Xu Jing, Zhao Dandan, Ren Zhengwei, Fu Feiran, Sun Yuxin, Fang Ming
School of Computer Science and Technology, Changchun University of Science and Technology, Changchun 130022, China.
Zhongshan Institute of Changchun University of Science and Technology, Zhongshan 528403, China.
J Imaging. 2022 Dec 25;9(1):5. doi: 10.3390/jimaging9010005.
In this paper, we propose an aerial images stitching method based on an as-projective-as-possible (APAP) algorithm, aiming at the problem artifacts, distortions, or stitching failure due to fewer feature points for multispectral aerial image with certain parallax. Our method incorporates accelerated nonlinear diffusion algorithm (AKAZE) into APAP algorithm. First, we use the fast and stable AKAZE to extract the feature points of aerial images, and then, based on the registration model of the APAP algorithm, we add line protection constraints, global similarity constraints, and local similarity constraints to protect the image structure information, to produce a panorama. Experimental results on several datasets demonstrate that proposed method is effective when dealing with multispectral aerial images. Our method can suppress artifacts, distortions, and reduce incomplete splicing. Compared with state-of-the-art image stitching methods, including APAP and adaptive as-natural-as-possible image stitching (AANAP), and two of the most popular UAV image stitching tools, Pix4D and OpenDroneMap (ODM), our method achieves them both quantitatively and qualitatively.
在本文中，我们提出了一种基于尽可能投影（APAP）算法的航空影像拼接方法，旨在解决因具有一定视差的多光谱航空影像特征点较少而导致的伪像、失真或拼接失败问题。我们的方法将加速非线性扩散算法（AKAZE）融入APAP算法。首先，我们使用快速稳定的AKAZE提取航空影像的特征点，然后，基于APAP算法的配准模型，添加线保护约束、全局相似性约束和局部相似性约束以保护图像结构信息，从而生成全景图。在多个数据集上的实验结果表明，所提出的方法在处理多光谱航空影像时是有效的。我们的方法可以抑制伪像、失真，并减少不完全拼接。与包括APAP和自适应尽可能自然图像拼接（AANAP）在内的现有最先进图像拼接方法，以及两种最流行的无人机图像拼接工具Pix4D和OpenDroneMap（ODM）相比，我们的方法在定量和定性方面均实现了更好的效果。
