基于SIFT改进的无人机图像匹配算法

Improved UAV Image Matching Algorithm Based on SIFT

针对无人机图像匹配时间较长的问题,提出了一种基于SIFT改进的无人机图像匹配算法。引入了FAST算法检测角点,它能快速通过比较中心像素点和一定领域内像元的灰度值以判断是否为角点,从而提高算法的速度。同时,为了弥补FAST算法在高斯差分金字塔上搜索的不足,使用了基于Ostu和GA的图像分割算法对图像进行分割,对分割图像构建高斯金字塔,在高斯金字塔上进行特征点搜索。实验结果表明,与传统的SIFT算法相比,改进算法提高了无人机图像匹配的速率和正确率。

Aiming at the problem that UAV image matching takes long time,an improved UAV image matching algorithm based on SIFT is proposed.By introducing the FAST corner point detection algorithm,which can quickly judge whether it is a corner point by comparing the gray value of the center pixel and the pixel in a certain field,thus improving the speed of the algorithm.At the same time,in order to make up for the shortcomings of the FAST algorithm in searching on the Gaussian difference pyramid,an algorithm based on Ostu and GA is used to segment the image,the Gaussian pyramid is constructed for the segmented image,and the feature points are searched on the Gaussian pyramid.Experimental results show that compared with the traditional SIFT algorithm,the new algorithm improves the speed and accuracy of UAV image matching.