Phase imaging always deals with the problem of phase invisibility when capturing objects with existing light sensors. However, there is a demand for multiplane full intensity measurements and iterative propagation process or reliance on reference in most conventional approaches. In this paper, we present an end-to-end compressible phase imaging method based on deep neural networks, which can implement phase estimation using only binary measurements. A thin diffuser as a preprocessor is placed in
