A Clearer Picture of Total Variation Blind Deconvolution

Perrone, Daniele; Favaro, Paolo (2015). A Clearer Picture of Total Variation Blind Deconvolution. IEEE transactions on pattern analysis and machine intelligence, 38(6), pp. 1041-1055. IEEE Computer Society 10.1109/TPAMI.2015.2477819

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Blind deconvolution is the problem of recovering a sharp image and a blur kernel from a noisy blurry image. Recently, there has been a significant effort on understanding the basic mechanisms to solve blind deconvolution. While this effort resulted in the deployment of effective algorithms, the theoretical findings generated contrasting views on why these approaches worked. On the one hand, one could observe experimentally that alternating energy minimization algorithms converge to the desired solution. On the other hand, it has been shown that such alternating minimization algorithms should fail to converge and one should instead use a so-called Variational Bayes approach. To clarify this conundrum, recent work showed that a good image and blur prior is instead what makes a blind deconvolution algorithm work. Unfortunately, this analysis did not apply to algorithms based on total variation regularization. In this manuscript, we provide both analysis and experiments to get a clearer picture of blind deconvolution. Our analysis reveals the very reason why an algorithm based on total variation works. We also introduce an implementation of this algorithm and show that, in spite of its extreme simplicity, it is very robust and achieves a performance comparable to the top performing algorithms.

Item Type: Journal Article (Original Article)
Division/Institute: 08 Faculty of Science > Institute of Computer Science (INF) > Computer Vision Group (CVG)
08 Faculty of Science > Institute of Computer Science (INF)
UniBE Contributor: Perrone, Daniele and Favaro, Paolo
Subjects: 000 Computer science, knowledge & systems
500 Science > 510 Mathematics
ISSN: 0162-8828
Publisher: IEEE Computer Society
Language: English
Submitter: Paolo Favaro
Date Deposited: 29 Jun 2016 14:39
Last Modified: 29 Jun 2016 15:08
Publisher DOI: 10.1109/TPAMI.2015.2477819
BORIS DOI: 10.7892/boris.82454
URI: http://boris.unibe.ch/id/eprint/82454

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