Super-resolution Image Reconstruction Algorithm Based on Sub-Pixel Shift

This paper studies the problem of multi-frame image super-resolution reconstruction. The process of image degradation is modeled by using the first-order Taylor expansion based on sub-pixel. Then the energy minimization function is established and the graph-cut algorithm is chosen to solve the energy minimization. In order to confirm this algorithm, we obtain the low resolution images by two ways: simulating image degradation and taking photos. By comparing the 4 × 4 times reconstruction results, it is shown that this algorithm is valid not only for simulation of low resolution images but also for real images. Besides, experimental results show that this algorithm possesses good anti-interference ability of noise.