Three-dimensional (3D) reconstruction based on aerial images has broad prospects, and feature matching is an important step of it. However, for high-resolution aerial images, there are usually problems such as long time, mismatching and sparse feature pairs using traditional algorithms. Therefore, an algorithm is proposed to realize fast, accurate and dense feature matching. The algorithm consists of four steps. Firstly, we achieve a balance between the feature matching time and the number of matching pairs by appropriately reducing the image resolution. Secondly, to realize further screening of the mismatches, a feature screening algorithm based on similarity judgment or local optimization is proposed. Thirdly, to make the algorithm more widely applicable, we combine the results of different algorithms to get dense results. Finally, all matching feature pairs in the low-resolution images are restored to the original images. Comparisons between the original algorithms and our algorithm show that the proposed algorithm can effectively reduce the matching time, screen out the mismatches, and improve the number of matches.

中文翻译：

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一种快速，准确，密集的航空影像特征匹配算法

基于航拍图像的三维（3D）重建具有广阔的前景，特征匹配是其中的重要一步。但是，对于高分辨率的航拍图像，使用传统算法通常会出现诸如长时间，不匹配和稀疏特征对等问题。因此，提出了一种快速，准确，密集的特征匹配算法。该算法包括四个步骤。首先，通过适当降低图像分辨率，在特征匹配时间和匹配对数之间取得平衡。其次，为实现不匹配的进一步筛选，提出了一种基于相似性判断或局部优化的特征筛选算法。第三，为了使算法更广泛地适用，我们将不同算法的结果结合起来以获得密集的结果。最后，低分辨率图像中的所有匹配特征对都将还原为原始图像。原始算法与我们算法的比较表明，所提出的算法可以有效减少匹配时间，筛选出不匹配项，提高匹配次数。