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Image Stitching Method of Aerial Image Based on Feature Matching and Iterative Optimization

This paper studies the mismatch of the overlap areas during the stitching process of Unmanned Aerial Vehicle (UAV) remote sensing images. For solving this problem, the feature points are filtered first by combining double matching with the Random sampling consensus (RANSAC) method. Secondly, to ensure the consistency of the projection relationship between each image and panoramic photograph, we propose a local stitching method. In order to avoid the mistake of image tilt caused by perspective changes accumulate as the number of images increases, we have established an image rotation coordinate system and limited the relationship between images to translation and rotation. The relative position of the coordinate origin is used to represent the translation distance, and the optimal rotation angle is solved by iteration. Finally, the overlapping parts of the image are fused by linear weighting. It is verified through the experimental results that the method proposed in this paper can guarantee faster processing speed and higher processing accuracy under the condition of a large number of images, thereby achieving an ideal stitching effect.