2016-06-23
Image reconstruction from sparse samples using directional total variation minimization
Publication
Publication
Presented at the
24th Signal Processing and Communication Application Conference (SIU 2016) (May 2016), Zonguldak, Turkey
This paper considers reconstruction of missing pixels and formulates the problem under directional total variation (DTV) regularization. In order to devise an algorithm, forward-backward splitting method is used as a convex optimization tool, in conjunction with a fast projected gradient-based algorithm. The results are compared with the results of TV-based setting, and the utility of using DTV is shown in terms of accuracy, when an image with a dominant direction is the case.
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| doi.org/10.1109/SIU.2016.7495957 | |
| 24th Signal Processing and Communication Application Conference (SIU 2016) | |
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Demircan Türeyen, E., Kamaşak, M. E., & Bayram, İ. (2016). Image reconstruction from sparse samples using directional total variation minimization. In Proceedings of the Signal Processing and Communication Application Conference. doi:10.1109/SIU.2016.7495957 |
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