Over the past decade, there has been a significant increase in the use of Unmanned Aerial Vehicles (UAVs) to support a wide variety of missions, such as remote surveillance, vehicle tracking, and object detection. For problems involving processing of areas larger than a single image, the mosaicking of UAV imagery is a necessary step. Real-time image mosaicking is used for missions that requires fast response like search and rescue missions. It typically requires information from additional sensors, such as Global Position System (GPS) and Inertial Measurement Unit (IMU), to facilitate direct orientation, or 3D reconstruction approaches to recover the camera poses. This paper proposes a UAV-based system for real-time creation of incremental mosaics which does not require either direct or indirect camera parameters such as orientation information. Inspired by previous approaches, in the mosaicking process, feature extraction from images, matching of similar key points between images, finding homography matrix to warp and align images, and blending images to obtain mosaics better looking, plays important roles in the achievement of the high quality result. Edge detection is used in the blending step as a novel approach. Experimental results show that real-time incremental image mosaicking process can be completed satisfactorily and without need for any additional camera parameters.
翻译:过去十年来,使用无人驾驶航空飞行器(无人驾驶飞行器)支持远程监视、车辆跟踪和物体探测等各种任务的情况显著增加。对于涉及处理大于单一图像区域的问题,对无人驾驶航空飞行器图像进行磨擦是一个必要步骤。对于需要快速反应的特派团,例如搜索和救援任务,使用实时图像透析方法,通常需要来自其他传感器的信息,如全球定位系统和惯性测量股(IMU),以促进直接定向或3D重建方法,以恢复相机配置。本文建议采用基于无人驾驶航空的系统,实时创建递增的马赛克,不需要直接或间接的相机参数,如定向信息。受以往方法的启发,在移动过程中,从图像中提取特征,将图像之间的类似关键点匹配,找到同色矩阵和调合图像,以及混合图像以获得更好的外观,在实现高质量图像配置方面发挥着重要作用。本文提议建立一个基于无人驾驶航空飞行器的系统,用于实时创建增量的马赛克,而不需要定向信息等。根据以往的方法,在移动过程中,从图像中找到类似的关键点,从图像中找到同谱矩阵矩阵矩阵矩阵,可以令人满意地显示任何升级的结果。