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

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Abstract

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.

Author

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

Journal

Astronomy & Astrophysics

Paper Publication Date

March 2015

Paper Type

Astrostatistics