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    Felizberta Lo Padilla Tong School of Social SciencesIp Ying To Lee Yu Yee School of Humanities and LanguagesRita Tong Liu School of Business and Hospitality ManagementS.K. Yee School of Health SciencesYam Pak Charitable Foundation School of Computing and Information Sciences
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Deepsea video descattering

Author(s)
Liu, Hui  
Author(s)
Chau, L.-P.
Date Issued
2019
Publisher
Springer
Journal
Multimedia Tools and Applications
Volume
78
Issue
20
Start page
28919
End page
28929
Abstract
This paper presents a new “marine snow” removal method for deepsea videos based on robust temporal-spatial decomposition. For deepsea videos, the contents of adjacent frames are almost identical or change very little except for the rapidly moving “marine snow” as well as noise, indicating that there exists high temporal-spatial correlation between the successive frames. Based on this observation, we first robustly approximate the deepsea video to recover its background using online robust principal component analysis in a sub-video-by-sub-video manner. Since the structure information of background cannot be well preserved during the background modeling, we further extract such information from the approximation error to compensate the obtained background, which is also formulated as a constrained convex optimization problem. The experimental results demonstrate that our proposed method can achieve comparable or even better results than the state of the art approach.
URI
https://repository.sfu.edu.hk/handle/sfu/4114
DOI
10.1007/s11042-017-5474-3
SFU Affiliated Publication
No
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