cloud detection based on segmentation with statistical and geometry features

ISCAS OpenIR

	cloud detection based on segmentation with statistical and geometry features
	Li Bangyu; Li Xia
	2012
会议名称	2012 32nd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2012
会议录名称	International Geoscience and Remote Sensing Symposium (IGARSS)
页码	6020-6023
会议日期	July 22, 2012 - July 27, 2012
会议地点	Munich, Germany
收录类别	EI
部门归属	(1) Institute of Software Chinese Academy of Sciences No. 4 South Fourth Street Haidian District Zhong Guan Cun Beijing China
摘要	Cloud detection, recognition has been received increasing attention during last decades in remote sensing application field. We propose a novel cloud detection algorithm based on statistical region merging segmentation with statistical and geometry features. To distinguish clouds objects from a background, the statistical region merging segmentation algorithm is firstly adopted to obtain semantic segmentation regions. Based on information of segmented patches, statistical features, including spectrum and geometry features are extracted to represent otherness between clouds and underlying surface. Such features are finally implied to math the feature temple by the nearest neighbor algorithm. We show in this paper the addressed method make a effective cloud detection without any prior constraints and auxiliary data. Experiments have been carried out on aerial optical images to validate our proposed method. © 2012 IEEE.; Cloud detection, recognition has been received increasing attention during last decades in remote sensing application field. We propose a novel cloud detection algorithm based on statistical region merging segmentation with statistical and geometry features. To distinguish clouds objects from a background, the statistical region merging segmentation algorithm is firstly adopted to obtain semantic segmentation regions. Based on information of segmented patches, statistical features, including spectrum and geometry features are extracted to represent otherness between clouds and underlying surface. Such features are finally implied to math the feature temple by the nearest neighbor algorithm. We show in this paper the addressed method make a effective cloud detection without any prior constraints and auxiliary data. Experiments have been carried out on aerial optical images to validate our proposed method. © 2012 IEEE.
关键词	Geology Geometrical Optics Image Segmentation Merging Remote Sensing
主办者	Geoscience and Remote Sensing Society (GRS)
语种	英语
内容类型	会议论文
URI标识	http://ir.iscas.ac.cn/handle/311060/15835
专题	中国科学院软件研究所
推荐引用方式 GB/T 7714	Li Bangyu,Li Xia. cloud detection based on segmentation with statistical and geometry features[C],2012:6020-6023.