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A fast super-resolution reconstruction algorithm designed for license plate recognition is proposed in this paper. It uses a new reduced cost function to produce images of higher resolution from low resolution frame sequences. Computational cost required in this algorithm is much lower compared with other methods. The effectiveness of the proposed algorithm is demonstrated through blind reconstruction experiments with real videos, whose result images are nearly equivalent to those yielded by classical MAP-based approaches. The presented algorithm can be applied in real-time recognition systems to improve their performances, and to reduce the requirement of imaging hardware.