Selection of GCP in geometric correction of remote sensing images
LIU Shanlei1, SHI Shanqiu1, ZHANG Lijing1, ZHAO Yindi2, WANG Guanghui3
1. Foundational Geography Information Center of Jiangsu Province, Nanjng 210013, China; 2. College of Environment Science and Spatial Informatics, China University of Mining & Technology, Xuzhou 221008, China; 3. Satellite Surveying and Mapping Application Center, National Administration of Surveying, Mapping and Geoinformation, Beijing 100830, China
Abstract：In order to improve the collection efficiency of GCP and reduce the influence of human factors,the authors used the improved watershed segmentation and weighted neighbor detection methods to select the cross point of roads as GCP,and employed GrabCut segmentation and contour detection methods to select the center of gravity of the region as GCP in the reference image. The ALOS image with 2.5 m resolution was geometrically corrected by the GCPs which were selected from aerial images with 0.5 m resolution. The results show that the GCP selection methods proposed in this paper for remote sensing image geometric correction are less affected by human factors,the precision is less than 1 pixel,and hence the semi-automatic extraction can be realized. The technical achievement in this paper has been applied to the GCP selection for the production of DOM,with an important role played in the renewal of DOM at middle and small scales.
刘善磊, 石善球, 张丽静, 赵银娣, 王光辉. 遥感图像几何纠正中GCP选取[J]. 国土资源遥感, 2014, 26(3): 86-91.
LIU Shanlei, SHI Shanqiu, ZHANG Lijing, ZHAO Yindi, WANG Guanghui. Selection of GCP in geometric correction of remote sensing images. REMOTE SENSING FOR LAND & RESOURCES, 2014, 26(3): 86-91.
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2014, Vol. 26 
