关键词: 无人机, 图像拼接, SURF, 球形校正, 单应性变换

Abstract:

In the emergency situations such as fire situation monitoring， the image of the task area is obtained through UAV aerial photography. The traditional UAV image mosaic method has the problem of low timeliness. However， the real-time splicing based on video suffers from problem of homography error accumulation and splicing interruption. This paper designs and implements a real-time video image stitching method for UAV based on spherical transformation. After spherical transformation is added， global consistency can be increased for large angle stitching. In addition， only a single homography matrix is calculated， which ensures the splicing efficiency of the algorithm on the premise of angle robustness. This paper first calculates the SURF feature description of the generated image， uses the matching algorithm to match the Speeded Up Robust Features（SURF）features between consecutive images， and then uses the random sampling consistency algorithm to screen the matching. According to the matching relationship between images， the homography transformation matrix is calculated， and the error correction sphere parameters are calculated after the homography matrix is split. After the spherical transformation correction， homography is used to complete image mosaic， and finally image fusion is carried out. The experimental results show that the method proposed in this paper can improve the timeliness of traditional image mosaic（Compared with the Shape-Preserving Half-Projective （SPHP） algorithm， the tie splicing time has been reduced from 2 345.25 ms to 1 528.6 ms， resulting in a 34.8% improvement in algorithm efficiency） and the robustness of image splicing with the change of camera angle and it can still perform well in situations with large angles and poor visual perception.

Key words: UAV, image stitching, SURF, spherical transformation, homography transformation