摘要
为解决存在较大程度旋转和缩放的图像配准问题,提出了一种基于尺度不变特征变换(SIFT,Scale Invariant Features Transform)的图像配准算法.采用对数极坐标变换(LPT,Log-Polar Transform)进行图像粗匹配,对图像旋转角度和缩放尺度变化量进行估计,并对图像加以校正;在粗匹配的基础上对图像进行分块,根据信息熵原理提取子块的SIFT特征和不变矩特征,构造新型的特征描述符;结合欧氏距离和Procrustes迭代算法获得图像的同名点对,并估计图像形变参数,完成图像配准.实验结果表明:该算法速度快、稳定性强,并能达到亚像素级的匹配精度.
To resolve the problem of large angle and large scale image registration, an improved approach based on scale invariant feature transform （SIFT） is proposed. The log-polar technique was applied to estimate the parameters of rotations scales between reference image and sensed image. The images were segmented into sub-blocks and six candidates of sub-blocks were extracted according to information entropy, where SIFT features and moment features were fused to form a new feature descriptor. The image registration result was calculated from the matching points which were obtained by combining the Euclidean distance and the algorithm of iterative procrustes. The experimental results show that the proposed method is fast with high-precision.
出处
《北京航空航天大学学报》
EI
CAS
CSCD
北大核心
2010年第9期1121-1124,1130,共5页
Journal of Beijing University of Aeronautics and Astronautics
基金
航空科学基金资助项目(20085113007)
关键词
图像配准
尺度不变特征变换
矩特征
image registration
scale invariant feature transform
moment features
