中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Fast Object-Level Change Detection for VHR Images

文献类型:期刊论文

作者Huo, Chunlei1; Zhou, Zhixin1,2; Lu, Hanqing1; Pan, Chunhong1; Chen, Keming1
刊名IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
出版日期2010
卷号7期号:1页码:118-122
关键词Fast multitemporal segmentation object-level change vector analysis progressive classification
英文摘要Anovel approach is presented for change detection of very high resolution images, which is accomplished by fast object-level change feature extraction and progressive change feature classification. Object-level change feature is helpful for improving the discriminability between the changed class and the unchanged class. Progressive change feature classification helps improve the accuracy and the degree of automation, which is implemented by dynamically adjusting the training samples and gradually tuning the separating hyperplane. Experiments demonstrate the effectiveness of the proposed approach.
WOS标题词Science & Technology ; Physical Sciences ; Technology
类目[WOS]Geochemistry & Geophysics ; Engineering, Electrical & Electronic ; Remote Sensing ; Imaging Science & Photographic Technology
研究领域[WOS]Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology
关键词[WOS]SEGMENTATION ; DOMAIN ; SVM
收录类别SCI
语种英语
WOS记录号WOS:000276079000024
源URL[http://ir.ia.ac.cn/handle/173211/3687]  
专题自动化研究所_模式识别国家重点实验室_遥感图像处理团队
作者单位1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
2.Beijing Inst Remote Sensing, Beijing 100854, Peoples R China
推荐引用方式
GB/T 7714
Huo, Chunlei,Zhou, Zhixin,Lu, Hanqing,et al. Fast Object-Level Change Detection for VHR Images[J]. IEEE GEOSCIENCE AND REMOTE SENSING LETTERS,2010,7(1):118-122.
APA Huo, Chunlei,Zhou, Zhixin,Lu, Hanqing,Pan, Chunhong,&Chen, Keming.(2010).Fast Object-Level Change Detection for VHR Images.IEEE GEOSCIENCE AND REMOTE SENSING LETTERS,7(1),118-122.
MLA Huo, Chunlei,et al."Fast Object-Level Change Detection for VHR Images".IEEE GEOSCIENCE AND REMOTE SENSING LETTERS 7.1(2010):118-122.

入库方式: OAI收割

来源:自动化研究所

浏览0
下载0
收藏0
其他版本

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。