Efficient Marginal Likelihood Optimization in Blind Deconvolution
In blind deconvolution one aims to estimate from an input blurred image y a sharp image x and an unknown blur kernel k. Recent research shows that a key to success is to consider the overall shape of the posterior distribution p(x, k|y) and not only its mode. This leads to a distinction between MAPx...
Main Authors: | Levin, Anat, Weiss, Yair, Durand, Fredo, Freeman, William T. |
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Other Authors: | Fredo Durand |
Published: |
2011
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Online Access: | http://hdl.handle.net/1721.1/62035 |
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