摘要
探地雷达(GPR)图像双曲波提取是分析地下目标位置和结构的重要方法,但在真实环境中,由于噪声和杂波的干扰,使得提取出的双曲波存在结构不完整、碎片化和形状异常等问题,不利于数据分析和三维建模等后续操作。为此,提出了一种基于多标签层次聚类的双曲波提取方法(MHCE)。首先通过信息熵评价像素邻域的稳定性,构造了基于信息熵的距离度量来进行层次聚类;然后利用聚类后的邻接空间进行多标签聚类以降低杂波和噪声对双曲波提取的影响;最后结合多标签聚类结果的拟合形状和纹理方向提取双曲波。实验表明,该方法对于真实GPR图像双曲波具有较好的鲁棒性,能够获得规范化的双曲波形状和位置参数。
Hyperbola extraction in ground penetrating radar(GPR) images is an important feature to analyze the location and structure of underground objects. However, there are often some problems with the extracted hyperbola, such as incomplete structure, fragmentation, and shape anomalies, caused by the interference of noise and clutter that are typical of real environments. These issues are not conducive to the subsequent quantitative operations, such as data analysis and 3 D modeling. In this context, this paper proposed a multi-label hierarchical clustering-based hyperbola extraction method(MHCE) for the hyperbola extraction of GPR images. Firstly, through evaluating the stability between pixel neighborhoods by the means of information entropy, an information entropy-based distance method was constructed to conduct the hierarchical clustering algorithm. Next, a multi-label clustering method was proposed based on the adjacency space of the clustering results, so as to reduce the influence of clutter and noise on hyperbola extraction. Finally, the hyperbola was extracted combined with the fitting shape and texture orientation of the multi-label clustering results. The experimental results show that this method is robust for GPR images and can be used to obtain the shape and position parameters of a normalized hyperbola.
作者
李文生
原达
苗翠
王冬雨
LI Wen-sheng;YUAN Da;MIAO Cui;WANG Dong-yu(Key Laboratory of Intelligent Information Processing,Shandong Technology and Business University,Yantai Shandong 264005,China)
出处
《图学学报》
CSCD
北大核心
2020年第3期399-408,共10页
Journal of Graphics
基金
山东省重点研发计划项目(2019GGX101040)。
关键词
探地雷达图像
双曲波
信息熵
多标签层次聚类
鲁棒性
ground penetrating radar image
hyperbola
information entropy
multi-label hierarchical clustering algorithm
robustness
