Automatic registration of fused lidar/digital imagery (texel images) for three-dimensional image creation
Automatic registration of fused lidar/digital imagery (texel images) for three-dimensional image creation
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DOI：
10.1117/1.oe.54.3.031105
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发表时间：
2014-11
影响因子：
1.3
通讯作者：
S. Budge;Neeraj S. Badamikar;Xuan Xie
中科院分区：
文献类型：
--
作者：
S. Budge;Neeraj S. Badamikar;Xuan Xie
抽象。已经提出了几种基于摄影测量的方法，其从不同视角从数字图像中导出三维（3-D）信息，并且已经提出了基于激光雷达的方法，其合并激光雷达点云并将合并的点云与数字图像纹理化。单独的图像配准难以处理具有低对比度的平滑区域，而单独的点云合并难以处理离群值，并且在合并过程中缺乏适当的收敛。本文提出了一种创建3D图像的方法，该方法利用纹素图像（像素融合激光雷达和数字图像）的独特属性来提高融合3D图像的质量和鲁棒性。所提出的方法使用图像处理和点云合并联合收割机纹理图像的迭代技术。由于数字图像像素和激光雷达3D点在传感器级融合，因此生成更准确的3D图像，因为图像数据的配准自动改善了点云的合并，反之亦然。实例说明了该方法优于其他方法的价值。所提出的方法还包括修改的情况下，传感器的位置和姿态的估计是已知的，当从低成本的全球定位系统和惯性测量单元传感器。
Abstract. Several photogrammetry-based methods have been proposed that the derive three-dimensional (3-D) information from digital images from different perspectives, and lidar-based methods have been proposed that merge lidar point clouds and texture the merged point clouds with digital imagery. Image registration alone has difficulty with smooth regions with low contrast, whereas point cloud merging alone has difficulty with outliers and a lack of proper convergence in the merging process. This paper presents a method to create 3-D images that uses the unique properties of texel images (pixel-fused lidar and digital imagery) to improve the quality and robustness of fused 3-D images. The proposed method uses both image processing and point-cloud merging to combine texel images in an iterative technique. Since the digital image pixels and the lidar 3-D points are fused at the sensor level, more accurate 3-D images are generated because registration of image data automatically improves the merging of the point clouds, and vice versa. Examples illustrate the value of this method over other methods. The proposed method also includes modifications for the situation where an estimate of position and attitude of the sensor is known, when obtained from low-cost global positioning systems and inertial measurement units sensors.