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Feature Correspondence and Semi-Automatic Ground Truthing for Airborne Data Collection

机译:机载数据采集的特征对应和半自动地面真相

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A significant amount of airborne data has been collected in the past and more is expected to be collected in the future to support airborne landmine detection research and evaluation under various programs. In order to evaluate mine and minefield detection performance for sensor and detection algorithms, it is essential to generate reliable and accurate ground truth for the location of the mine targets and fiducials present in raw imagery. The current ground truthing operation is primarily manual, which makes the ground truthing a time consuming and expensive exercise in the overall data collection effort. In this paper, a semi-automatic ground-truthing technique is presented which reduces the role of the operator to a few high-level input and validation actions. A correspondence is established between the high-contrast targets in the airborne imagery called the image features, and the known GPS locations of the targets on the ground called the map features by imposing various position and geometric constraints. These image and map features may include individual fiducial targets, rows of fiducial targets and triplets of non-collinear fiducials. The targets in the imagery are established using the RX anomaly detector. An affine or linear conformal transformation from map features to image features is calculated based on feature correspondence. This map-to-image transformation is used to generate ground-truth for mine targets. Since accurate and reliable flight-log data is currently not available, one-time specification of a few parameters like flight speed, flight direction, camera resolution and specification of the location of the initial frame on the map is required from the operator. These parameters are updated and corrected for subsequent frames based on the processing of previous frames. Image registration is used to ground-truth images which do not have enough high-contrast fiducials for reliable correspondence. A GUI called SemiAutoGT developed in MATLAB for the ground truthing process is briefly discussed. Results are presented for ground-truthing of the data collected under the Lightweight Airborne Multispectral Minefield Detection (LAMD) program.
机译:过去已经收集了大量的空中数据,并有望在将来收集更多的数据,以支持各种计划下的空中地雷探测研究和评估。为了评估传感器和检测算法的防雷和雷场检测性能,必须生成可靠和准确的地面真相,以对原始图像中存在的防雷目标和基准进行定位。当前的地面实况操作主要是手动操作,这使得地面实况成为整个数据收集工作中既耗时又昂贵的练习。在本文中,提出了一种半自动的地面实战技术,该技术将操作员的角色简化为一些高级输入和验证操作。通过施加各种位置和几何约束,在航空影像中的高对比度目标(称为图像特征)与目标在地面上的已知GPS位置(称为地图特征)之间建立了对应关系。这些图像和地图特征可能包括单个基准目标,基准目标行和非共线基准的三元组。使用RX异常检测器确定图像中的目标。根据特征对应关系计算从地图特征到图像特征的仿射或线性共形变换。这种地图到图像的转换用于为地雷目标生成地面真相。由于目前尚无法获得准确和可靠的飞行日志数据,因此需要操作员一次性指定一些参数,例如飞行速度,飞行方向,相机分辨率以及地图上初始帧的位置。基于先前帧的处理,针对后续帧更新和校正这些参数。图像配准用于真实图像,这些图像没有足够的高对比度基准以实现可靠的通信。简要讨论了在MATLAB中为地面实况处理开发的名为SemiAutoGT的GUI。给出了根据轻型机载多光谱雷场探测(LAMD)程序收集的数据的真实结果。

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