Unsupervised feature learning for scene classification of high resolution remote sensing image

doi:10.1109/ChinaSIP.2015.7230392

OPT OpenIR > 光谱成像技术研究室

	Unsupervised feature learning for scene classification of high resolution remote sensing image
	Fu, Min1,2 ; Yuan, Yuan1 ; Lu, Xiaoqiang1
	2015
会议名称	IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2015
会议录名称	2015 IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2015 - Proceedings
页码	206-210
会议日期	2015-07
会议地点	Chengdu, China
出版者	Institute of Electrical and Electronics Engineers Inc.
产权排序	1
摘要	Due to the rapid development of various satellite sensors, a large amount of high resolution remote sensing images can be obtained. In order to efficiently represent the scenes from these high resolution images, an unsupervised feature learning method is proposed for high resolution image scene classification. In the proposed method, a set of filter banks are learned in an unsupervised manner from the unlabeled image patches, which are robust, efficient and do not need elaborately designed descriptors such as SIFT. And then, each image is encoded by these filter banks using a soft distance assignment scheme, generating a final feature vector to excellently represent the image scene. Finally, by virtue of the traditional SVM classifier, the sematic concepts of different scenes can be categorized. Experimental evaluation on the the high resolution remote sensing images demonstrates the effectiveness and good performance of the proposed method. © 2015 IEEE.
作者部门	光学影像学习与分析中心
DOI	10.1109/ChinaSIP.2015.7230392
收录类别	EI
ISBN号	9781479919482
语种	英语
引用统计
文献类型	会议论文
条目标识符	http://ir.opt.ac.cn/handle/181661/27822
专题	光谱成像技术研究室
通讯作者	Lu, Xiaoqiang
作者单位	1.Center for OPTical IMagery Analysis and Learning (OPTIMAL), State Key Laboratory of Transient Optics and Photonics, Xi'An Institute of Optics and Precision Mechanics, Xi'an Shaanxi, China 2.University of the Chinese Academy of Sciences, 19A Yuquanlu, Beijing, China
推荐引用方式 GB/T 7714	Fu, Min,Yuan, Yuan,Lu, Xiaoqiang. Unsupervised feature learning for scene classification of high resolution remote sensing image[C]:Institute of Electrical and Electronics Engineers Inc.,2015:206-210.

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文件名称/大小	文献类型	版本类型	开放类型	使用许可
Unsupervised feature（1044KB）	会议论文		限制开放	CC BY-NC-SA	请求全文