Building Extraction from Remotely Sensed Images by Integrating Saliency Cue

doi:10.1109/JSTARS.2016.2603184

CORC > 自动化研究所 > 中国科学院自动化研究所 > 模式识别国家重点实验室 > 多媒体计算与图形学团队

	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
刊名	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
关键词	Buildings Fully Connected Conditional Random Field (Crf) Saliency
DOI	10.1109/JSTARS.2016.2603184
文献子类	Article
英文摘要	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.
WOS关键词	AUTOMATED DETECTION ; OBJECT RECOGNITION ; VISUAL-ATTENTION ; FRAMEWORK
WOS研究方向	Engineering ; Physical Geography ; Remote Sensing ; Imaging Science & Photographic Technology
语种	英语
WOS记录号	WOS:000395876100010
资助机构	National Natural Science Foundation of China(61331018 ; National High-Tech Research and Development Program of China (863 Program)(2015AA016402) ; 61620106003 ; 91338202 ; 61502490 ; 61671451)
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/12296]
专题	自动化研究所_模式识别国家重点实验室_多媒体计算与图形学团队
通讯作者	Xiaopeng Zhang
作者单位	Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
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.