Simultaneous change region and pattern identification for very high-resolution images
Huo, Chunlei1; Huo, Leigang2; Zhou, Zhixin3; Pan, Chunhong1
2017-10-27
发表期刊JOURNAL OF APPLIED REMOTE SENSING
卷号11
文章类型Article
摘要By taking advantages of fine details obtained by the improved spatial resolution, very high-resolution images are promising for detecting change regions and identifying change patterns. However, high overlaps between different change patterns and the complexities of multiclass classification make it difficult to reliably separate change features. A framework named simultaneous change region and pattern identification (SCRAPI) is proposed for simultaneously detecting change regions and identifying change patterns, whose components are aimed at capturing overlaps between change patterns and reducing overlaps driven by user-specific interests. To validate the effectiveness of SCRAPI, a supervised approach is illustrated within this framework, which starts with modeling the relationship between change features by interclass couples and intraclass couples, followed by metric learning where structural sparsity is captured by the mixed norm. Experiments demonstrate the effectiveness of the proposed approach. (C) 2017 Society of Photo-Optical Instrumentation Engineers (SPIE)
关键词Change Detection Change Pattern Feature Classification Feature Learning Distance Tuning
WOS标题词Science & Technology ; Life Sciences & Biomedicine ; Technology
DOI10.1117/1.JRS.11.045007
关键词[WOS]VHR IMAGES ; CLASSIFICATION ; ALGORITHMS ; SELECTION
收录类别SCI
语种英语
项目资助者Natural Science Foundation of China(91438105 ; 61375024 ; 61302170 ; 91338202)
WOS研究方向Environmental Sciences & Ecology ; Remote Sensing ; Imaging Science & Photographic Technology
WOS类目Environmental Sciences ; Remote Sensing ; Imaging Science & Photographic Technology
WOS记录号WOS:000414075200001
引用统计
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/20753
专题模式识别国家重点实验室_先进数据分析与学习
作者单位1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing, Peoples R China
2.Guangxi Teachers Educ Univ, Sch Comp & Informat Engn, Nanning, Peoples R China
3.Beijing Inst Remote Sensing, Beijing, Peoples R China
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Huo, Chunlei,Huo, Leigang,Zhou, Zhixin,et al. Simultaneous change region and pattern identification for very high-resolution images[J]. JOURNAL OF APPLIED REMOTE SENSING,2017,11.
APA Huo, Chunlei,Huo, Leigang,Zhou, Zhixin,&Pan, Chunhong.(2017).Simultaneous change region and pattern identification for very high-resolution images.JOURNAL OF APPLIED REMOTE SENSING,11.
MLA Huo, Chunlei,et al."Simultaneous change region and pattern identification for very high-resolution images".JOURNAL OF APPLIED REMOTE SENSING 11(2017).
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