A New Accuracy Assessment Method for One-Class Remote Sensing Classification

doi:10.1109/TGRS.2013.2283082

	A New Accuracy Assessment Method for One-Class Remote Sensing Classification
	Li, Wenkai; Guo, Qinghua
	2014
发表期刊	IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
ISSN	0196-2892
卷号	52 期号:8 页码:4621-4632
摘要	In one-class remote sensing classification, users are only interested in classifying one specific land type (positive class), without considering other classes (negative class). Previous researchers have proposed different one-class classification methods without requiring negative data. An appropriate accuracy measure is usually needed to tune free parameters/threshold and to evaluate the classification result. However, traditional accuracy measures, such as the kappa coefficient and F-measure (F), require both positive and negative data, and hence, they are not applicable for positive-only data. In this paper, we investigate a new accuracy assessment method that does not require negative data. Two new statistics F-pb (proxy of F-measure based on positive-background data) and F-cpb (prevalence-calibrated proxy of F-measure based on positive-background data) can be calculated from a modified confusion matrix, where the observed negative data are replaced by background data. To investigate the effectiveness of the new method, we produced different one-class classification results using two scenes of aerial photograph, and the accuracy values were evaluated by F-pb, F-cpb, kappa coefficient, and F. The effectiveness of F-pb in model and threshold selection was investigated as well. Experimental results show that the behaviors of F-pb, F-cpb, F, and kappa coefficient are similar, and they all rank the models by accuracy similarly. In model and threshold selection, the classification accuracy values produced by maximizing F-pb and F are similar, and they are higher than those produced by setting an arbitrary rejection fraction. Therefore, we conclude that the new method is effective in model selection, threshold selection, and accuracy assessment, and it will have important applications in one-class remote sensing classification since negative data are not needed.
关键词	Accuracy assessment background F-measure negative one-class remote sensing classification positive
学科领域	Geochemistry & Geophysics ; Engineering, Electrical & Electronic ; Remote Sensing ; Imaging Science & Photographic Technology
DOI	10.1109/TGRS.2013.2283082
收录类别	SCI
语种	英语
WOS关键词	SUPERVISED IMAGE CLASSIFICATION ; PRESENCE-ABSENCE MODELS ; SPECIES DISTRIBUTIONS ; F-SCORE ; PREDICTION ; SUPPORT ; SET
WOS研究方向	Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology
WOS记录号	WOS:000332598500012
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
文献子类	Article
出版地	PISCATAWAY
EISSN	1558-0644
资助机构	National Science Foundation of China [31270563] ; National Science Foundation [BDI-0742986]
作者邮箱	qguo@ucmerced.edu
引用统计	被引频次：47[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ibcas.ac.cn/handle/2S10CLM1/27222
专题	植被与环境变化国家重点实验室
作者单位	Chinese Acad Sci, Inst Bot, State Key Lab Vegetat & Environm Change, Beijing 100093, Peoples R China; Univ Calif, Sch Engn, Merced, CA 95343 USA
推荐引用方式 GB/T 7714	Li, Wenkai,Guo, Qinghua. A New Accuracy Assessment Method for One-Class Remote Sensing Classification[J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,2014,52(8):4621-4632.
APA	Li, Wenkai,&Guo, Qinghua.(2014).A New Accuracy Assessment Method for One-Class Remote Sensing Classification.IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,52(8),4621-4632.
MLA	Li, Wenkai,et al."A New Accuracy Assessment Method for One-Class Remote Sensing Classification".IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 52.8(2014):4621-4632.

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