Synthetic aperture radar oil spills detection based on morphological characteristics

被引:10
|
作者
Lia, Yu [1 ,2 ,3 ,4 ]
Zhanga, Yuanzhi [1 ,2 ,3 ,4 ,5 ]
机构
[1] Chinese Univ Hong Kong, Inst Space & Earth Informat Sci, Hong Kong, Hong Kong, Peoples R China
[2] Chinese Univ Hong Kong, Shenzhen Res Inst, Hong Kong, Hong Kong, Peoples R China
[3] Chinese Univ Hong Kong, Inst Space & Earth Informat Sci, Shenzhen, Peoples R China
[4] Chinese Univ Hong Kong, Shenzhen Res Inst, Shenzhen, Peoples R China
[5] Chinese Acad Sci, Natl Astron Observ, Beijing 100012, Peoples R China
基金
美国国家科学基金会;
关键词
synthetic aperture radar (SAR); oil spill; classification; support vector machine (SVM);
D O I
10.1080/10095020.2014.883109
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
In recent years, oil spills in coastal regions have received a lot of public concern for its strong impact on the coastal ecological system. Synthetic aperture radar (SAR) is regarded as one of the most suitable sensors for oil spill monitoring for its wide-area and all-day all-weather surveillance capabilities. However, due to its special imaging mechanism, multiplicative speckle noise and dark patches caused by other physical phenomena always affect the accuracy of oil spill detection. In this work, an oil spill detection method based on dual-threshold segmentation and support vector machine was proposed. Experiments on SAR images illustrated the effectiveness of the proposed method in detecting and tracing oil spill from SAR images.
引用
收藏
页码:8 / 16
页数:9
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