An end-to-end network for multiple scattering media imaging

In this paper, we propose an end-to-end neural network abbreviated as TCNN to solve the blind phase retrieval problem in multiple scattering imaging. TCNN is a kind of auto-encoder with a transform layer, which acts as a bridge between transforming domains. Compared to double phase retrieval method, TCNN can directly estimate the image from those phaseless measurements through the nonlinear network structure. During training, the parameters of TCNN are updated by the adaptive moment estimation algorithm Adam. Numerical experiments show that TCNN can recover images with comparable quality to that of state-of-the-art methods. Moreover, TCNN hugely reduces the time cost for recovering images once the training procedure is completed.