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航空影像的人工构造物提取与变化检测
刘莹
学位类型硕士
导师杨辽
2015
学位授予单位中国科学院大学
学位授予地点北京
学位专业测绘工程
关键词数字表面模型 Dsm 人工构造物提取 Ssim算子 变化检测
摘要人工构造物变化检测是城市监测的一个最基本的过程,传统的变化检测方法中尽管从不同时期的二维遥感影像中可以获取很多有用的变化信息,但是由于图像获取条件和传感器参数的不同,处理不同时期人工构造物变化检测的时候卫星数据的2D信息传递方式不同,获取时间、条件等不同,不能充分获得人工构造物在垂直方向上的变化。此外,由于相似的光谱特征很难去区分建筑物和其他的地物,比如道路和桥梁就跟建筑物有相似的光谱特征故而在变化检测过程中很难区分出来。因此数字表面模型(Digital Surface Models,简称DSM)提供的高程信息就尤为重要,高度信息变化是城市变化监测的重要部分,尤其是对人工构造物的变化检测。目前很多研究都是基于激光雷达数据进行的变化检测,但是激光雷达获取的数据频率少而且在偏远地区和大面积的变化检测中较难运用。尤其在一些突如其来的灾难中,航空影像数据的方便、快捷、实惠和容易获取为救灾减灾提供了便利条件,航空影像的DSM获取成为变化检测的基础。 论文针对高分辨率航空影像获取的DSM精确表示的人工构造物的三维信息,数字真正射影像图(True Digital Orthophoto Model ,简称TDOM)提供的形状、纹理、灰度信息,运用改进的算法和技术全面地分析二维、三维信息的综合变化情况,快速、准确地获取城市内人工构造物的变化情况。主要完成了以下内容: (1)DSM和TDOM的获取与优化。引用概率松弛全局一致性匹配算法获取特征点、线、面并进行匹配,生成初始的DSM模型,然后通过高程阈值约束法,对点云数据进行高精度的地面点和人工构造物约束分类,从而生成较为精细的DSM模型。 (2)人工构造物提取的变化检测。即先分类后比较变化的检测过程,与传统方法的不同之处在于,利用DSM提供的三维信息数据获取具有高程值的人工构造物轮廓,TDOM提供的形状、纹理、位置信息的二维轮廓,二者融合、拓扑化后进行变化检测,获得二维、三维信息的综合变化结果。 (3)人工构造物的直接变化检测。利用DSM的高程、位置变化和TDOM的形状、纹理信息变化进行综合变化检测的过程,通过对DSM和TDOM数据的利用,既保证了三维信息的变化,也保证了二维信息的变化情况。 论文中提出的技术和方法均利用实验和其他方法比较的方式验证了其有效性和实用性。方法弥补了只利用灰度、形状、位置信息检测时,形状不变、位置、灰度值不变而高度发生变化的人工构造物不能被检测出的问题。通过试验发现分类后的变化检测人工干预较多,精度稍高,但分类后的检测方法需要处理的数据较多,相对较耗时耗力,对于实时、快速的需求来说,直接的、自动化的方法更实用。
其他摘要Change detection is man-made structures a fundamental process of urban monitoring. Although the traditional change detection methods get a lot of useful change information from the two-dimensional remote sensing images at different times, it can’t obtain artificial structure changes in the vertical direction sufficiently. It is difficult to obtain sufficient artificial structures changes in the vertical direction because the different conditions and sensor acquisition parameters. In addition, it is hard to distinguish spectral difference between buildings and other surface objects due to the similarity of their spectral features, such as building roads and bridges. The elevation information from digital surface models is particularly important to monitor changes, especially for change detection of artificial structures. At present, a lot of change detection studies are based on lidar data, but the frequency of lidar data is less and it is almost unusable when used to detect the changes in remote areas or at large-scale areas. Aerial imagery has the characteristics of convenient, fast, affordable and easy to be obtained, and can be served as a convenient tool especially for unexpected disaster relief. The digital surface model from high resolution aerial images can acquired three-dimensional information of artificial construct. The true digital orthophoto provides the shape, texture, gray information of observed objects. We used improved algorithms and techniques to accomplish quick and accurate detection of comprehensive changes of urban man-made structures in two-dimensional and three-dimensional aspects. The main novel points of this paper are described in the following: (1) The acquisition and optimization of digital surface model and true digital orthophoto model. First, we produce the initial digital surface model by using a probabilistic relaxation matching algorithm to obtain global consistency of feature points, lines, surfaces and matching model. Then we obtain refined digital surface model by the elevation value constraint method for point cloud data points precision ground and artificial constraint classification structures. (2) The change detection of posting extraction of artificial structures. This method is different from the most conventional methods. We get the artificial structures profile with elevation values from digital surface model. At the same time, we get the texture information, location information, shape information as two-dimensional from true digital orthophoto model. Two-dimensional and three-dimensional information was combined in a topology design. At last, we obtain the artificial structures results of performing change detection in different periods. (3) Direct the change detection. It is a process of using the change information of elevation information from digital surface model and position, shape, texture changes from true digital orthophoto model. This method not only guarantee in the change of three-dimensional information, and also to ensure the changes in the two-dimensional information. The efficiency and robustness of the proposed technology and the method are evaluated via comparative experiments and real practical applications. The method makes up the problem that the artificial structure can't be detected by the change of shape, position and gray value when the gray scale, shape and position information is detected. Found several tests post classification change detection of too much manual intervention, slightly higher accuracy, but classified detection methods need to deal with a lot of data, a relatively time-consuming and labor-intensive, for the demand of real-time and quick, direct, automated method more practical.
学科领域测绘工程
语种中文
文献类型学位论文
条目标识符http://ir.xjlas.org/handle/365004/14657
专题研究系统_荒漠环境研究室
作者单位中科院新疆生态与地理研究所
推荐引用方式
GB/T 7714
刘莹. 航空影像的人工构造物提取与变化检测[D]. 北京. 中国科学院大学,2015.
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