OCEAN FRONT DETECTION FROM SAR IMAGERY USING SLIC SUPERPIXEL SEGMENTATION METHOD

被引：0

作者：

Xu, Xuefeng ^{[1
,2
]}

Du, Yanlei ^{[1
,3
]}

Cui, Guangxi ^{[1
,2
]}

Yang, Xiaofeng ^{[1
,3
]}

机构：

[1] Chinese Acad Sci, Aerosp Informat Res Inst, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China

[2] Univ Chinese Acad Sci, Beijing 100049, Peoples R China

[3] Key Lab Earth Observat Hainan Prov, Sanya 572029, Peoples R China

来源：

2022 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2022) | 2022年

关键词：

Synthetic aperture radar; simple linear iterative clustering (SLIC); ocean front; superpixel;

D O I：

10.1109/IGARSS46834.2022.9884664

中图分类号：

P [天文学、地球科学];

学科分类号：

07 ;

摘要：

Ocean front can influent the distribution of sea material and it has an impact on underwater acoustic communication. Thus, the detection of ocean front is very important. In this paper, the simple linear iterative clustering (SLIC) superpixel segmentation approach is applied to ocean front detection in SAR images, which can suppress the influence of coherent speckle noise and extract the fuzzy boundary from high-resolution SAR images. The results show that this method can extract ocean front with one pixel width and the extraction of ocean front is in good agreement with human visual interpretation. This method provides a new idea to extract ocean fronts from SAR images.

引用

页码：2578 / 2581

页数：4

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