摘要
针对无人机空中姿态不稳定,其拍摄影像存在倾斜、曝光不均匀等缺点,采用常规的影像匹配方法效果不佳,甚至无法匹配,而SIFT算法对图像几何变形、分辨率差异、旋转等有较好适应性。利用SIFT算法对无人机影像进行特征点的提取,并采用最小二乘算法对影像进行精匹配。同时,为了减少拼接过程中误差的传播,提出了分块拼接方法。实验结果表明:SIFT算法适用于无人机影像匹配,在精匹配过程中采用最小二乘算法能够有效地剔除误匹配,并减小了时间复杂度和空间复杂度。
The matching effect of conventional methods is poor, sometimes even not matching due to the instability of Unmanned Aerial Vehicle （UAV） air gesture and the defects such as the existence of its tilted capture images, uneven exposure. SIFT algorithm has a good adaptability for image geometric distortion, resolution differences and rotation, etc. The SIFT algorithm is introduced to extract the feature points of UAV images, and the least-squares algorithm is used to match the images precisely. Moreover, the block splicing method is proposed to reduce the error spread in the process of stitching. The experimental results show that SIFT image matching algorithm has a good adaptability in matching UAV images. The matching error can be eliminated effectively to introduce the least-squares algorithm in the matching process. What is more, the time and space complexity can be obviously reduced.
出处
《光电工程》
CAS
CSCD
北大核心
2011年第2期122-126,共5页
Opto-Electronic Engineering
基金
"十一五"国家科技支撑计划重大项目(2006BAJ05A13)
