【摘要】 针对大规模显微图像拼接中的误差累积问题,提出了一种新的图像拼接模型。首先利用基于区域的对准方法,按照由粗到细的分层对准策略,提高图像对准的速度与准确性。然后,利用所有重叠图像对的对准约束,建立了一种图像拼接模型,并通过求解线性方程组得到拼接模型的最优解,从而实现了大规模显微图像的自动拼接。从实验结果看,该算法有效地消除了误差的累积效应,获得了理想的拼接效果。更多还原

【Abstract】 Image mosaicing is an important technology in the field of image processing and computer vision. To eliminate error accumulation in the mosaicing of large-scale microscope images, a new algorithm was proposed. The algorithm solved the local alignment parameters with the hierarchical model to increase the robustness and speed of image alignment. Then it constructed the global image alignment model and gets the optimization solution by solving a set of linear equations. Experiments show that this algorithm effectively eliminates error accumulation and gets the desired result.更多还原