项目名称: 基于散射点密度信息熵的层析SAR建筑三维重建新方法研究
项目编号: No.61501019
项目类型: 青年科学基金项目
立项/批准年度: 2016
项目学科: 无线电电子学、电信技术
项目作者: 刘慧
作者单位: 北京建筑大学
项目金额: 19万元
中文摘要: 使用层析SAR点云数据,分析构建地面建筑的三维模型是SAR三维信息获取领域的重要课题。但目前,由于层析SAR点云中目标的检测和提取理论和方法还不够完善,在具有道路、树木及其他构造物的复杂环境中,建筑立面的检测和提取还很难。本课题针对层析SAR点云中的散射点密度估计问题,开展不同概率空间中的散射点密度信息熵的理论研究,发现层析SAR点云中建筑物散射点密度在不同概率空间中的分布规律,研究层析SAR点云中检测和提取建筑物的概率统计建模理论。针对建筑三维重建问题,开展层析SAR点云数据的生成、建筑的检测和提取、建筑立面的分割、建筑散射点高度重估等方法研究,探索层析SAR点云的建筑三维重建的新理论和新方法。
中文关键词: 散射点密度;信息熵;层析SAR;建筑三维重建
英文摘要: It is a important subject in the field of SAR 3D information acquisition to analysis and reconstruct the building 3D model using TomoSAR point cloud data. But at present, because the method of the target detection and extraction in TomoSAR point cloud is not perfect enough, it is very difficult to detect and extract the building in the complex environment that the building is surrounded by roads, trees and other structures. the subject aims at the problem of scatterer density estimation of TomoSAR point cloud, studies the scatterer density information entropy theory of different probability space, discovers the rules of building scatterer density probability distribution in TomoSAR point cloud, studies probability statistic model establishing theory of detecting and extracting building in TomoSAR point cloud. Aims the problem of building 3D reconstruction, studies the methods of TomoSAR point cloud data generation, building detection and extraction, segmentation of building facades and re-estimation of scatterer point height, explores the new theory and new method of building 3D reconstruction in TomoSAR point cloud.
英文关键词: Scatterer Point Density;Imformation Entropy ;TomoSAR;Building 3D Reconstruction