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《Remote Sensing Technology and Application》 2018-01
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An Improved Method for Object Extracting based on Context Information Using Multisouce Data

Wu Di;Shi Wenzhong;Gao Lipeng;Zhang Hua;He Pengfei;School of Environment Science and Spatial Informatics,China University of Mining and Technology;Department of Land Surveying and Geo-Informatics,The Hong Kong Polytechnic University;School of Remote Sensing and Information Engineering,Wuhan University;  
This paper proposed a new method which combines the airborne LiDAR data with aerial image to extract Rolling Stones on mountainous.Firstly,the aerial image is processed with multi-scale segmentation to get segmentation objects,and the LiDAR data are processed by classification,interpolation,difference for elevation information.Then compute the segmentation object based on visible-band difference vegetation index to remove the interference of vegetation information,and the nonvegetated segmentation objects are obtained.In order to effectively use the shadow,this paper put forward the normalized difference shadow index and use threshold segmentation to get shadow object.And then the automatic extraction algorithm based on the shadow and elevation information is used to preliminary obtain the rolling stones information.Finally,The height threshold filtering is set according to the actual demand to get the final rolling information.This paper took a certain area of Hong Kong aviation image and LiDAR data as experimental data to validate the proposed method.The results show that the method can well extract the Rolling Stones and effectivly distinguish the exposed bedrock,roads and similar spectral information of ground objects as Rolling Stones.The extraction accuracy of Rolling Stones is above 88% which basically satisfies the needs of rockfall in lands department.
【Fund】: 国家自然科学重点基金项目“可靠性遥感影像分类与空间关联分析研究”(41331175)
【CateGory Index】: TP391.41
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