SEI: TRUE Orthoimage Generation of High-Resolution UAV Video for Forest Fire Surveillance

该项目正在开发利用森林地区无人驾驶航空器视频数据生成高分辨率真视频正射影像的技术。在生成真实视频正射图像方面存在许多技术挑战。为应对这些挑战，该项目正在建立严格的摄影测量自校准模型，以便：（a）消除树木造成的地形位移;（B）补偿房屋和道路等遮挡物体，这些物体通常是消防期间生命存在的重要指标;提高了无人机传感器外方位参数和透镜畸变确定的精度，同时解决了这两个问题。该项目的目标是：（1）为森林火灾专家、分析人员、决策人员和消防人员提供高度准确可靠的森林火灾监测数据，以提高森林火灾监测效率，改善森林火灾管理，减轻森林火灾灾害;（2）增加和扩展无人机视频图像的适用性和可用性，以快速响应时间紧迫的事件和自然灾害。该项目的更广泛影响包括：（1）所提出的方法对美国未来无人机应用战略在监视，实时响应时间关键事件，环境监测等领域具有重要意义;（2）所提出的技术可以直接用于美国工业，因此该项目显着增加和扩展了商用无人机的可用性。

This project is developing techniques for high-resolution true video orthoimage generation from Unmanned Aerial Vehicle (UAV) video data in forest areas. There are many technical challenges in generating true video orthoimages. To address these challenges, the project is establishing a rigorously photogrammetric self-calibration model to: (a) remove the relief displacement caused by trees; (b) compensate for the occluded objects, such as houses and roads, which are usually important indicators of life existence during firefighting; and (c) increase the accuracy of UAV sensor's exterior orientation parameters and lens distortion determination, which are solved simultaneously. The objectives of the project are: (1) to provide highly accurate and reliable forest fire surveillance data for forest fire experts, analysts, decision-makers and firefighters in order to increase the efficiency of monitoring forest fires to improve forest fire management and mitigate forest fire disasters; (2) to increase and extend the applicability and usability of the UAV video images in fast response to time-critical events and natural disasters. The broader impacts of the project include: (1) the proposed methods are significantly beneficial to the future U.S. UAV application strategy in areas such as surveillance, real-time response to time-critical events, environmental monitoring, etc; (2) the proposed technique can be directly used by U.S. industry, thus the project significantly increases and extends the usability of commercial UAVs.