基于数字表面模型( DSM) 的建筑物分割是遥感三维城市建模的关键技术之一．为解决DSM 分割中因地形起伏和边界处干扰物等引起的建筑物分割精度低的问题，文中
提出一种层次化的建筑物分割方法LS-OＲTSEG． 该方法首先利用水平集方法初步提取各个潜在的建筑物区域，对各潜在区域进行适当扩展，进而针对扩展区域利用一种基于多重随机纹理模型的分割方法进行精细分割，进一步优化建筑物局部边界分割结果． 实验表明，文中方法能够有效提高建筑物分割精度．

Segmenting buildings in digital surface model ( DSM) is a key technique of 3D city reconstruction based on remote sensing data.In order to overcome the poor performance caused by the negative interference of topographic relief and edge in the segmentation of buildings in DSM,a hierarchical segmentation method named LSORTSEG is proposed in light of both level-set ( LS) method and the model of occlusions of random texture ( ORTSEG) .In this method,firstly,the potential building regions are extracted roughly by means of the LS method.Secondly,the regions are expanded properly.Then,the expanded regions are segmented by using the ORTSEG for an optimized segmentation of buildings.Experimental results show that the proposed method can improve the segmentation accuracy of buildings effectively.