针对具有复杂场景的航拍图像提出了一种基于图分割理论与Hausdorff距离的多分辨率影像匹配方法。在高斯金字塔图像模型中，低分辨率的图像通过图分割方法，充分考虑图像中的局部和全局的信息，提取到稳定和完整的图像区域边界，并以区域边界作为待匹配的曲线。再通过计算曲线的统计特性作为图像间待匹配特征，并由信号相关的度量方法粗估计出图像间全局仿射变换参数。利用粗估计的参数在高分辨率层次上进一步通过基于Hausdorff距离的匹配方法搜索到精确的变换参数。实验结果表明，该方法在较大变形和强噪音干扰的情况下对复杂场景的图像也能有效地完成匹配。

This paper proposes a multiresolution image matching framework based on graph cut theory and Hausdorff distance for aerial images with complex scene. After the establishment of Gaussian pyramid image model, we adopt graph cut segmentation in the lowest level and extract robust and integral region boundaries with full consideration of both local and global information. The output region boundaries will be used as candidate curves for further matching. After calculating the statistical information of curves as matching features, we can evaluate the coarse affine transformation parameters using simple correlation measure. The coarse affine transformation parameters estimated can be further used to search in fine levels based on the Hausdorff distance measure. The experiment shows that our method can overcome great distortion and suppress strong noise, and successfully match the images of complex scenes.