A new productive framework for point-based matching of oblique aircraft and UAV-based images,The Photogrammetric Record

当前位置： X-MOL 学术 › Photogramm. Rec. › 论文详情

Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)

A new productive framework for point-based matching of oblique aircraft and UAV-based images
The Photogrammetric Record ( IF 2.1 ) Pub Date : 2021-07-23 , DOI: 10.1111/phor.12374
Sıla Bas ₁ , Ali Ozgun Ok ₁

Affiliation

A novel productive framework for point-based feature matching of oblique aircraft and UAV imagery is presented. The proposed framework makes use of the powerful AKAZE descriptor for feature extraction and an iterative scheme is developed to construct as many tentative matches as possible. During the iterations, cross checks, together with Lowe’s nearest-next distance ratio test, are used to filter erroneous matches. In order to extract putative matches from the tentative matches, three robust approaches, including graph-cut RANSAC, are evaluated along with the epipolar constraint enforced between the two datasets. The developed framework was validated using the ISPRS image orientation benchmark dataset and yielded successful results in terms of matching precision, even for some difficult cases. The results also outperformed the results of previously developed approaches in the same context.

中文翻译：

一种新的基于点的倾斜飞机和基于无人机的图像匹配的高效框架

提出了一种用于斜向飞机和无人机图像基于点的特征匹配的新型高效框架。所提出的框架利用强大的 AKAZE 描述符进行特征提取，并开发了一种迭代方案来构建尽可能多的暂定匹配。在迭代过程中，交叉检查与 Lowe 的最近距离比测试一起用于过滤错误的匹配。为了从暂定匹配中提取假定匹配，评估了三种稳健的方法，包括图形切割 RANSAC，以及在两个数据集之间强制执行的对极约束。开发的框架使用 ISPRS 图像方向基准数据集进行了验证，并在匹配精度方面取得了成功，即使是在一些困难的情况下也是如此。

更新日期：2021-09-19

点击分享查看原文

点击收藏

阅读更多本刊最新论文