基于局部不变性特征的无人机影像特征点提取  

UAV Image Feature Extraction Based on Local Invariant Features

作　　者：甘洁[1] 

机构地区：[1]福建省基础地理信息中心,福建福州350003

出　　处：《地理空间信息》2015年第3期47-49,9,共3页Geospatial Information

摘　　要：针对不同尺度影像特征点提取的问题,提出了基于局部不变性特征的算法。以经典的SIFT特征点检测算法为参照,详细分析了SURF特征点检测算法,并通过实验从特征点提取速度和适应性2个方面对Moravec、Harris、SUSAN、SIFT、SURF等算法进行了比较。结果表明,SURF算法提取影像特征点的速度较快、适应性较强。According to the problems of different scales image feature extraction, this paper proposed an algorithm based on local invariant features. Referring to the classic SIFT algorithm, the paper analyzed the most popular SURF feature detection algorithm, and compared Moravec algorithm, Harris algorithm, SUSAN algorithm, SIFT algorithm with SURF algorithm in feature extraction speed and adaptability through experimental study. Experimental results show that the SURF algorithm is better than other algorithm in extraction speed and adaptability.

关 键 词：影像 特征点提取 算法 局部不变性特征 SIFT SURF 

分 类 号：P231.5[天文地球—摄影测量与遥感]