KOPRI Repository

Robust Mosaicking of Lightweight UAV Images Using Hybrid Image Transformation Modeling

Cited 1 time in wos
Cited 1 time in scopus
Metadata Downloads
Title
Robust Mosaicking of Lightweight UAV Images Using Hybrid Image Transformation Modeling
Other Titles
복합 영상변환모델링을 이용한 소형 무인기 영상들의 강인 모자이킹
Authors
Kim, Jae-In
Kim, Hyun-cheol
Kim, Taejung
Subject
Environmental Sciences & Ecology; Geology; Remote Sensing; Imaging Science & Photographic Technology
Keywords
lightweight UAV; image mosaic; imaging geometry; tiepoint area ratio
Issue Date
2020-03
Citation
Kim, Jae-In, Kim, Hyun-cheol, 김태정. 2020. "Robust Mosaicking of Lightweight UAV Images Using Hybrid Image Transformation Modeling". REMOTE SENSING, 12(6): 1002-1002.
Abstract
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.
URI
https://repository.kopri.re.kr/handle/201206/11978
DOI
http://dx.doi.org/10.3390/rs12061002
Appears in Collections  
2020-2020, Study on remote sensing for quantitative analysis of changes in the Arctic cryosphere (20-20) / Kim, Hyun-cheol (PE20080)
Files in This Item

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

Browse