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Online blind deconvolution for astronomical imaging
Atmospheric turbulences blur astronomical images taken by earth-based telescopes. Taking many short-time exposures in such a situation provides noisy images of the same object, where each noisy image has a different blur. Commonly astronomers apply a technique called “Lucky Imaging” that selects a few of the recorded frames that fulfill certain criteria, such as reaching a certain peak intensity (“Strehl ratio”). The selected frames are then averaged to obtain a better image. In this paper we introduce and analyze a new method that exploits all the frames and generates an improved image in an online fashion. Our initial experiments with controlled artificial data and real-world astronomical datasets yields promising results.
@inproceedings{5649, title = {Online blind deconvolution for astronomical imaging}, journal = {Proceedings of the First IEEE International Conference Computational Photography (ICCP 2009)}, abstract = {Atmospheric turbulences blur astronomical images taken by earth-based telescopes. Taking many short-time exposures in such a situation provides noisy images of the same object, where each noisy image has a different blur. Commonly astronomers apply a technique called “Lucky Imaging” that selects a few of the recorded frames that fulfill certain criteria, such as reaching a certain peak intensity (“Strehl ratio”). The selected frames are then averaged to obtain a better image. In this paper we introduce and analyze a new method that exploits all the frames and generates an improved image in an online fashion. Our initial experiments with controlled artificial data and real-world astronomical datasets yields promising results.}, pages = {1-7}, publisher = {IEEE}, organization = {Max-Planck-Gesellschaft}, school = {Biologische Kybernetik}, address = {Piscataway, NJ, USA}, month = apr, year = {2009}, slug = {5649}, author = {Harmeling, S. and Hirsch, M. and Sra, S. and Sch{\"o}lkopf, B.}, month_numeric = {4} }