Road Extraction from VHR Remote-Sensing Imagery via Object Segmentation Constrained by Gabor Features
文献类型：期刊论文
| 作者 | Chen, Li1; Zhu, Qing1; Xie, Xiao2,3; Hu, Han4; Zeng, Haowei1 |
| 刊名 | ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
 |
| 出版日期 | 2018-09-01 |
| 卷号 | 7期号:9页码:21 |
| 关键词 | edge constraints Gabor features object segmentation region growing road extraction shape features |
| ISSN号 | 2220-9964 |
| DOI | 10.3390/ijgi7090362 |
| 英文摘要 | Automatic road extraction from remote-sensing imagery plays an important role in many applications. However, accurate and efficient extraction from very high-resolution (VHR) images remains difficult because of, for example, increased data size and superfluous details, the spatial and spectral diversity of road targets, disturbances (e.g., vehicles, shadows of trees, and buildings), the necessity of finding weak road edges while avoiding noise, and the fast-acquisition requirement of road information for crisis response. To solve these difficulties, a two-stage method combining edge information and region characteristics is presented. In the first stage, convolutions are executed by applying Gabor wavelets in the best scale to detect Gabor features with location and orientation information. The features are then merged into one response map for connection analysis. In the second stage, highly complete, connected Gabor features are used as edge constraints to facilitate stable object segmentation and limit region growing. Finally, segmented objects are evaluated by some fundamental shape features to eliminate nonroad objects. The results indicate the validity and superiority of the proposed method to efficiently extract accurate road targets from VHR remote-sensing images. |
| 资助项目 | National Natural Science Foundation of China[41631174] ; National Natural Science Foundation of China[41701466] |
| WOS研究方向 | Physical Geography ; Remote Sensing |
| 语种 | 英语 |
| WOS记录号 | WOS:000445767900030 |
| 出版者 | MDPI |
| 源URL | [http://210.72.129.5/handle/321005/123181]  |
| 专题 | 中国科学院沈阳应用生态研究所 |
| 通讯作者 | Zhu, Qing; Xie, Xiao |
| 作者单位 | 1.Southwest Jiaotong Univ, Fac Geosci & Environm Engn, Chengdu 611756, Sichuan, Peoples R China 2.Chinese Acad Sci, Inst Appl Ecol, Lab Environm Computat & Sustainabil Liaoning Prov, Shenyang 110016, Liaoning, Peoples R China 3.Nucl Ind Huzhou Engn Investigat Inst, Huzhou 313000, Peoples R China 4.Hong Kong Polytech Univ, Dept Land Surveying & Geoinformat, Hong Kong, Hong Kong, Peoples R China |
| 推荐引用方式 GB/T 7714 | Chen, Li,Zhu, Qing,Xie, Xiao,et al. Road Extraction from VHR Remote-Sensing Imagery via Object Segmentation Constrained by Gabor Features[J]. ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION,2018,7(9):21. |
| APA | Chen, Li,Zhu, Qing,Xie, Xiao,Hu, Han,&Zeng, Haowei.(2018).Road Extraction from VHR Remote-Sensing Imagery via Object Segmentation Constrained by Gabor Features.ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION,7(9),21. |
| MLA | Chen, Li,et al."Road Extraction from VHR Remote-Sensing Imagery via Object Segmentation Constrained by Gabor Features".ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION 7.9(2018):21. |
入库方式： OAI收割
来源：沈阳应用生态研究所
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