VSP-Based Warping for Stitching Many UAV Images

Image stitching aims to mosaic individual images together to build a broader panorama, wherein image registration is the most critical step. In this step, all sub-images are normally brought into alignment by warping functions, each of which is often parameterized by rotation, scale and translation...

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Bibliographic Details
Published in:	IEEE transactions on geoscience and remote sensing 2023-01, Vol.61, p.1-1
Main Authors:	He, Lin, Li, Xinyi, He, Xinguo, Li, Jun, Song, Shuang, Plaza, Antonio
Format:	Article
Language:	eng
Subjects:	Alignment Autonomous aerial vehicles Computation Error analysis Image registration Image stitching Jacobian matrices Measurement Optimization panorama Regularization Shape Stitching Translation UAV images Unmanned aerial vehicles Vectors VSP Warping
Online Access:	Get full text
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Summary:	Image stitching aims to mosaic individual images together to build a broader panorama, wherein image registration is the most critical step. In this step, all sub-images are normally brought into alignment by warping functions, each of which is often parameterized by rotation, scale and translation factors. Existing methods usually have to estimate such parameters simultaneously, which incur the problems of unstable and time-consuming computations, especially for stitching large number of UAV images. In this paper, a novel stitching method using vector shape preserving (VSP)-based warping is proposed, which is especially suitable for stitching many UAV images. We innovatively construct warping vectors and involve them to measure registration error to preserve vector shapes, which allows separately dealing with a re-plane stage and a translation stage. Additionally, a novel scale regularization processing connected to the warping is designed for the tractable computation. Our method is able to achieve low computational cost, high alignment accuracy and meanwhile valid real-world interpretation. Experimental results on four real-world UAV image datasets validate the excellent performance of our method.
ISSN:	0196-2892 1558-0644