Study of method for fast segmentation based on UAV image
LU Heng1,2,3, FU Xiao4, LIU Chao1,2, GUO Jiawei3,4, GOU Si1,2, LIU Tiegang1,2
1. State Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan University, Chengdu 610065, China;
2. College of Hydraulic and Hydroelectric Engineering, Sichuan University, Chengdu 610065, China;
3. Key Laboratory of Geo-spatial Information Technology, Ministry of Land and Resources, Chengdu University of Technology, Chengdu 610059, China;
4. Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 611756, China
In order to solve the problem that it is difficult to obtain spatial data in time in the earthquake stricken area, the authors propose in this paper a more efficient new segmentation algorithm on the basis of the own features of unmanned aerial vehicle(UAV) remote sensing images. Firstly, the image is divided into several homogeneous color areas and texture areas through variance detection on the color space. Secondly, preliminary partition of the homogeneous color area is directly achieved by Mean Shift method. Meanwhile, for the texture area, a high dimensional feature space is set up based on the color, texture, and shape information, and the proper bandwidth is calculated according to the normalized distribution density before applying Mean Shift algorithm on the feature space to model classification so as to reach the partition. Finally, an object function is set up to realize area merging and then reach the final partition results by smoothing over partitioned areas. Tests were conducted for high spatial resolution remote sensing image segmentation on UAV images of Lushan earthquake stricken area. A segmentation matching index which considers area and spectrum is proposed to evaluate the segmentation result. The experimental results show that the improved method performs better than the traditional method, and can provide data protection for subsequent damage information extraction.
鲁恒, 付萧, 刘超, 郭加伟, 苟思, 刘铁刚. 基于无人机影像的快速分割方法[J]. 国土资源遥感, 2016, 28(2): 72-78.
LU Heng, FU Xiao, LIU Chao, GUO Jiawei, GOU Si, LIU Tiegang. Study of method for fast segmentation based on UAV image. REMOTE SENSING FOR LAND & RESOURCES, 2016, 28(2): 72-78.
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2016, Vol. 28 
