Abstract
Single image blind deconvolution aims to estimate the unknown blur from a single observed blurred image and recover the original sharp image. Such task is severely ill-posed and typical approaches involve some heuristic or other steps without clear mathematical explanation to arrive at an acceptable solution. We show that a straightforward maximum a posteriory estimation combined with very sparse priors and an efficient numerical method can produce results, which compete with much more complicated state-of-the-art methods.
This work was supported by GA UK under grant 938213, by GACR under grant 13-29225S, and by AVCR under grant M100751201.
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Kotera, J., Šroubek, F., Milanfar, P. (2013). Blind Deconvolution Using Alternating Maximum a Posteriori Estimation with Heavy-Tailed Priors. In: Wilson, R., Hancock, E., Bors, A., Smith, W. (eds) Computer Analysis of Images and Patterns. CAIP 2013. Lecture Notes in Computer Science, vol 8048. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40246-3_8
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DOI: https://doi.org/10.1007/978-3-642-40246-3_8
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