Knowledge Commons of Institute of Automation,CAS
Sea--Land Segmentation Via Hierarchical Region Merging and Edge Directed Graph Cut | |
Cheng, Dongcai; Meng, Gaofeng; Pan, Chunhong | |
2016 | |
会议名称 | International Conference on Image Processing |
会议日期 | September 25-28, 2016 |
会议地点 | Phoenix, Arizona, USA |
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. In this paper, we propose a hierarchical region merging approach to automatically extract the sea area and employ edge directed graph cut (GC) to accomplish the final segmentation. Firstly, an image is segmented into superpixels and a graph-based merging method is employed to extract the maximum area of sea region (MASR). Then the non-connected sea regions are identified by measuring the distance between their superpixels and the MASR. When modelling the pairwise term in GC, we incorporate edge information between neighboring superpixels to reduce under--segmentation. Experimental results on a set of challenging images demonstrate the effectiveness of our method by comparing it with the state-of-the-art approaches. |
关键词 | Sea--land Segmentation Hierarchical Region Merging Maximum Area Of Sea Region (Masr) K-means Edge Directed Graph Cut (Gc) |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/15516 |
专题 | 多模态人工智能系统全国重点实验室_先进时空数据分析与学习 |
作者单位 | 中国科学院自动化研究所 |
第一作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Cheng, Dongcai,Meng, Gaofeng,Pan, Chunhong. Sea--Land Segmentation Via Hierarchical Region Merging and Edge Directed Graph Cut[C],2016. |
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Sea--Land Segmentati(919KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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