摘要
针对发生较大角度旋转及平移时图像配准精度不高,图像配准对局部形变和光照较为敏感的问题,本文提出了基于直线和SURF特征的图像分区域配准算法。首先利用Hough变换实现图像的粗配准;然后对图像进行分区,在子区域内利用SURF算子求取变换模型参数,完成图像的配准。实验表明该方法可用于红外与可见光图像的配准,与传统方法相比,本方法能够在图像存在大角度旋转和平移时实现高精度配准,且在图像存在局部形变及光照不均时精度较好。
An algorithm of image registration based on Hough transform and SURF features is proposed, to solve the problem that the accuracy is low in image registration when large angle rotation and translation occur, and the problem that traditional method is sensitive about local deformation and uneven illumination. Firstly, Hough transform is used to extract straight line features to estimate the rotation and translation parameters to achieve a rough image registration. Then, the image is divided into a few parts, and the SURF is used to do the precisely match sub-regionally. Finally, matching parameters are calculated and the registration is accomplished. Experiments show that the method can be used in the registration of IR and VI images, compared with traditional methods, and this method can achieve higher accuracy in the presence of a large angle rotation and translation and get a better result when localized deformation or uneven illumination is occurring.
出处
《光电工程》
CAS
CSCD
北大核心
2015年第4期68-74,共7页
Opto-Electronic Engineering
基金
国家自然科学基金(61340056)资助项目
