Remote Sensing | |
Accurate Annotation of Remote Sensing Images via Active Spectral Clustering with Little Expert Knowledge | |
Gui-Song Xia2  Zifeng Wang2  Caiming Xiong3  Liangpei Zhang2  Soe Myint1  Xiaofeng Li1  | |
[1] State Key Laboratory for Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan 430079, China;;State Key Laboratory for Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan 430079, China; E-Mails:;Department of Statistics, University of California, Los Angeles, CA 90095, USA; E-Mail: | |
关键词: information mining; remote sensing image annotation; image clustering; active clustering; expert knowledge; | |
DOI : 10.3390/rs71115014 | |
来源: mdpi | |
【 摘 要 】
It is a challenging problem to efficiently interpret the large volumes of remotely sensed image data being collected in the current age of remote sensing “big data”. Although human visual interpretation can yield accurate annotation of remote sensing images, it demands considerable expert knowledge and is always time-consuming, which strongly hinders its efficiency. Alternatively, intelligent approaches (e.g., supervised classification and unsupervised clustering) can speed up the annotation process through the application of advanced image analysis and data mining technologies. However, high-quality expert-annotated samples are still a prerequisite for intelligent approaches to achieve accurate results. Thus,
【 授权许可】
CC BY
© 2015 by the authors; licensee MDPI, Basel, Switzerland.
【 预 览 】
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