Abstract
We present a novel method for removing rain streaks from a single input image by decomposing it into a rain-free background layer B and a rain-streak layer R. A joint optimization process is used that alternates between removing rain-streak details from B and removing non-streak details from R. The process is assisted by three novel image priors. Observing that rain streaks typically span a narrow range of directions, we first analyze the local gradient statistics in the rain image to identify image regions that are dominated by rain streaks. From these regions, we estimate the dominant rain streak direction and extract a collection of rain-dominated patches. Next, we define two priors on the background layer B, one based on a centralized sparse representation and another based on the estimated rain direction. A third prior is defined on the rain-streak layer R, based on similarity of patches to the extracted rain patches. Both visual and quantitative comparisons demonstrate that our method outperforms the state-of-the-art.
Original language | American English |
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Title of host publication | Proceedings - 2017 IEEE International Conference on Computer Vision, ICCV 2017 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 2545-2553 |
Number of pages | 9 |
ISBN (Electronic) | 9781538610329 |
DOIs | |
State | Published - 22 Dec 2017 |
Event | 16th IEEE International Conference on Computer Vision, ICCV 2017 - Venice, Italy Duration: 22 Oct 2017 → 29 Oct 2017 |
Publication series
Name | Proceedings of the IEEE International Conference on Computer Vision |
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Volume | 2017-October |
ISSN (Print) | 1550-5499 |
Conference
Conference | 16th IEEE International Conference on Computer Vision, ICCV 2017 |
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Country/Territory | Italy |
City | Venice |
Period | 22/10/17 → 29/10/17 |
Bibliographical note
Funding Information:We thank reviewers for the valuable comments. This work was supported in part by the 973 Program (2015CB351706), the Shenzhen Science and Technology Program (JCYJ20170413162617606 and JCYJ20170413162256793), the National Natural Science Foundation of China (61233012), the Israel Science Foundation (ISF grant No. 2366/16), and the ISF-NSFC joint research program (grant No. 2217/15).
Publisher Copyright:
© 2017 IEEE.