Single image orientation of UAV's imagery using orthogonal projection model

M. Tjahjadi, F. Agustina
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引用次数: 11

Abstract

A Perspective based image restitution for registering and processing UAV's images is widely known in photogrammetry and computer vision communities. Despite its reliability to compute all necessary parameters to model 3D objects, however it is less suitable to process images which have a very narrow angular field of view. An interested feature on images captured from a very distant imaging object or by a long focal length camera occupies a small portion of the field of view. The perspective model produces unstable results or singular outcomes if the image's field of view is less than 10 degrees. The captured ground features are usually located on small clusters which have very narrow field of view. Therefore, stable registration results are barely achieved. On the other hand, the orthogonal projection model was claimed to give stable results in such situation, particularly for a remote sensing imagery and a non-topographic photogrammetry. This paper demonstrates a feasibility of the orthogonal model based space resection to perform a featured based UAV image registration using surveyed ground control points. Using a minimum of 4 points to reach the field of view of around 6 degrees on each cluster, a five-group of collected clusters is computed. Whilst the perspective model produces erratic results, the orthogonal model gives better solution of exterior orientation parameters in all parts of the image.
利用正交投影模型实现无人机图像的单像定向
基于视角的无人机图像复原配准和处理方法在摄影测量学和计算机视觉领域得到了广泛的应用。尽管它可以可靠地计算所有必要的参数来建模三维物体,但是它不太适合处理具有非常窄角度视场的图像。从非常远的成像物体或由长焦距相机捕获的图像上的感兴趣的特征占据了视场的一小部分。如果图像的视场小于10度,透视模型会产生不稳定的结果或奇异的结果。捕获的地面特征通常位于视野非常狭窄的小集群上。因此,很难获得稳定的配准结果。另一方面,正交投影模型声称在这种情况下,特别是对于遥感图像和非地形摄影测量,可以提供稳定的结果。本文论证了基于正交模型的空间交会利用地面测控点进行特征图像配准的可行性。使用至少4个点来达到每个星团约6度的视野,计算收集到的5组星团。虽然透视模型产生的结果不稳定,但正交模型可以更好地解决图像所有部分的外部方向参数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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