中文摘要：

图像配准是超分辨率图像重建过程中的一个重要步骤。在实际应用中，Keren算法在旋转角度大于6。时存在较大的配准误差，且其计算复杂度随着图像平移量增大将增长数倍；Vandewalle算法在角度配准中存在一定的优势，但整体配准精度不如Keren算法。针对两种配准算法存在的问题，利用测量平差中附有限制条件的间接平差原理，提出一种改进算法。利用Vandewalle算法解算出图像间的旋转参数和平移参数，将旋转参数作为Keren算法参数的限制条件，并以平移参数作为初始值，代入Keren配准公式中，依据附有限制条件的间接平差原理，迭代求出平移参数的改正值。研究表明，该算法成功避免了大角度旋转情况下Keren算法因角度的泰勒级数展开所带来的误差，提高了配准精度，且具有更好的重建效果。

英文摘要：

Image registration is an important step in the process of super-resolution image reconstruc- tion. In practical applications when the rotation angle is greater than 6°, the Keren algorithm will cre- ate greater registration error, and its computational complexity as the amount of image shift will grow several times larger. Considering the Vandewalle algorithm, its registration under certain rotation an- gle conditions is a certain advantage, but the overall registration accuracy is lower than the Keren al- gorithm. Aiming to solve the problems of two existing registration algorithms, we combined Adjust- ment of Indirect observations with Constraints to proposed an improved image registration method. The proposed algorithm calculates the rotation parameters and translation parameters using the Vandewalle algorithm between the images. Then, the rotation parameters are included as the known values used in Keren algorithm, while the translation parameters are taken as observations, Using the adjustment of indirect observations with constraints iterative shift parameter correction values we came to the final registration parameters. Our studies show that the algorithm avoids errors stemming from the Taylor series expansion of angle when using the Keren algorithm In the case of large angles, improving the registration accuracy with better reconstrNetinn r l,~