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Drone Image Stitching Guided by Robust Elastic Warping and Locality Preserving Matching | IEEE Conference Publication | IEEE Xplore

Drone Image Stitching Guided by Robust Elastic Warping and Locality Preserving Matching


Abstract:

Image stitching stitches multiple overlapping images into a seamless image according to the corresponding geometric relationship between the reference and source images. ...Show More

Abstract:

Image stitching stitches multiple overlapping images into a seamless image according to the corresponding geometric relationship between the reference and source images. In this study, the parallax-tolerant image stitching method based on robust elastic warping is applied to the stitching of drone images, and locality-preserving feature matching is used to effectively remove outliers from the drone images. The method can be divided into three stages, namely, locality-preserving feature matching, robust elastic warping, and global projectivity preservation. First, a set of high- precision point matching is provided for a drone image, and local matching is used. Second, the robust elastic warping function eliminates the parallax error, and the input image is distorted according to the calculated deformation on the grid plane. Finally, the global projectivity-preserving method is applied to obtain high-precision result panoramas. Experiments on several sets of drone images demonstrate that our method can generate better panoramas over the competitors.
Date of Conference: 28 July 2019 - 02 August 2019
Date Added to IEEE Xplore: 14 November 2019
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Conference Location: Yokohama, Japan

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