Abstract

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.

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