一种改进的APAP影像匹配算法

针对无人机影像匹配时易出现影像重影、透视失真和耗时较长等问题，本文提出了一种改进的APAP算法。该算法首先利用SIFT算法选取特征点，通过改进RANSAC算法去除误匹配点；然后根据APAP算法对影像进行网格划分，求每个网格的单应性矩阵，并对单应性矩阵进行线性化；最后根据线性化的单应性矩阵进行影像匹配，单应性矩阵的线性化不仅对影像匹配时产生的重影现象有较好的削弱作用，而且能减少非重叠区域的透视失真。试验结果表明，本文方法在匹配效率和匹配效果方面效果显著。

An improved APAP image matching algorithm

Aiming at the problems of image ghosting, perspective distortion and long time consumption when UAV image matching, this paper proposes an improved APAP algorithm. First, this algorithm uses SIFT algorithm to select feature points and removes the mismatch point by improving RANSAC algorithm. Then, according to the APAP algorithm, the image is meshed, the homography matrix of each mesh is obtained, and the homography matrix is linearized. Finally, the image matching is performed according to the linearized homography matrix, and the homography matrix is Linearization not only weakens the ghosting phenomenon caused by image matching, but also reduces the perspective distortion of non-overlapping regions. The experimental results show that the proposed method is effective in matching efficiency and matching effect.