AN OPTIMAL IMAGE SELECTION METHOD TO IMPROVE QUALITY OF RELATIVE RADIOMETRIC CALIBRATION FOR UAV MULTISPECTRAL IMAGES

Shin, J.; Cho, Y.; Lee, H.; Yoon, S.; Ahn, H.; Park, C.; Kim, T.

Radiometric calibration has become important pre-processing with increasing use of unmanned aerial vehicle (UAV) images in various applications. In order to convert the digital number (DN) to reflectance, vicarious radiometric calibration is widely used including relative radiometric calibration. Some UAV sensor systems can measure irradiance for precise relative radiometric calibration. However, most of UAV sensor systems cannot measure irradiance and therefore precise relative radiometric calibration is needed to produce reflectance map with vicarious calibration. In this study, an optimal image selection method is proposed to improve quality of relative radiometric calibration. The method, relative calibration by the optimal path (RCOP), uses filtered tie points acquired in geometric calibration based on selection optimal image by Dijkstra algorithm. About 100 multispectral images were acquired with a RedEdge-M camera and a fixed-wing UAV. The reflectance map was produced using RCOP and vicarious calibration using ground reference panels. A validation data was processed using irradiance for precise relative radiometric calibration. As a result, the RCOP method showed root mean square error (RMSE) of 0.03–0.10 reflectance to validation data. Therefore, the proposed method can be used to produce precise reflectance map by vicarious calibration.

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Shin, J. / Cho, Y. / Lee, H. / et al: AN OPTIMAL IMAGE SELECTION METHOD TO IMPROVE QUALITY OF RELATIVE RADIOMETRIC CALIBRATION FOR UAV MULTISPECTRAL IMAGES. 2020. Copernicus Publications.

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