计算机应用 ›› 2019, Vol. 39 ›› Issue (6): 1810-1815.DOI: 10.11772/j.issn.1001-9081.2018102164

• 虚拟现实与多媒体计算 • 上一篇    下一篇

基于纹理分水岭的斜坡单元提取算法

程露, 周波   

  1. 合肥工业大学 计算机与信息学院, 合肥 230601
  • 收稿日期:2018-10-26 修回日期:2018-12-16 发布日期:2019-06-17 出版日期:2019-06-10
  • 通讯作者: 周波
  • 作者简介:程露(1992-),女,安徽合肥人,硕士研究生,主要研究方向:数字图像处理;周波(1981-),男,湖北宜昌人,副教授,博士,主要研究方向:数字地形分析。
  • 基金资助:
    国家自然科学基金资助项目(41401445,41371421);安徽省自然科学基金资助项目(1508085QD76);合肥工业大学宣城校区博士产学研启动专项基金资助项目(XC20116JZBZ20)。

Slope unit extraction algorithm based on texture watershed

CHENG Lu, ZHOU Bo   

  1. School of Computer Science and Information Engineering, Hefei University of Technology, Heifei Anhui 230601, China
  • Received:2018-10-26 Revised:2018-12-16 Online:2019-06-17 Published:2019-06-10
  • Supported by:
    This work is partially supported by the National Natural Science Foundation of China (41401445, 41371421), the Natural Science Foundation of Anhui Province (1508085QD76), the Doctoral Production & Learning & Research Special Fund of Xuancheng Campus of Hefei University of Technology (XC20116JZBZ20).

摘要: 斜坡单元在以滑坡为主的地质灾害预防和评价中有着广泛的应用,其提取和划分是滑坡灾害风险评估的首要工作和重要基础。针对传统地理信息系统(GIS)方法提取的斜坡单元存在平行边界和误分割问题,提出了基于纹理分水岭的斜坡单元提取方法,通过分割地形图像划分斜坡单元。首先通过预处理地形数据得到数字高程模型(DEM)图像,利用灰度共生矩阵提取DEM纹理特征;然后计算融合灰度和纹理特征的梯度图像,对梯度图像进行基于标记的分水岭分割,使其能够准确获取山体和流域边界;最后,结合正负地形,对山体对象进行分水岭分割以实现斜坡单元的提取。实验结果表明,所提方法对不同地貌类型和分辨率的DEM图像都有良好的划分效果;相较于传统的GIS方法,该方法能够正确分割水平面和倾斜面,有效避免因洼地填平处理而产生的平行边界问题。

关键词: 斜坡单元, 数字高程模型, 分水岭算法, 正负地形, 纹理梯度

Abstract: Slope units are widely used in the prevention and evaluation of landslide-based geological hazards, whose extraction and division are the primary target and important foundation for the risk assessment of landslide hazards. Considering the parallel boundaries and incorrect segmentation problems of the slope units extracted by traditional Geographic Information System (GIS) method, a slope unit extraction algorithm based on texture watershed was proposed, in which slope units were extracted by segmenting terrain images. Firstly, a Digital Elevation Model (DEM) image was obtained by the pretreatment of terrain data, and DEM texture features were extracted by gray level co-occurrence matrix. Then, the gradient image with gray level fused with texture features was calculated and segmented by marker-based watershed segmentation to accurately obtain mountain boundaries and watershed boundaries. Finally, combined with positive and negative terrains, the mountain objects were segmented by watershed segmentation to extract slope units. The experimental results show that the proposed method is pretty effective in segmentation for DEM images of different landform types and resolutions. Compared with traditional GIS method, horizontal planes and inclined planes can be segmented correctly, and the problem of parallel boundaries caused by filling of depressions can be effectively avoided through the proposed method.

Key words: slope unit, Digital Elevation Model (DEM), watershed algorithm, positive and negative terrain, texture gradient

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