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用于低成本无人机应用的FLIR VUE PRO热成像相机快速几何校准的测试场概念

The Conception of Test Fields for Fast Geometric Calibration of the FLIR VUE PRO Thermal Camera for Low-Cost UAV Applications.

作者信息

Fryskowska-Skibniewska Anna, Delis Paulina, Kedzierski Michal, Matusiak Dominik

机构信息

Department of Imagery Intelligence, Faculty of Civil Engineering and Geodesy, Military University of Technology, 00-908 Warsaw, Poland.

出版信息

Sensors (Basel). 2022 Mar 23;22(7):2468. doi: 10.3390/s22072468.

Abstract

The dynamic evolution of photogrammetry led to the development of numerous methods of geometric calibration of cameras, which are mostly based on building flat targets (fields) with features that can be distinguished in the images. Geometric calibration of thermal cameras for UAVs is an active research field that attracts numerous researchers. As a result of their low price and general availability, non-metric cameras are being increasingly used for measurement purposes. Apart from resolution, non-metric sensors do not have any other known parameters. The commonly applied process is self-calibration, which enables the determining of the approximate elements of the camera's interior orientation. The purpose of this work was to analyze the possibilities of geometric calibration of thermal UAV cameras using proposed test field patterns and materials. The experiment was conducted on a FLIR VUE PRO thermal camera dedicated to UAV platforms. The authors propose the selection of various image processing methods (histogram equalization, thresholding, brightness correction) in order to improve the quality of the thermograms. The consecutive processing methods resulted in over 80% effectiveness on average by 94%, 81%, and 80 %, respectively. This effectiveness, for no processing and processing with the use of the filtering method, was: 42% and 38%, respectively. Only high-pass filtering did not improve the obtained results. The final results of the proposed method and structure of test fields were verified on chosen geometric calibration algorithms. The results of fast and low-cost calibration are satisfactory, especially in terms of the automation of this process. For geometric correction, the standard deviations for the results of specific methods of thermogram sharpness enhancement are two to three times better than results without any correction.

摘要

摄影测量学的动态发展催生了众多相机几何校准方法,这些方法大多基于构建具有可在图像中区分特征的平面靶标(场)。无人机热成像相机的几何校准是一个活跃的研究领域,吸引了众多研究人员。由于价格低廉且普遍可得,非量测相机越来越多地用于测量目的。除分辨率外,非量测传感器没有任何其他已知参数。常用的方法是自校准,它能够确定相机内方位的近似元素。这项工作的目的是分析使用所提出的测试场图案和材料对无人机热成像相机进行几何校准的可能性。实验在一款专用于无人机平台的FLIR VUE PRO热成像相机上进行。作者提出选择各种图像处理方法(直方图均衡化、阈值处理、亮度校正)以提高热成像图的质量。连续的处理方法平均有效率分别达到94%、81%和80%,超过80%。对于不进行处理和使用滤波方法进行处理的情况,有效率分别为42%和38%。只有高通滤波没有改善所得结果。在所选择的几何校准算法上验证了所提出方法和测试场结构的最终结果。快速且低成本校准的结果令人满意,尤其是在该过程的自动化方面。对于几何校正,热成像图锐化增强特定方法结果的标准偏差比未进行任何校正的结果好两到三倍。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/28aa/9003006/fb788c783c82/sensors-22-02468-g001.jpg

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