针对超分辨率图像重建的病态问题，设计了一种新的自适应超分辨率图像序列重建算法。该算法在L1范数重建框架下，利用金字塔算法与Lucas-Kanade算法相结合的方法实现图像配准，获得亚像素的运动估计；通过引入移位算子给出了基于正交梯度算子的正则项的实现方法，并从自适应的角度选择正则化参数，最后通过最速下降法求解模型的目标泛函最小值。结果表明：对于模拟实验和真实序列实验，该方法相比于样条插值算法、Tikhonov正则化算法、双边全变差重建算法都有一定的优势，能够取得更好的复原效果，并且由于正则项较为简单，重建所需时间相对减少。

For the ill-posed problem of super resolution reconstruction, a new adaptive algorithm for image sequence was proposed. The new algorithm was based on the framework of L1-norm. In the new algorithm, the pyramidal algorithm coupled with Lucas-Kanade algorithm was used for images registration to obtain the sub-pixel motion estimation. Displacement operator was introduced to achieve the regular term based on the orthogonal gradient operator and the regularization parameter was determined adaptively. Finally, the steepest descent method was used to solve the minimum of the constraint equation. The simulation experiments and the true sequence experiments show that the method proposed has advantages over spline interpolation, Tikhonov reconstruction and bilateral total variation reconstruction. On the one hand it can provide better reconstructing results, on the other hand the reconstruction time is reduced at the same time since the regularization item is simple.