Bregman Approach to Single Image De-Raining
| dc.contributor.author | Szirmay-Kalos, Laszlo | en_US |
| dc.contributor.author | Tóth, Márton | en_US |
| dc.contributor.editor | Theisel, Holger and Wimmer, Michael | en_US |
| dc.date.accessioned | 2021-04-09T18:20:27Z | |
| dc.date.available | 2021-04-09T18:20:27Z | |
| dc.date.issued | 2021 | |
| dc.description.abstract | Surveillance cameras are expected to work also in bad visibility conditions, which requires algorithmic solutions to improve the captured image and to eliminate image degradation caused by these weather conditions. Algorithms for such tasks belong to the field of computational photography and have been successful in eliminating haze, fog, motion blur, etc. This paper presents a simple algorithm to suppress rain or snow from single images. The algorithm uses energy minimization, and we propose a novel data term and a Bregman distance based regularization term reflecting the particular properties of precipitation. | en_US |
| dc.description.sectionheaders | Imaging and Video | |
| dc.description.seriesinformation | Eurographics 2021 - Short Papers | |
| dc.identifier.doi | 10.2312/egs.20211017 | |
| dc.identifier.isbn | 978-3-03868-133-5 | |
| dc.identifier.issn | 1017-4656 | |
| dc.identifier.pages | 33-36 | |
| dc.identifier.uri | https://doi.org/10.2312/egs.20211017 | |
| dc.identifier.uri | https://diglib.eg.org:443/handle/10.2312/egs20211017 | |
| dc.publisher | The Eurographics Association | en_US |
| dc.title | Bregman Approach to Single Image De-Raining | en_US |
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