Open AccessResearch on Mosaic Method of UAV Low-altitude Remote Sensing Image based on SIFT and SURF
Author(s) -
Hang Zhu,
Jinhui Yu,
Cui Zhang,
Shu Liu
Publication year - 2022
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2203/1/012027
Subject(s) - image stitching , scale invariant feature transform , computer vision , artificial intelligence , computer science , low altitude , panorama , remote sensing , aerial image , mosaic , drone , feature (linguistics) , field (mathematics) , image (mathematics) , altitude (triangle) , geography , mathematics , linguistics , philosophy , geometry , archaeology , biology , pure mathematics , genetics
Unmanned aerial vehicle (UAV) low-altitude remote sensing image stitching is a new technology to promptly grasp the lodging situation of rice. The effect of image stitching depends on different application scenarios, so that it is necessary to explore low-altitude remote sensing image stitching algorithm suitable for rice lodging monitoring. The research adopts SIFT (Scale invariant feature transform) and SURF (Speeded up robust features) feature detection algorithms to conduct mosaic experiments based on drone images of a rice field in Dehui City, Jilin Province. The results demonstrate that the image stitching technology based on surf algorithm possesses better real-time performance, and the panorama obtained can well reflect the lodging condition of rice field. This research can provide technical reference for the actual lodging monitoring of rice field.