利用改进ORB算法的无人机影像匹配

doi:10.13474/j.cnki.11-2246.2024.0121

测绘通报 ›› 2024, Vol. 0 ›› Issue (1): 126-130,149.doi: 10.13474/j.cnki.11-2246.2024.0121

利用改进ORB算法的无人机影像匹配

李冰, 赖祖龙, 孙杰, 丁开华

中国地质大学地理与信息工程学院, 湖北武汉 430074

收稿日期:2023-04-18 出版日期:2024-01-25 发布日期:2024-01-30
通讯作者: 赖祖龙。E-mail:laizulong@cug.edu.cn
作者简介:李冰(1999—),男,硕士生,研究方向为摄影测量与图像处理等。E-mail:libing2016@cug.edu.cn
基金资助:
国家自然科学基金(42174012)

UAV image matching based on improving the ORB algorithm

LI Bing, LAI Zulong, SUN Jie, DING Kaihua

School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China

Received:2023-04-18 Online:2024-01-25 Published:2024-01-30

摘要/Abstract

摘要： 针对ORB算法面对光照变化时提取特征点数量不稳定及特征点定位精度仅有像素级的问题,本文设计了一种基于前背景对比的自适应阈值方法,且结合现有的亚像素定位方法对ORB算法进行了改进。同时为了避免RANSAC算法因需人工设置阈值导致误差的问题,将MAGSAC++算法引入特征匹配过程,用于误匹配剔除。试验结果表明,改进算法能够获取数量较多的匹配数目,对光照变化具有更好的稳健性,且匹配精度提高了7%以上。

关键词: ORB算法, 特征提取, 自适应阈值, 影像匹配, 误匹配剔除

Abstract: This paper addresses the problem of unstable feature point extraction and pixel-level feature point localization accuracy faced by the ORB algorithm when encountering changes in illumination. To improve the ORB algorithm, a self-adaptive threshold method based on foreground-background contrast is proposed in conjunction with existing sub-pixel localization techniques. In order to avoid the error caused by the need for manual threshold setting in RANSAC algorithm, this paper introduces the MAGSAC++algorithm into the feature matching process for false match elimination. Experimental results show that the improved algorithm can obtain a larger number of matches, has better robustness to changes in illumination, and improves matching accuracy by at least 7%.

Key words: ORB algorithm, feature extraction, adaptive threshold, image matching, mismatch removal

中图分类号:

李冰, 赖祖龙, 孙杰, 丁开华. 利用改进ORB算法的无人机影像匹配[J]. 测绘通报, 2024, 0(1): 126-130,149.

LI Bing, LAI Zulong, SUN Jie, DING Kaihua. UAV image matching based on improving the ORB algorithm[J]. Bulletin of Surveying and Mapping, 2024, 0(1): 126-130,149.

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利用改进ORB算法的无人机影像匹配

UAV image matching based on improving the ORB algorithm

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