Automatic Aerial Image RegistrationWithout Correspondence

Yingen Xiong, Francis K. H. Quek
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引用次数: 24

Abstract

This paper presents an approach for registering aerial images taken at different time, viewpoints, or heights. Different from conventional image registration algorithms, our approach does not need image matching or correspondence. In this approach, we extract a number of corner features as the basis for registration and create a number of image patches with the corner points as centers on both reference and observed images. In order to let the corresponding patches cover same scene, we use a circle which the radius can be changed as the shape of the image patches. In this way, the image patches can handle the case in which there are rotation and scaling at the same time between reference and observed images. With the orientation differences of patches between these two images, we create an angle histogram with a voting procedure. The rotation angle between the two images can be determined by seeking the orientation difference that corresponds to the maximum peak in the histogram. Once we get the rotation angle, we seek back for the two corresponding patches which the value of orientation difference is the same as the rotation angle. The ratio of radii of these two patches is the value of the scaling. The proposed approach can handle the situation of large rotation and scaling between reference and observed images. It is applied to real aerial images and the results are very satisfying.
自动航空图像配准无对应
本文提出了一种在不同时间、视点或高度拍摄的航拍图像的配准方法。与传统的图像配准算法不同,我们的方法不需要图像匹配或对应。在这种方法中,我们提取一些角点特征作为配准的基础,并在参考图像和观察图像上以角点为中心创建一些图像补丁。为了使对应的小块覆盖同一个场景,我们使用一个半径可以改变的圆作为图像小块的形状。这样,图像补丁可以处理参考图像和观测图像之间同时存在旋转和缩放的情况。利用两幅图像之间patch的方向差异,通过投票程序创建角度直方图。通过寻找直方图中最大峰对应的方向差来确定两幅图像之间的旋转角度。一旦得到旋转角度,我们再寻找方向差值与旋转角度相同的两个对应的patch。这两个patch的半径之比就是缩放值。该方法可以处理参考图像和观测图像之间的大旋转和缩放情况。将该方法应用于实际航拍图像,取得了令人满意的效果。
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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