ROBUST VHR IMAGE CHANGE DETECTION BASED ON LOCAL FEATURES AND MULTI-SCALE FUSION

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 先进时空数据分析与学习

	ROBUST VHR IMAGE CHANGE DETECTION BASED ON LOCAL FEATURES AND MULTI-SCALE FUSION
	Xu, Yuan; Huo, Chunlei; Xiang, Shiming; Pan, Chunhong; Xu Yuan
	2013
会议名称	2013 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP)
会议录名称	IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
页码	1991-1995
会议日期	2013
会议地点	Vancouver
摘要	Urban change detection of Very High Resolution (VHR) remote sensing images is challenging, due to the ill-posed nature of change detection problem, the inherent nature of VHR image, the complex morphology of urban scenes, etc. To address the above difficulties, a robust approach is proposed, which is based on discriminative local features, robust distance metric and novel multi-scale fusion strategy. By integrating these components synergistically, the proposed approach is superior to the traditional approaches in capturing semantic changes and removing the false changes. Comparative experiments demonstrate the effectiveness and advantages of the proposed approach.
关键词	Change Detection Vhr Image Local Features Belief Propagation Multi-scale Fusion
收录类别	EI
文献类型	会议论文
条目标识符	http://ir.ia.ac.cn/handle/173211/4730
专题	多模态人工智能系统全国重点实验室_先进时空数据分析与学习中国科学院自动化研究所
通讯作者	Xu Yuan
作者单位	National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences
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	Xu, Yuan,Huo, Chunlei,Xiang, Shiming,et al. ROBUST VHR IMAGE CHANGE DETECTION BASED ON LOCAL FEATURES AND MULTI-SCALE FUSION[C],2013:1991-1995.

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