMPOSITION APPROACH FOR ASTRONOMICAL IMAGE RESTORATION

Rahul Mourya (1) , Loïc Denis (1) , Jean-Marie Becker (1) , Éric Thiébaut (2)

1 LHC - Laboratoire Hubert Curien
2 CRAL - Centre de Recherche Astrophysique de Lyon

With the progress of adaptive optics systems, ground-based telescopes acquire images with improved resolutions. However, compensation for atmospheric turbulence is still partial, which leaves good scope for digital restoration techniques to recover fine details in the images. A blind image deblurring algorithm for a single long-exposure image is proposed, which is an instance of maximum-a-posteriori estimation posed as constrained non-convex optimization problem. A view of sky contains mainly two types of sources: point-like and smooth extended sources. The algorithm takes into account this fact explicitly by imposing different priors on these components, and recovers two separate maps for them. Moreover, an appropriate prior on the blur kernel is also considered. The resulting optimization problem is solved by alternating minimization. The initial experimental results on synthetically corrupted images are promising, the algorithm is able to restore the fine details in the image, and recover the point spread function.

Mots clés: Astronomical imaging; blind image deblurring; non-convex optimization; alternate minimization; Huber function; ADMM

Domaines: Traitement des images [eess.IV]; Traitement du signal et de l'image [eess.SP]

Rahul Mourya, Loïc Denis, Jean-Marie Becker, Éric Thiébaut. A BLIND DEBLURRING AND IMAGE DECOMPOSITION APPROACH FOR ASTRONOMICAL IMAGE RESTORATION. European Conference on Signal Processing 2015, Aug 2015, Nice, France. ⟨hal-01219248⟩