中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
SeNet: Structured Edge Network for Sea--Land Segmentation

文献类型:期刊论文

作者Cheng, Dongcai; Meng, Gaofeng; Cheng, Guangliang; Pan, Chunhong
刊名IEEE Geoscience and Remote Sensing Letters
出版日期2017
期号2页码:247-251
关键词Sea--land Segmentation Deconvolution Network (Deconvnet) Local Smooth Regularization Structured Edge Network (Senet)
英文摘要  Separating an optical remote sensing image into sea  and land areas is very challenging yet of great importance to the coastline extraction and subsequent object detection. Traditional methods based on handcrafted feature extraction and image processing often face dilemma when confronting high resolution remote sensing images for their complicated texture and intensity distribution. In this paper, we apply the prevalent deep convolution neural networks (CNN) to the sea--land segmentation problem and make two innovations on top of the traditional structure: firstly, we propose a local smooth regularization to achieve better spatially consistent results, which frees us from the complicated morphological operations that are commonly used in traditional methods; secondly, we use a multi-task loss to simultaneously obtain the segmentation and edge detection results. The attached structured edge detection branch can further refine the segmentation result and dramatically improve edge accuracy. Experiments  on a set of natural-colored images from Google Earth demonstrate the effectiveness of our approach in terms of quantitative and visual performances compared with state-of-the-art methods.
源URL[http://ir.ia.ac.cn/handle/173211/15514]  
专题自动化研究所_模式识别国家重点实验室_遥感图像处理团队
作者单位中国科学院自动化研究所
推荐引用方式
GB/T 7714
Cheng, Dongcai,Meng, Gaofeng,Cheng, Guangliang,et al. SeNet: Structured Edge Network for Sea--Land Segmentation[J]. IEEE Geoscience and Remote Sensing Letters,2017(2):247-251.
APA Cheng, Dongcai,Meng, Gaofeng,Cheng, Guangliang,&Pan, Chunhong.(2017).SeNet: Structured Edge Network for Sea--Land Segmentation.IEEE Geoscience and Remote Sensing Letters(2),247-251.
MLA Cheng, Dongcai,et al."SeNet: Structured Edge Network for Sea--Land Segmentation".IEEE Geoscience and Remote Sensing Letters .2(2017):247-251.

入库方式: OAI收割

来源:自动化研究所

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