采用局域像素匹配的随机抽样一致改进算法

Improved random sampling consensus algorithm using local pixel matching

为提高图像拼接的配准精度和稳健性,提出基于局域像素匹配的随机抽样一致改进算法。在完成尺度不变特征变换算子或其他算子图像特征提取、特征匹配之后,利用独立于特征匹配点的局域像素,通过参考图像局域像素与映射的待拼接图像局域像素匹配,优选4对最佳特征匹配点,确定最佳单应矩阵。实验结果表明:与随机抽样一致经典算法相比,该方法未明显增加计算耗时,单应矩阵更准确,图像拼接稳健性更好。

In order to improve the registration precision and robustness of image splicing,an improved random sampling consensus algorithm based on local pixel matching was proposed.After completing image feature extracting and feature matching with the scale invariant feature transform operator or other operator,using the local pixels that are independent of feature matching points,then the optimal configuration of the four pairs of feature matching points,and the best homography matrix were determined by matching the local pixel of the reference image with the mapped local pixel of the image to be stitched.The experimental results show that,compared with the classical random sampling consensus algorithm,the computation time is close,the homography matrix is more accurate,and the image mosaic is more robust.