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	A New Method for Spatial Feature Extraction and Classification of Remote Sensing Image
	Zhang, Xi ; Zhang, Shuyi ; Xu, Jiangfeng ; Wang, Jinfei
	2006
关键词	spatial feature exaction classification support vector machine boost kernal method SVM
英文摘要	The extraction and classification problem of spatial features from high r esolution satellite sensor image, especially from the image covering urban areas, is a very significant but challenging task. However, it is very difficult to be implemented and the main obstacle comes from high-dimensional and complicated properties of spatial features. In this paper, we propose to use a two-dimension wave-let transform as well as a classification method---support vector machine (SVM) to address this issue. Also, a boosting method is involved in order to improve the accuracy of classification. We will show in our experiment that SVM with Boosting leads to a more admissible result by choosing several SVM kernels, including the linear kernel and the Gaussian kernel.; Geosciences, Multidisciplinary; Remote Sensing; Imaging Science & Photographic Technology; EI; CPCI-S(ISTP); 0
语种	英语
出处	SCI ; EI
内容类型	其他
源URL	[http://hdl.handle.net/20.500.11897/315421]
专题	数学科学学院
推荐引用方式 GB/T 7714	Zhang, Xi,Zhang, Shuyi,Xu, Jiangfeng,et al. A New Method for Spatial Feature Extraction and Classification of Remote Sensing Image. 2006-01-01.

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