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Automatic Seamline Network Generation for Urban Orthophoto Mosaicking with the Use of a Digital Surface Model

机译:使用数字表面模型自动生成城市正射影像马赛克的接缝线网络

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Intelligent seamline selection for image mosaicking is an area of active research in the fields of massive data processing, computer vision, photogrammetry and remote sensing. In mosaicking applications for digital orthophoto maps (DOMs), the visual transition in mosaics is mainly caused by differences in positioning accuracy, image tone and relief displacement of high ground objects between overlapping DOMs. Among these three factors, relief displacement, which prevents the seamless mosaicking of images, is relatively more difficult to address. To minimize visual discontinuities, many optimization algorithms have been studied for the automatic selection of seamlines to avoid high ground objects. Thus, a new automatic seamline selection algorithm using a digital surface model (DSM) is proposed. The main idea of this algorithm is to guide a seamline toward a low area on the basis of the elevation information in a DSM. Given that the elevation of a DSM is not completely synchronous with a DOM, a new model, called the orthoimage elevation synchronous model (OESM), is derived and introduced. OESM can accurately reflect the elevation information for each DOM unit. Through the morphological processing of the OESM data in the overlapping area, an initial path network is obtained for seamline selection. Subsequently, a cost function is defined on the basis of several measurements, and Dijkstra’s algorithm is adopted to determine the least-cost path from the initial network. Finally, the proposed algorithm is employed for automatic seamline network construction; the effective mosaic polygon of each image is determined, and a seamless mosaic is generated. The experiments with three different datasets indicate that the proposed method meets the requirements for seamline network construction. In comparative trials, the generated seamlines pass through fewer ground objects with low time consumption.
机译:用于图像拼接的智能接缝线选择是海量数据处理,计算机视觉,摄影测量和遥感领域中积极研究的领域。在数字正射图(DOM)的镶嵌应用中,镶嵌中的视觉过渡主要是由重叠DOM之间的定位精度,图像色调和高地物体的起伏位移的差异引起的。在这三个因素中,解决图像无缝拼接的凸版位移相对较难解决。为了最小化视觉不连续性,已经研究了许多优化算法来自动选择接缝线以避免高地面物体。因此,提出了一种新的使用数字表面模型(DSM)的自动接缝线选择算法。该算法的主要思想是基于DSM中的高程信息将接缝线引导到较低的区域。鉴于DSM的海拔高度与DOM并不完全同步,因此推导并引入了一个称为正像海拔高度同步模型(OESM)的新模型。 OESM可以准确反映每个DOM单元的海拔信息。通过对重叠区域中OESM数据的形态学处理,获得了用于接缝线选择的初始路径网络。随后,基于多次测量来定义成本函数,并采用Dijkstra的算法来确定距初始网络的最小成本路径。最后,将所提出的算法用于自动接缝线网络的构建。确定每个图像的有效镶嵌多边形,并生成无缝镶嵌。通过三个不同的数据集进行的实验表明,该方法满足了接缝网络建设的要求。在比较试验中,生成的接缝线通过较少的地面物体,耗时少。

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