Research on UAV Image Mosaic Based on Improved AKAZE Feature and VFC Algorithm

Q. Yan, Qianwen Li, Tongkang Zhang
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引用次数: 1

Abstract

Aiming at the problem of low matching efficiency of traditional AKAZE algorithm, an improved algorithm is proposed that combines AKAZE and FREAK algorithms. First, AKAZE is used to extract feature points to ensure the accuracy of feature detection, and then the FREAK operator is used to calculate the descriptor, and then the VFC algorithm is used to perform accurate matching to improve the matching efficiency, and finally the weighted fusion algorithm is used to fuse the image. The research results show that compared with the traditional SIFT, the improved AKAZE algorithm improves the feature extraction time by about 1.11s, and the improved AKAZE algorithm in terms of computing descriptor efficiency increases the time by 1.32s than the SIFT and AKAZE algorithms, which can get higher The accuracy and matching results of the UAV realize rapid and seamless splicing of UAV images.
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基于改进AKAZE特征和VFC算法的无人机图像拼接研究
针对传统AKAZE算法匹配效率低的问题,提出了一种结合AKAZE算法和FREAK算法的改进算法。首先利用AKAZE提取特征点,保证特征检测的准确性,然后利用FREAK算子计算描述子,然后利用VFC算法进行精确匹配,提高匹配效率,最后利用加权融合算法对图像进行融合。研究结果表明,与传统SIFT相比,改进的AKAZE算法特征提取时间提高了约1.11s,改进的AKAZE算法在计算描述子效率方面比SIFT和AKAZE算法提高了1.32s,能够获得更高的无人机精度和匹配结果,实现了无人机图像的快速无缝拼接。
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