基于遥感图像的大规模城市建模中的建筑物轮廓提取
发布时间：2018-12-29 14:36
【摘要】：3D数字城市是视景仿真以及数字地球的基础。实现城市数字化的关键是进行快速有效的城市建模。但多数建模方法都需要很多先验信息甚至大量人力，并且手工建模很难处理大规模分布的城市元素，，所以仅依靠手工建模不容易满足大规模城市的高效建模。 本文采用了一种基于遥感图像的、无成本的、灵活的自动3D数字城市建模方法，其主要内容包括图像分割、图像形态学运算、建筑物轮廓提取、3D模型重建、纹理贴图等，可有效解决手工建模的不足。 在上述基于图像的三维重建方法中，建筑物轮廓的识别与提取决定着最后的重建效果，而图像的分割与形态学运算直接影响着建筑物轮廓的提取。文章重点论述了基于遥感图像的建筑物轮廓提取过程及方法，并研究了图像分割和图像形态学对最后结果的影响。对于遥感图像中建筑物轮廓的提取，本文采用了区域特征与边缘信息相结合的方法：首先对图像采用Mean Shift多尺度分割算法进行预分割，随后再用Otsu阈值算法对其进行后续分割，初步清除图像中的大部非建筑物部分；最后使用形态学运算对分割结果进行优化，有效地将与建筑屋顶颜色特征及光谱特征都相似的道路分离出去。文章最后对基于建筑物轮廓的三维重建过程进行了简要介绍。 实验结果表明：本文所用方法可达到令人满意的建筑物提取效果，实用价值较高；易于理解与实现也是本文所用方法的优点。
[Abstract]:The 3D digital city is the foundation of visual simulation and digital earth. The key to realize the city digitization is to carry on the fast and effective city modeling. However, most modeling methods require a lot of prior information or even a lot of manpower, and manual modeling is difficult to deal with large-scale distributed urban elements, so it is not easy to satisfy the efficient modeling of large-scale cities by manual modeling alone. In this paper, a kind of automatic 3D digital city modeling method based on remote sensing image, which is cost free and flexible, is adopted. Its main contents include image segmentation, image morphology operation, building contour extraction, 3D model reconstruction, texture mapping and so on. It can effectively solve the problem of manual modeling. In the above three dimensional reconstruction method based on image the recognition and extraction of building contour determine the final reconstruction effect and the segmentation and morphological operation of image directly affect the extraction of building contour. This paper mainly discusses the process and method of building contour extraction based on remote sensing image, and studies the effect of image segmentation and image morphology on the final results. For the extraction of building contour from remote sensing image, this paper adopts the method of combining regional features with edge information. Firstly, the Mean Shift multi-scale segmentation algorithm is used to pre-segment the image, and then the Otsu threshold algorithm is used to segment the image. Initial removal of most non-building parts of the image; Finally, the segmentation results are optimized by morphological operation, and the roads which are similar to the building roof color and spectral features are effectively separated out. At last, the process of 3D reconstruction based on building contour is briefly introduced. The experimental results show that the method used in this paper can achieve a satisfactory result of building extraction, and is of high practical value, and is also the advantage of the method used in this paper.
【学位授予单位】：西安电子科技大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TP751
本文编号：2394961
[Abstract]:The 3D digital city is the foundation of visual simulation and digital earth. The key to realize the city digitization is to carry on the fast and effective city modeling. However, most modeling methods require a lot of prior information or even a lot of manpower, and manual modeling is difficult to deal with large-scale distributed urban elements, so it is not easy to satisfy the efficient modeling of large-scale cities by manual modeling alone. In this paper, a kind of automatic 3D digital city modeling method based on remote sensing image, which is cost free and flexible, is adopted. Its main contents include image segmentation, image morphology operation, building contour extraction, 3D model reconstruction, texture mapping and so on. It can effectively solve the problem of manual modeling. In the above three dimensional reconstruction method based on image the recognition and extraction of building contour determine the final reconstruction effect and the segmentation and morphological operation of image directly affect the extraction of building contour. This paper mainly discusses the process and method of building contour extraction based on remote sensing image, and studies the effect of image segmentation and image morphology on the final results. For the extraction of building contour from remote sensing image, this paper adopts the method of combining regional features with edge information. Firstly, the Mean Shift multi-scale segmentation algorithm is used to pre-segment the image, and then the Otsu threshold algorithm is used to segment the image. Initial removal of most non-building parts of the image; Finally, the segmentation results are optimized by morphological operation, and the roads which are similar to the building roof color and spectral features are effectively separated out. At last, the process of 3D reconstruction based on building contour is briefly introduced. The experimental results show that the method used in this paper can achieve a satisfactory result of building extraction, and is of high practical value, and is also the advantage of the method used in this paper.
【学位授予单位】：西安电子科技大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TP751
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