基于自适应筛选Harris角点检测的快速图像配准算法

针对传统Harris角点检测算法的图像配准过程计算量大、速度慢等问题,提出一种快速预筛选Harris角点检测算法。首先通过FAST算法快速排除大量非特征点,再通过抑制半径解决FAST角点聚簇现象,然后在FAST角点邻域内筛选出Harris角点,最后采用Brute-Force匹配方式得到精准匹配。实验结果表明:所提改进算法不仅提高了角点检测速度而且减少了冗余角点数量,在图像配准过程中有效提高了配准速度与精度,配准效果良好。

Fast Image Registration Algorithm Based on Adaptive Screening Harris Corner Detection

Aiming at the problems of large amount of calculation and slow speed in the process of image registration for traditional Harris corner detection algorithm, in this paper, a fast pre-screening Harris corner detection algorithm was proposed. Firstly, a large number of non-feature points were quickly eliminated with the FAST algorithm, and then the clustering of FAST corners was solved by suppressing the radius. Secondly, Harris corners in the neighborhood of FAST corners were selected, and finally Brute-Force matching was used to realize accurate matching. Experimental results show that the proposed algorithm not only improves the corner detection speed but also reduces the number of redundant corners, and it effectively improves the registration speed and accuracy, realizing a good registration effect.