针对传统图像拼接方法处理速度慢、效率低、无法满足高分辨率图像快速准确拼接的需要,提出一种基于ORB特征的高分辨率图像拼接改进算法。首先在ORB特征点提取的基础上,采用汉明距离进行快速粗匹配;然后基于渐进采样一致性(PROSAC)算法对匹配点对进行优化,去除误匹配点对之后,求解图像变换矩阵;最后采用渐入渐出加权融合算法对图像重叠区域进行融合,去除拼接痕迹。实验结果表明,相较于传统算法,本文算法不仅在处理速度上具有明显优势,而且匹配准确度更高,能够对高分辨率图像实现快速准确的拼接。

The traditional image stitching method has low processing speed, is inefficient, and unable to meet the requirements for fast and accurate stitching of high-resolution images. This paper proposes an improved algorithm of high-resolution image stitching based on Oriented FAST and Rotated BRIEF (ORB) features. First, based on the ORB feature point extraction, the Hamming distance is used for fast rough matching. Then, the matching point pair is optimized based on the progressive sampling consistency (PROSAC) algorithm. Next, after removing the mismatch point pair, the image transformation matrix is solved. Finally, the weighted fusion algorithm is used to fuse the overlapping areas of the image to remove the stitching traces. Experimental results show that the proposed algorithm not only has more advantages in processing speed but also has a higher matching accuracy compared to traditional algorithms. In addition, it can realize fast and accurate stitching of high-resolution images.