基于局部重叠区域的无显著特征图像配准算法

Non-saliency Feature Image Registration Algorithm Based on Local Overlapping Region

针对沙漠、戈壁等特征不显著场景在配准过程中存在快速性、精确性等问题,提出一种基于局部重叠区域的特征不显著图像配准方法。首先利用图像标记对待配准图像进行预处理增强其特征,接着通过多相机三维投影对多幅待配准图像重叠区域进行预算,并采用图像掩膜和图像分割技术将重叠区域分割出来,最后对重叠区域使用ORB+GMS(Oriented Brief-Grid-based Motion Statistics for Fast)融合算法进行配准,完成多幅图像的配准工作。基于图像重叠区域的配准避免了无显著特征图像在进行整体配准时精确性低的缺点,并且由于是局部配准,相较于全局配准拥有更快的配准速度。对比传统配准方法和本文提出的改进配准方法,实验结果显示,本文提出的改进方法配准精度在传统配准方法的基础上提升了28%,同时,算法具有更高的鲁棒性和实时性。

Aiming at the problems of rapidity and accuracy in the registration process of scenes with non-saliency features such as desert and Gobi,this paper proposes a non-saliency feature image registration method based on local overlapping region. Firstly,the image to be registered is preprocessed by using the image mark to enhance its features,then the overlapping area of multiple images to be registered is budgeted through multi camera three-dimensional projection,and the overlapping area is segmented by using the image mask and the image segmentation technology. Finally,the overlapping area is registered by ORB+GMS(Oriented Brief-Grid-based Motion Statistics for Fast)fusion algorithm to complete the registration of multiple images. The registration based on the image overlapping region avoids the disadvantage of low accuracy in the overall registration of images with non-saliency features. Due to the local registration,it has a faster registration speed than the global registration. Compared the traditional registration method with the improved registration method proposed in this paper,the experimental results show that the registration accuracy of the improved method proposed in this paper is improved by 28% on the basis of the traditional registration method. The algorithm has higher robustness and real-time performance.