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Dual Smoothing for Marine Oil Spill Segmentation

Ren, Peng, Di, Mengmeng, Song, Huajun, Luo, Chunbo and Grecos, Christos (2016) Dual Smoothing for Marine Oil Spill Segmentation. IEEE Geoscience and Remote Sensing Letters, 13 (1). pp. 82-86. ISSN 1558-0571

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We present a novel marine oil spill segmentation method that characterizes two smoothing modules at the label level and the pixel level separately. At the label level, we exploit the rolling guidance filter for smoothing the label cost volumes. It enables scale-aware labeling and thus alleviates the ambiguous segmentation that blurs the detailed structures of oil spills. At the pixel level, we adapt a cooperative model for smoothing higher order pixel variations, which has the potential of preserving elongated strips that often arise in oil spills. We integrate the two smoothing modules operating at different levels into an energy minimization formulation, which is referred to as dual smoothing. The coupling of the two smoothing modules enables an effective complement to each other such that the specific structures of oil spills are accurately characterized. We compute the optimal labeling of the dual-smoothing framework based on graph cuts. The proposed dual-smoothing framework is especially effective in segmenting elongated and detailed oil spills, and the experimental results demonstrate its advantages over thresholding- and graph-cut-based segmentations.

Item Type: Article
Subjects: Q Science > QA Mathematics > Electronic computers. Computer science
T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science
Q Science > QA Mathematics > Computer software
T Technology > T Technology (General) > Information Technology > Computer software
H Social Sciences > HD Industries. Land use. Labor > Specific Industries > Oil Industry
Divisions: School of Computing > Staff Research and Publications
Depositing User: Caoimhe Ni Mhaicin
Date Deposited: 28 Feb 2019 13:19
Last Modified: 28 Feb 2019 13:19

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