【摘要】 为了提高图像拼接速度并满足高分辨率图像的实时拼接需求，提出了一种基于ORB(Oriented Fast and Rotated Brief)算法和MSAC(M-estimator Sample Consensus)算法的快速图像拼接方法。ORB算法特征匹配速度快，能够满足实时性要求。首先采用ORB算法进行图像特征点提取；然后，采用MSAC算法对匹配点对进行优化，剔除图像拼接中的伪匹配点对，通过正确的匹配点对求解图像变换矩阵；最后，采用双线性插值融合算法消除可见接缝并去除拼接痕迹。实验结果表明，本文方法在保证图像拼接质量的同时具有更快的拼接速度。更多还原

【Abstract】 In this paper we propose a fast image stitching method based on the ORB(Oriented Fast and Rotated Brief)algorithm and the MSAC(M-estimator Sample Consensus)algorithm to improve the speed of image stitching and meet the real-time stitching requirements of high-resolution images.The ORB algorithm has extremely fast feature matching speed, meeting the real-time requirements.Therefore, the ORB algorithm is first adopted for feature point extraction.Subsequently, the MSAC algorithm is employed to optimize the matched point pairs, eliminating false matching point pairs in image stitching, and solves the image transformation matrix based on the correct matching point pairs.Finally, the bilinear interpolation fusion algorithm is used to eliminate visible seams and stitching artifacts.The experimental results demonstrate that our method ensures image stitching quality while achieving faster computational speed.更多还原