摘要
针对大面积图像配准鲁棒性和实时性差的问题,提出一种基于子图特征的快速图像配准算法.提取对比度强、结构清晰的子图,依次采用改进的Harris检测算法提取角点,4阶梯度向量对角点进行描述,欧氏距离进行特征向量相似性度量,并利用最小二乘法进行变换参数估计,采用双线性插值法重建待配准图像.实验结果表明,子图法不但比大图法的配准精度高,配准速度快,而且这种思想可以推广到FMT和MI配准法等其他配准算法.
For the poor robustness and real-time problem of large area image registration, a newfast image registration algorithm based on the sub-image features was proposed. First, the sub-image with strong contrast, clear structure was extracted. And then sequentially, the improvedHarris detector was taken to extract the corners, the 4-order gradient vectors was used todescribe the corners, the improved Euclidean distance was taken to measure eigenvectors＇similarity, and the transformation parameters were estimated with Least Squares. Lastly,bilinear interpolation was used to reconstruct the registered image. Experimental results showthat the registration accuracy and registration speed of the proposed method are higher than thewhole image method, and this idea can be extended to other registration algorithm such as FMTand MI registration methods.
出处
《北京理工大学学报》
EI
CAS
CSCD
北大核心
2015年第7期744-749,共6页
Transactions of Beijing Institute of Technology
基金
国家自然科学基金资助项目(61171194)
新起点计划项目(zk10201305)
关键词
子图
HARRIS角点
梯度向量
变换参数估计
sub image
Harris eorner
gradient vector
transformation parameters estimation
