Super-resolution reconstruction for far-field beam profile based on deep learning

In order to obtain more information of far-field beam profile from limited measured data, a novel super-resolution reconstruction method for far-field beam profile based on deep learning is proposed. In this paper, the high/low resolution spot image sample is obtained by simulation, the EDSR neural network training model is used to study the mapping relationship between high/ low resolution spot images, and the super-resolution reconstruction method based on deep learning is realized. The experimental results show that the super-resolution reconstruction based on deep learning is superior to the conventional algorithms in PSNR and SSIM.