Aerial Image Stitching Based on Fusion of Geographic Coordinates and Image Features

Liangchao Guo, Huyang Zhu, Yuwei Liu, Xiaoliang Sun, Xichao Teng
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引用次数: 1

Abstract

With the rapid development of unmanned aerial vehicle technology, unmanned aerial vehicles have been widely used to obtain ground remote sensing images. Due to the limited field of view of a single remote sensing image, it is necessary to stitch the images to obtain a large-scale scene image to apply to various practical applications. This paper introduces a two-stage stitching algorithm combining geographic coordinate information and image features. The stitching of sequence images is divided into intra-line stitching and inter-line stitching. Firstly, we use geographic coordinates and image features to calculate transformation parameters between a row of images, respectively, and select an appropriate transformation matrix to stitch a single row of images based on the rotation parameters in the homography matrix. Then, we also calculate the transformation matrices between different rows of images based on the geographic coordinate information and image features, and select the appropriate transformation matrix based on the comparison of the rotation parameters in different transformation matrices. Stitching experiments are carried out for various scenarios. Compared with traditional stitching methods, the proposed method integrates information from different sources, has higher reliability, and can adapt to stitching of various types of scenarios.
基于地理坐标与图像特征融合的航空图像拼接
随着无人机技术的快速发展,无人机在获取地面遥感影像方面得到了广泛的应用。由于单幅遥感图像的视场有限,有必要对图像进行拼接,得到大尺度的场景图像,以应用于各种实际应用。介绍了一种结合地理坐标信息和图像特征的两阶段拼接算法。序列图像的拼接分为线内拼接和线间拼接。首先,利用地理坐标和图像特征分别计算行图像之间的变换参数,并根据单应性矩阵中的旋转参数选择合适的变换矩阵对单行图像进行拼接;然后,根据地理坐标信息和图像特征计算不同行图像之间的变换矩阵,并通过对不同变换矩阵中旋转参数的比较选择合适的变换矩阵。针对不同的场景进行了拼接实验。与传统拼接方法相比,该方法集成了不同来源的信息,具有更高的可靠性,能够适应不同场景的拼接。
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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