Road Extraction Via Adpative Graph Cuts with Multiple Features
文献类型：会议论文
| 作者 | Cheng GL(程光亮) ; Wang Y(王颖); Zhu FY(朱飞云); Pan CH(潘春洪)
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| 出版日期 | 2014 |
| 会议日期 | 2014年10月 |
| 会议地点 | 法国巴黎 |
| 关键词 | Road Extraction Adaptive Graph Cuts Multiple Spatially Contextual Feature |
| 英文摘要 | Accurate road extraction from complex backgrounds plays a fundamental role in a wide range of remote sensing applications. There are two shortcomings for the existing methods: 1) Most of them ignore the spatially contextual information inherent in images; 2) Few existing methods show robustness to the occlusions of cars or trees. To address these two problems, we propose a novel approach via adaptive graph cuts with multiple features. Specifically, for the former problem, we apply multiple features (spectral feature, spatial feature and gradient feature) to obtain not only the spectral characteristic but also the spatially contextual feature. In this way, the structural information of road network can be effectively captured. For the latter, adaptive graph cuts based algorithm is adopted. These two schemes show better performance than state-of-the-art methods under the conditions of occlusions. Experiments on 25 images indicate the validity and effectiveness of our method by comparing with state-of-the-art approaches |
| 源URL | [http://ir.ia.ac.cn/handle/173211/14536]  |
| 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 GL,Wang Y,Zhu FY,et al. Road Extraction Via Adpative Graph Cuts with Multiple Features[C]. 见:. 法国巴黎. 2014年10月. |
入库方式： OAI收割
来源：自动化研究所
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