Computer Science
Scientific paper
Nov 2000
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2000spie.4123...73l&link_type=abstract
Proc. SPIE Vol. 4123, p. 73-83, Image Reconstruction from Incomplete Data, Michael A. Fiddy; Rick P. Millane; Eds.
Computer Science
Scientific paper
The atmosphere introduces random distortions to propagating wavefronts, resulting in speckled images at ground based telescopes. Blind deconvolution seeks to solve this problem of reconstructing the object and the atmospheric point spread function simultaneously. Due to the ill-posed nature of the problem, the quality of the reconstructions depends strongly on the available a priori information, with a tradeoff between the potential accuracy of the solution and the ease of obtaining it. We investigate the different a priori assumptions that can be made and compare their effectiveness in contrasting the solution.
Lane Richard G.
Leung W.-Y. V.
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