Super-resolution method using sparse regularization for point-spread function recovery

F. M. Ngolè Mboula (1) , J.-L. Starck (1) , S. Ronayette (1) , K. Okumura (1) , J. Amiaux (1)

1 AIM (UMR7158 / UMR_E_9005 / UM_112) - Astrophysique Interprétation Modélisation

In large-scale spatial surveys, such as the forthcoming ESA Euclid mission, images may be undersampled due to the optical sensors sizes. Therefore, one may consider using a super-resolution (SR) method to recover aliased frequencies, prior to further analysis. This is particularly relevant for point-source images, which provide direct measurements of the instrument point-spread function (PSF). We introduce SParse Recovery of InsTrumental rEsponse (SPRITE), which is an SR algorithm using a sparse analysis prior. We show that such a prior provides significant improvements over existing methods, especially on low signal-to-noise ratio PSFs.

Keywords: techniques: image processing; methods: numerical

Domains: Physics [physics]; Astrophysics [astro-ph]

F. M. Ngolè Mboula, J.-L. Starck, S. Ronayette, K. Okumura, J. Amiaux. Super-resolution method using sparse regularization for point-spread function recovery. Astronomy and Astrophysics - A&A, 2015, 575, pp.A86. ⟨10.1051/0004-6361/201424167⟩. ⟨cea-01290110⟩