A Robust Space-time Super-resolution Reconstruction Algorithm Based on Multiple Video Sequences

To improve the temporal-spatial resolution of video, a space-time super-resolution reconstruction algorithm using L1 norm minimization is proposed, and space-time regularization based on the total variation is utilized. The proposed algorithm can increase the resolution both in time and in space by using multiple low resolution video sequences of the same scene obtained at sub-pixel and sub-frame misalignments. This algorithm does not require large matrixes directly constructed, which reduces greatly the memory requirements. Experimental results show the effectiveness of the algorithm and verify the robustness of the algorithm to errors in imaging model estimation.