Department of Remote Sensing, Photogrammetry and Imagery Intelligence, Institute of Geodesy, Faculty of Civil Engineering and Geodesy, Military University of Technology, 01-476 Warsaw, Poland.
Sensors (Basel). 2018 Jul 26;18(8):2433. doi: 10.3390/s18082433.
In the last few years, it has been possible to observe a considerable increase in the use of unmanned aerial vehicles (UAV) equipped with compact digital cameras for environment mapping. The next stage in the development of photogrammetry from low altitudes was the development of the imagery data from UAV oblique images. Imagery data was obtained from side-facing directions. As in professional photogrammetric systems, it is possible to record footprints of tree crowns and other forms of the natural environment. The use of a multi-camera system will significantly reduce one of the main UAV photogrammetry limitations (especially in the case of multirotor UAV) which is a reduction of the ground coverage area, while increasing the number of images, increasing the number of flight lines, and reducing the surface imaged during one flight. The approach proposed in this paper is based on using several head cameras to enhance the imaging geometry during one flight of UAV for mapping. As part of the research work, a multi-camera system consisting of several cameras was designed to increase the total Field of View (FOV). Thanks to this, it will be possible to increase the ground coverage area and to acquire image data effectively. The acquired images will be mosaicked in order to limit the total number of images for the mapped area. As part of the research, a set of cameras was calibrated to determine the interior orientation parameters (IOPs). Next, the method of image alignment using the feature image matching algorithms was presented. In the proposed approach, the images are combined in such a way that the final image has a joint centre of projections of component images. The experimental results showed that the proposed solution was reliable and accurate for the mapping purpose. The paper also presents the effectiveness of existing transformation models for images with a large coverage subjected to initial geometric correction due to the influence of distortion.
在过去的几年中,人们已经可以观察到使用配备紧凑型数码相机的无人机 (UAV) 进行环境测绘的使用量有了相当大的增加。从低空摄影测量发展的下一阶段是开发来自无人机倾斜图像的图像数据。图像数据是从侧面方向获得的。与专业摄影测量系统一样,可以记录树冠和其他自然环境形式的足迹。使用多相机系统将显著降低无人机摄影测量的主要限制之一(特别是在多旋翼无人机的情况下),即减少地面覆盖面积,同时增加图像数量、增加飞行线数量并减少一次飞行中成像的表面。本文提出的方法基于在无人机的一次飞行中使用多个机头相机来增强成像几何形状以进行测绘。作为研究工作的一部分,设计了一个由多个相机组成的多相机系统,以增加总视场 (FOV)。因此,将有可能增加地面覆盖面积并有效地获取图像数据。获取的图像将进行拼接,以限制映射区域的总图像数量。作为研究的一部分,对一组相机进行了校准,以确定内部定向参数 (IOP)。接下来,提出了使用特征图像匹配算法进行图像对齐的方法。在所提出的方法中,图像以这样的方式组合,即最终图像具有组成图像的投影中心的公共中心。实验结果表明,所提出的解决方案对于测绘目的是可靠和准确的。本文还介绍了在初始几何校正后(由于失真的影响)对具有大覆盖范围的图像使用现有变换模型的有效性。