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Article

Robust Mosaicking of Lightweight UAV Images Using Hybrid Image Transformation Modeling

1
Unit of Arctic Sea-Ice Prediction, Korea Polar Research Institute (KOPRI), Incheon 21990, Korea
2
Department of Geoinformatic Engineering, Inha University, Incheon 21990, Korea
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(6), 1002; https://doi.org/10.3390/rs12061002
Received: 23 January 2020 / Revised: 13 March 2020 / Accepted: 18 March 2020 / Published: 20 March 2020
(This article belongs to the Special Issue Remote Sensing Images Processing for Disasters Response)
This paper proposes a robust feature-based mosaicking method that can handle images obtained by lightweight unmanned aerial vehicles (UAVs). The imaging geometry of small UAVs can be characterized by unstable flight attitudes and low flight altitudes. These can reduce mosaicking performance by causing insufficient overlaps, tilted images, and biased tiepoint distributions. To solve these problems in the mosaicking process, we introduce the tiepoint area ratio (TAR) as a geometric stability indicator and orthogonality as an image deformation indicator. The proposed method estimates pairwise transformations with optimal transformation models derived by geometric stability analysis between adjacent images. It then estimates global transformations from optimal pairwise transformations that maximize geometric stability between adjacent images and minimize mosaic deformation. The valid criterion for the TAR in selecting an optimal transformation model was found to be about 0.3 from experiments with two independent image datasets. The results of a performance evaluation showed that the problems caused by the imaging geometry characteristics of small UAVs could actually occur in image datasets and showed that the proposed method could reliably produce image mosaics for image datasets obtained in both general and extreme imaging environments. View Full-Text
Keywords: lightweight UAV; image mosaic; imaging geometry; tiepoint area ratio lightweight UAV; image mosaic; imaging geometry; tiepoint area ratio
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MDPI and ACS Style

Kim, J.-I.; Kim, H.-c.; Kim, T. Robust Mosaicking of Lightweight UAV Images Using Hybrid Image Transformation Modeling. Remote Sens. 2020, 12, 1002. https://doi.org/10.3390/rs12061002

AMA Style

Kim J-I, Kim H-c, Kim T. Robust Mosaicking of Lightweight UAV Images Using Hybrid Image Transformation Modeling. Remote Sensing. 2020; 12(6):1002. https://doi.org/10.3390/rs12061002

Chicago/Turabian Style

Kim, Jae-In, Hyun-cheol Kim, and Taejung Kim. 2020. "Robust Mosaicking of Lightweight UAV Images Using Hybrid Image Transformation Modeling" Remote Sensing 12, no. 6: 1002. https://doi.org/10.3390/rs12061002

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