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Proceedings Paper

Blind deconvolution of images with model discrepancies using maximum a posteriori estimation with heavy-tailed priors
Author(s): Jan Kotera; Filip Šroubek
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Paper 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 straight- forward maximum a posteriori estimation incorporating sparse priors and mechanism to deal with boundary artifacts, combined with an efficient numerical method can produce results which compete with or outperform much more complicated state-of-the-art methods. Our method is naturally extended to deal with overexposure in low-light photography, where linear blurring model is violated.

Paper Details

Date Published: 27 February 2015
PDF: 12 pages
Proc. SPIE 9404, Digital Photography XI, 94040B (27 February 2015); doi: 10.1117/12.2077158
Show Author Affiliations
Jan Kotera, Institute of Information Theory and Automation (Czech Republic)
Charles Univ. in Prague (Czech Republic)
Filip Šroubek, Institute of Information Theory and Automation (Czech Republic)

Published in SPIE Proceedings Vol. 9404:
Digital Photography XI
Nitin Sampat; Radka Tezaur; Dietmar Wüller, Editor(s)

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