Liu Shu-Bin, Wang Jin-Hui, Yuan Rong-Ying, Zhao Wu-Xiang, Li Lei, Wang Qiong-Hua
School of Electronics and Information Engineering, Sichuan University, Chengdu, 610065, China.
School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, 100191, China.
Sci Rep. 2020 Jul 24;10(1):12389. doi: 10.1038/s41598-020-69353-9.
In this paper, we propose a real time, ultrahigh accuracy and full-field-of-view (RUF) algorithm for full field of view (FOV) imaging system. The proposed algorithm combines rough matching and precise matching method to stitch multiple images with the whole FOV in short time and high imaging quality. In order to verify real-time imaging effect of RUF algorithm, we also fabricate a multi-camera imaging system which includes 19 independent cameras. And the experiment result practically illustrates that full-FOV system can achieve good performances under a near-limiting FOV of 360° × 240° with low distortion, meanwhile, optical resolution reaches up to 95 megapixels. 100% registration-accuracy RUF algorithm for imaging in one second can be widely applied to any optical imaging engineering field with large FOV, such as remote sensing imaging, microscopy imaging, monitoring system engineering fields and so on.
在本文中,我们针对全视场(FOV)成像系统提出了一种实时、超高精度和全视场(RUF)算法。所提出的算法结合了粗匹配和精确匹配方法,能够在短时间内以高成像质量拼接多个具有整个视场的图像。为了验证RUF算法的实时成像效果,我们还制造了一个包含19个独立相机的多相机成像系统。实验结果实际表明,全视场系统在近360°×240°的极限视场下能够实现低失真的良好性能,同时光学分辨率高达9500万像素。每秒成像的100%配准精度RUF算法可广泛应用于任何具有大视场的光学成像工程领域,如遥感成像、显微镜成像、监测系统工程领域等。