A novel remote sensing image retrieval method based on visual salient point features
文献类型：期刊论文
| 作者 | Wang, Xing1; Shao, Zhenfeng2; Zhou, Xiran2; Liu, Jun3 |
| 刊名 | SENSOR REVIEW
 |
| 出版日期 | 2014 |
| 卷号 | 34期号:4页码:349-359 |
| 关键词 | Image retrieval Image key points Remote sensing images Visual attention models |
| ISSN号 | 0260-2288 |
| DOI | 10.1108/SR-03-2013-640 |
| 通讯作者 | Shao, ZF (reprint author), Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430072, Peoples R China. |
| 英文摘要 | Purpose - This paper aims to present a novel feature design that is able to precisely describe salient objects in images. With the development of space survey, sensor and information acquisition technologies, more complex objects appear in high-resolution remote sensing images. Traditional visual features are no longer precise enough to describe the images. Design/methodology/approach - A novel remote sensing image retrieval method based on VSP (visual salient point) features is proposed in this paper. A key point detector and descriptor are used to extract the critical features and their descriptors in remote sensing images. A visual attention model is adopted to calculate the saliency map of the images, separating the salient regions from the background in the images. The key points in the salient regions are then extracted and defined as VSPs. The VSP features can then be constructed. The similarity between images is measured using the VSP features. Findings - According to the experiment results, compared with traditional visual features, VSP features are more precise and stable in representing diverse remote sensing images. The proposed method performs better than the traditional methods in image retrieval precision. Originality/value - This paper presents a novel remote sensing image retrieval method based on VSP features. |
| 资助项目 | National Basic Research Program of China[2010CB731800] ; National Science and Technology Specific Projects[2012YQ16018505] ; National Science and Technology Specific Projects[2013BAH42F03] ; National Natural Science Foundation of China[61172174] ; Program for New Century Excellent Talents in University[NCET-12-0426] ; Fundamental Research Fund for the Central Universities[201121302020008] ; Program for Luojia young scholars of Wuhan University |
| WOS研究方向 | Instruments & Instrumentation |
| 语种 | 英语 |
| WOS记录号 | WOS:000342049500003 |
| 出版者 | EMERALD GROUP PUBLISHING LIMITED |
| 源URL | [http://119.78.100.138/handle/2HOD01W0/744]  |
| 专题 | 中国科学院重庆绿色智能技术研究院 |
| 通讯作者 | Shao, Zhenfeng |
| 作者单位 | 1.Wuhan Univ, Sch Remote Sensing & Informat Engn, Wuhan 430072, Peoples R China 2.Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430072, Peoples R China 3.Chinese Acad Sci, Chongqing Inst Green & Intelligent Technol, Chongqing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Wang, Xing,Shao, Zhenfeng,Zhou, Xiran,et al. A novel remote sensing image retrieval method based on visual salient point features[J]. SENSOR REVIEW,2014,34(4):349-359. |
| APA | Wang, Xing,Shao, Zhenfeng,Zhou, Xiran,&Liu, Jun.(2014).A novel remote sensing image retrieval method based on visual salient point features.SENSOR REVIEW,34(4),349-359. |
| MLA | Wang, Xing,et al."A novel remote sensing image retrieval method based on visual salient point features".SENSOR REVIEW 34.4(2014):349-359. |
入库方式： OAI收割
来源：重庆绿色智能技术研究院
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