首页> 外文期刊>International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences >THE ONE TO MULTIPLE AUTOMATIC HIGH ACCURACY REGISTRATION OF TERRESTRIAL LIDAR AND OPTICAL IMAGES
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THE ONE TO MULTIPLE AUTOMATIC HIGH ACCURACY REGISTRATION OF TERRESTRIAL LIDAR AND OPTICAL IMAGES

机译:陆地激光和光学图像的一对多自动高精度配准

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The registration of ground laser point cloud and close-range image is the key content of high-precision 3D reconstruction of cultural relic object. In view of the requirement of high texture resolution in the field of cultural relic at present, The registration of point cloud and image data in object reconstruction will result in the problem of point cloud to multiple images. In the current commercial software, the two pairs of registration of the two kinds of data are realized by manually dividing point cloud data, manual matching point cloud and image data, manually selecting a two – dimensional point of the same name of the image and the point cloud, and the process not only greatly reduces the working efficiency, but also affects the precision of the registration of the two, and causes the problem of the color point cloud texture joint. In order to solve the above problems, this paper takes the whole object image as the intermediate data, and uses the matching technology to realize the automatic one-to-one correspondence between the point cloud and multiple images. The matching of point cloud center projection reflection intensity image and optical image is applied to realize the automatic matching of the same name feature points, and the Rodrigo matrix spatial similarity transformation model and weight selection iteration are used to realize the automatic registration of the two kinds of data with high accuracy. This method is expected to serve for the high precision and high efficiency automatic 3D reconstruction of cultural relic objects, which has certain scientific research value and practical significance.
机译:地面激光点云和近距离图像的配准是对文物的高精度3D重建的关键内容。鉴于目前文物领域对高纹理分辨率的要求,在对象重建中对点云和图像数据的配准将导致点云对多个图像的问题。在当前的商业软件中,通过手动划分点云数据,手动匹配点云和图像数据,手动选择图像名称和图像名称相同的二维点来实现两种数据的两对配准。点云,该过程不仅大大降低了工作效率,而且影响了两者的配准精度,并引起了色点云纹理联合的问题。为了解决上述问题,本文将整个物体图像作为中间数据,并利用匹配技术实现了点云与多幅图像之间的自动一一对应。利用点云中心投影反射强度图像与光学图像的匹配实现同名特征点的自动匹配,并使用罗德里戈矩阵空间相似度转换模型和权重选择迭代实现两种的自动配准数据的准确性。该方法有望用于文物的高精度,高效3D自动重建,具有一定的科研价值和现实意义。

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