Development and Comparative Analysis of Mapping Quality Prediction Technology Using Orientation Parameters Processed in UAV Software

초록

Commercial Unmanned Aerial Vehicle (UAV) image processing software products currently used in the industry provides camera calibration information and block bundle adjustment accuracy. However, they provide mapping accuracy achievable out of input UAV images. In this paper, the quality of mapping is calculated by using orientation parameters from UAV image processing software. We apply the orientation parameters to the digital photogrammetric workstation (DPW) for verifying the reliability of the mapping quality calculated. The quality of mapping accuracy was defined as three types of accuracy: Y-parallax, relative model and absolute model accuracy. The Y-parallax is an accuracy capable of determining stereo viewing between stereo pairs. The Relative model accuracy is the relative bundle adjustment accuracy between stereo pairs on the model coordinates system. The absolute model accuracy is the bundle adjustment accuracy on the absolute coordinate system. For the experimental data, we used 723 images of GSD 5 cm obtained from the rotary wing UAV over an urban area and analyzed the accuracy of mapping quality. The quality of the relative model accuracy predicted by the proposed technique and the maximum error observed from the DPW showed precise results with less than 0.11 m. Similarly, the maximum error of the absolute model accuracy predicted by the proposed technique was less than 0.16 m. © 2019 The authors.

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