Fast Super-Resolution Reconstruction for Video-Based Pattern Recognition

A fast super-resolution reconstruction algorithm is proposed in this paper. It uses a new reduced cost function to produce images of higher resolution from low resolution frame sequences. The result photos can greatly promote the recognition rate, and reduce the hardware requirements for imaging system. Blind reconstruction experiments using real videos of moving vehicles showed that the proposed algorithm can efficiently enhance the quality of plate images, while its computational cost is quite lower compared with other super-resolution methods. It can be applied in real-time systems.