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

By F. M. Ngolè Mboula, J.-L. Starck, S. Ronayette, K. Okumura and J. Amiaux

Abstract

International audienceIn 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

Topics: methods: numerical, techniques: image processing, [ PHYS.ASTR ] Physics [physics]/Astrophysics [astro-ph]
Publisher: EDP Sciences
Year: 2015
DOI identifier: 10.1051/0004-6361
OAI identifier: oai:HAL:cea-01290110v1
Provided by: Hal-Diderot

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