Two noise-robust axial scanning multi-image phase retrieval algorithms based on Pauta criterion and smoothness constraint

We proposed two noise-robust iterative methods for phase retrieval and diffractive imaging based on the Pauta criterion and the smoothness constraint. The work is to address the noise issue plaguing the application of iterative phase retrieval algorithms in coherent diffraction imaging. It is demonstrated by numerical analysis and experimental results that our proposed algorithms have higher retrieval accuracy and faster convergence speed at a high shot noise level. Moreover, they are proved to hold the superiority to cope with other kinds of noises. Due to the inconvenience of conventional iteration indicators in experiments, a more reliable retrieval metric is put forward and verified its effectiveness. It should be noted that the proposed methods focus on exploiting the longitudinal diversity. It is anticipated that our work can further expand the application of iterative multi-image phase retrieval methods.