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Blind deconvolution of turbulence-degraded images using natural PSF priors

: Baena Gallé, Roberto; Gladysz, Szymon; Mugnier, Laurent; Gudimetla, Rao; Johnson, Robert L.; Kann, Lee

Fulltext urn:nbn:de:0011-n-3201718 (343 KByte PDF)
MD5 Fingerprint: a167df13ce8b8dc55d461643a0d16a0c
Created on: 14.1.2015

Optical Society of America -OSA-, Washington/D.C.:
Signal Recovery and Synthesis : Seattle, Washington United States July 13-17, 2014
Washington, DC: OSA, 2014
ISBN: 978-1-55752-308-2
3 pp.
Conference "Signal Recovery and Synthesis" <2014, Seattle/Wash.>
Conference Paper, Electronic Publication
Fraunhofer IOSB ()

Deconvolution of images taken through atmospheric turbulence often requires regularization in order to prevent the restoration algorithm over-fitting the noisy observation. For this purpose many object priors have been proposed but their utility might be limited to one class of real objects. Optical effects of atmospheric turbulence are well understood and therefore priors on the point-spread function form a viable alternative. We show their usefulness.