Abstract:The low-resolution iris images contain less effective information, and their actual application will affect the recognition accuracy.Image super-resolution reconstruction technology can solve this problem effectively.Based on the difference between structure and texture of iris images, this paper proposes a dual-channel network structure which is suitable for iris images.We design dual-path residual dense blocks to extract deep features and use post-magnification strategy to reconstruct the final image.Experiments are conducted on the CASIA-IrisV4 image library.Comparied with classic methods, the reconstructed images have clearer structure and richer texture details.The result of the iris matching experiments shows the EER are all optimal, which means the reconstructed iris images reach a better recognition performance.