Knowledge Commons of Institute of Automation,CAS
Building Extraction from Remotely Sensed Images by Integrating Saliency Cue | |
Li, Er; Xu, Shibiao(共同第一作者); Meng, Weiliang; Zhang, Xiaopeng; Xiaopeng Zhang | |
发表期刊 | IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING |
2016-09-14 | |
卷号 | 10期号:3页码:906-919 |
文章类型 | Article |
摘要 | In this paper, we propose a novel two-step building extraction method from remote sensing images by integrating saliency cue. We first utilize classical features such as shadow, color, and shape to find out initial building candidates. A fully connected conditional random field model is introduced in this step to ensure that most of the buildings are incorporated. While it is hard to further remove the mislabled rooftops from the building candidates by only using classical features, we adopt saliency cue as a new feature to determine whether there is a rooftop in each segmentation patch obtained from previous step. The basic idea behind the use of saliency information is that rooftops are more likely to attract visual attention than surrounding objects. Based on a specifically designed saliency estimation algorithm for building object, we extract saliency cue in the local region of each building candidate, which is integrated into a probabilistic model to get the final building extraction result. We show that the saliency cue can provide an efficient probabilistic indication of the presence of rooftops, which helps to reduce false positives while without increasing false negatives at the same time. Experimental results on two benchmark datasets highlight the advantages of the integration of saliency cue and demonstrate that the proposed method outperforms the stateof- the-art methods. |
关键词 | Buildings Fully Connected Conditional Random Field (Crf) Saliency |
WOS标题词 | Science & Technology ; Technology ; Physical Sciences |
DOI | 10.1109/JSTARS.2016.2603184 |
关键词[WOS] | AUTOMATED DETECTION ; OBJECT RECOGNITION ; VISUAL-ATTENTION ; FRAMEWORK |
收录类别 | SCI |
语种 | 英语 |
项目资助者 | National Natural Science Foundation of China(61331018 ; National High-Tech Research and Development Program of China (863 Program)(2015AA016402) ; 61620106003 ; 91338202 ; 61502490 ; 61671451) |
WOS研究方向 | Engineering ; Physical Geography ; Remote Sensing ; Imaging Science & Photographic Technology |
WOS类目 | Engineering, Electrical & Electronic ; Geography, Physical ; Remote Sensing ; Imaging Science & Photographic Technology |
WOS记录号 | WOS:000395876100010 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/12296 |
专题 | 多模态人工智能系统全国重点实验室_多媒体计算 |
通讯作者 | Xiaopeng Zhang |
作者单位 | Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China |
第一作者单位 | 模式识别国家重点实验室 |
推荐引用方式 GB/T 7714 | Li, Er,Xu, Shibiao,Meng, Weiliang,et al. Building Extraction from Remotely Sensed Images by Integrating Saliency Cue[J]. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING,2016,10(3):906-919. |
APA | Li, Er,Xu, Shibiao,Meng, Weiliang,Zhang, Xiaopeng,&Xiaopeng Zhang.(2016).Building Extraction from Remotely Sensed Images by Integrating Saliency Cue.IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING,10(3),906-919. |
MLA | Li, Er,et al."Building Extraction from Remotely Sensed Images by Integrating Saliency Cue".IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 10.3(2016):906-919. |
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Building Extraction (1646KB) | 期刊论文 | 出版稿 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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